tl;dr

When I consider Sandia separated from the tsunami of change sweeping over society, clarity is found. Moving to Sandia was a huge mistake professionally. I did not fit in there, and my career was much less than what it could have been because of that. I’m an extroverted rebel, and Sandia is introverted conformity. Hierarchy is rigid and matters most of all. Information and organization is tightly controlled and fragmented. At Los Alamos, my career moved in a coherent direction. My knowledge and expertise were valued. At Sandia, the same career was an incoherent mess. My knowledge and expertise are greatest in an area that expresses the culture of Sandia most pathologically. It was hopeless from the outset unless I was willing to change; I was not. Some people have incredible careers at Sandia. It is right for them. It was not for me. It was a good job with a good salary and benefits. Moving was right for my family. For my family, living in Albuquerque was better; Sandia was just the route there.

“Healey’s First Law Of Holes: When in one, stop digging.” ― Denis Healey

The Perspective I needed

My last post did wonders for my ability to write about my time at Sandia. In a way, it works sort of like the math technique called separation of variables. I managed to pull my time at Sandia out of the stream of modernity, our current societal crisis. There I could look at it alone. I cannot write this in the same way either. The core of the narrative arc does not match what happened in school or Los Alamos. The coherence of direction and growth disappeared at Sandia. This essay will be organized by theme rather than chronology. It is the only way to make sense of this.

The other major realization was that Sandia would always be compared with Los Alamos. Sandia does it to itself. Sandia has a huge chip on its shoulder. Los Alamos birthed Sandia from itself. Los Alamos had this important gestational role in my career. It birthed me; it was where I had my technical childhood and adolescence; it’s where I came to adulthood. The changes due to the passage of time make this comparison unfair to Sandia. The 1980’s and 1990’s still had the momentum of the post-WW2-Cold War support of science. Los Alamos and Sandia of that time were much better than today. Virtually every institution in the country was better. Today, the institutions are under assault. and most in free fall. I lived this precipitous decline at Sandia. This warps my perspective considerably.

The thing is that when I walked in the door, I was full of optimism and hope. This comparison could have been a good one; it could have actually ended up with Sandia being better. In pure hindsight, that’s an impossibility. This impossibility is mostly the result of who I am. I realize that my innate personality and talents, my motivation, are all ill-suited for Sandia. All of these are more well-suited and better taken advantage of at Los Alamos. I should say the Los Alamos when I was there before the scandals that distorted it.

One of my issues with Sandia is that I tried to make it work and express optimism about it at the start. I was not willing to ingest the message that it was the wrong place for me after I made this big change. I moved the family; I bought a home; I settled into life. All of these things skewed me towards trying to make it work. I really wasn’t honest with myself about what was going on.

This also enticed my friend Jim Kamm to come to Sandia as well. This was a direct consequence of the optimistic hope that Sandia could be better than Los Alamos. I had expressed this optimism to him. Jim had a different calculus around life at Sandia, and he tried to make it work. Increasingly, Sandia made it harder and harder for him to continue working. Part of it was his life. He insisted on staying at his home in Santa Fe, which made the commute precarious. Changes at Sandia made it impossible for him to reasonably get to work. He eventually returned to Los Alamos and was there for a short time. Finally, being fed up, retiring, and moving to France. My sense was that his departure had as much to do with changes in America that he found unacceptable and troubling.

I should focus on those things about Sandia, good and bad, that didn’t work for me.

“I’ve always believed there are moments in our lives which can be defined as a transition between the before and after, between the cause and the effect.” ― Benjamin X. Wretlind

What Went Wrong?

“Follow the urge to transition from one phase of your life to the next. Whether this is inside or outside work, it’s time for intentional transformation to take place.” ― Robin S. Baker

Sandia is a very collaborative place, but only on a small scale. At first, I felt a deep sense of commitment and collaboration within the department I was working in. I was working on overhauling the numerical solution of hydrodynamics in the code ALEGRA. It was work I was perfect for. I also accepted the rather extreme limitations of the code. It was deeply imperfect. This was challenging, and it forged a tight team. In that time, I felt deep accomplishments that are a source of pride.

Shortly after I arrived at Sandia, we had a crisis. Our funding was under threat because the code was unreliable for our primary customer. This was the Army, not DOE or ASC. In short, we needed to improve or else. The code was too fragile and slow for its users. We were handed a death sentence by them unless we made progress. I was a key part of the plan. With focus and joint effort, we succeeded in a massive improvement. We improved the code and its robustness massively. The Army was overjoyed with our work. It stands as one of the greatest achievements of my career. The team was essential to success, and it should have bonded us. Inside my department, it was celebrated. Outside the department, it was totally meh. My Center and Sandia as a whole didn’t even know it happened, much less care. This is the origin of all that went wrong.

The problem with Sandia is that collaboration at a large scale is utterly and completely discouraged. There is no broader institutional identity aside from “we’re engineers, damn it”. Sandia is more of a federation of centers and projects under a common banner. Our great work with ALEGRA meant nothing to the Lab. Cynically, I would say because the money was so little. There’s truth in that. In a sense, Sandia works like the United States before the Civil War. This is where each state has great power, and the federal government is weak. It is completely different than Los Alamos with its “federal” model, and the lack of recognition disappointed me.

If you move or change jobs at Sandia, it is virtually like changing employers. Not in the sense that your benefits or basic rules of employment change. Rather, your interactions and your friends completely change. You no longer interact with the same people. Over a short time, it eventually turns into a completely different community. Any achievements in your former organization are pretty meaningless. People who succeed are those who stay put. You are primarily recognized by your organizational achievements (for a technical person). Cross-organizational achievements are mostly recognized by managers. Money and program building are the most prized. Technical achievements are rarely viewed as important.

Sandia is very fractured, and this is paralleled by its attitude towards information sharing. Information is not shared by default. Once you get outside your organization or project, the information becomes attenuated and hard to get a hold of. One of the key cultural notions of Sandia is “need to know”. It is applied very strictly, far more strictly than the way it was applied at Los Alamos. At Los Alamos, the sharing and collaboration happened on a large scale. Your identity was the whole lab, and achievements in other organizations meant something if you moved. This led to substantial coherence of my career there, even while changing organizations. At Sandia, changing organizations was professional suicide. Working on a small project with little funding growth was also bad for you, too. Politics and money are the lifeblood of success.

This distinction, the innately tribal nature of identity at Sandia, is my second greatest issue at the laboratory. This follows the diminished role of technical achievement and mastery. I found that my professional life there was far poorer. Rarely enriched by the breadth of scientists, disciplines, and expertise that I encountered at Los Alamos. This is part of a lack of generosity. The information rules and time-keeping norms hurt generosity. The lack of a common identity was even more toxic in this regard. I had more intense interactions locally, but once you got past your local organization, things narrowed and became incredibly superficial. This drove a deep sense of dissatisfaction that grew with each passing year. By the time I had been at Sandia for five years, it felt like this was the wrong place for me. This would coincide with other forces in my life.

One of the key things that I came to realize immediately is that Sandia is extremely conscious of hierarchy. If you are at a certain level, you’re expected to remain silent unless you’re spoken to. If you’re the lowest-ranking person in a room, your silence is presumed to be complete unless you’re called on. There’s always a deference to the people of rank. I saw this clearly immediately. It was a fairly complete departure from the free-wheeling culture of Los Alamos. Politics was much more important than Sandia. The issue is that the political nature of Sandia was very introverted and subtle. Conversely, Los Alamos was an extroverted politics, where it was a free-for-all and very open. Rank mattered little at Los Alamos, especially as a scientist. Managers were treated with modest disdain. Their rank did matter somewhat. Sandia inverted this completely.

Let me be clear: in the grand scheme of things, both Los Alamos and Sandia are exceptional technical organizations. Los Alamos is more scientific. Sandia is an engineering organization first and foremost. Both places do exceptionally high-quality work and hold themselves to very high standards. This is compared with the vast majority of other government labs and universities. The number of places in the USA better than Sandia or Los Alamos is a small number of exceptional ones. Sandia is far better administratively, too. They have bureaucratic competence that Los Alamos can only dream of.

The problem is that those standards are slipping with time. The decline is profound. The sort of professional excellence I aspire to work towards is no longer supported. I would say, in broad terms, no longer supported by either organization today. It is certainly not encouraged by current organizational behavior or societal norms. Both places are in deep decline. This reflects the science and engineering in the United States dropping in quality. Both Los Alamos and Sandia reflect that decline strongly.

“Self-awareness is the foundation of meaningful change. Know thyself.” ― Binod Shankar

Politics and Conflict

In relative terms, both places are quite good, even exceptional by the standards of the day. In terms of what the country needs and the sort of standard we should expect from them, both places leave very much to be desired. The decline in science in the United States is across the board. Perhaps the only exception right now is in terms of AI. Our lead there is precarious in the extreme and threatened by a national strategy that is foolish at best. Massive cuts in fundamental foundational research will produce a diminished status in AI as well. The combination of declining institutions and lower funding is the recipe for long-term failure. We can argue that the USA is still the leader. Even if true, that lead will evaporate soon.

At Sandia. technical achievements, while important, mattered little compared to your political stance. There was a reward for political or programmatic success. Often, the people who succeeded the best were either quietly supportive of their management’s decisions or actively acted as a mouthpiece for what the managers wanted to do. Being a tactical leader or doing work of high technical quality was unimportant and would lead to no substantial success. This, along with my area of work, limited my professional achievement in terms of institutional recognition.

Where Los Alamos has (had) an open and aggressive politics. At Los Alamos, beliefs are shared and debated in a vigorous and public way. Sandia is far more behind the scenes, with Machiavellian actors doing things that are unseen. Often manifesting in extremely manipulative ways. In a brutal sense, in Los Alamos, you get stabbed, but they stab you from the front. You know who’s killing you. At Sandia, you get stabbed in the back. The result’s the same; you’re stabbed, but at least at Los Alamos, you knew where the perpetrator was. If you are me, the Los Alamos model of open and identified conflict was far better than being undercut without knowing who was your undoing. Los Alamos is rude and in your face. Sandia is polite and tends to keep their opinions to themselves, or rather, talk behind your back and spread rumors. Sandia is a passive-aggressive culture to a fault.

To make another analogy, this time using warfare, Los Alamos had open battles. These would be like the sort of pitched battles between the Spartans and the Persians, or trench warfare in World War One, or the grand sweeping blitzkriegs and armored combats of World War Two. Sandia was more like cyber and drone warfare: everything hidden. No less dangerous, but subtle, unseen, and rarely admitted openly by those engaged in it. Conflicts are unavoidable. Warfare is never good, but the kind that you wish to engage in is a matter of personal taste. In retrospect, my personal taste was slanted towards the open conflict, which felt honest and true and less like lying. I’m not a good poker player. Sandia is much more like poker than a boxing match.

My Personal Response

All of this wasn’t fully realized or even articulated, perhaps until now. By the time I’d been at Sandia a little over ten years, these factors started to weigh on me. I knew I didn’t fit in, and if I was going to be true to myself, I would never fit in. In retrospect, I began truly realizing this around my 50th birthday. This became a time of a bit of a midlife crisis. It had some distinct manifestations.

“One of the most dangerous things that you can do is to change yourself before you know yourself.” ― Craig D. Lounsbrough

It was perhaps most acutely marked by getting my very first tattoo shortly after I turned 50. Having one tattoo, I didn’t stop there, and more than twenty-five tattoos later, I’m still at it. My pace has slowed, but I did design a pretty massive one to commemorate my retirement. I could argue that getting tattoos is a distinctly Albuquerque thing. Albuquerque is one of the more heavily tattooed places in the United States. I think in a deeper way, this was simply an outward sign of rebellion against who I was forced to be at Sandia. I needed to express myself. I needed an outlet. Part of the outlet was the tattoos. The other part is the blog, but that story is deeper. If you look at them, these tattoos tell a story of what I care about, what is important in my life.

The blog and other writing outlets are a huge outlet. The idea was hatched in my 2013 performance review (the year of my 50th birthday). The blog was a response to a frustrating professional development plan. It had become clear that I already knew more professionally than was useful at Sandia. If I wasn’t going to be a manager (and I wasn’t), professional development was moot. I did want to write more, and the blog was the way to do it regularly. Writing is also tantamount to thinking clearly. Both better writing and thinking are invaluable professionally. Their benefits are clear more broadly in life. It seemed like a great idea. In a different world, or ten years earlier, it was.

I started writing. I experimented with different themes and approaches. After a bit, I found my voice and stride. The blog could take on a more personal, informal, and unprofessional tone. I expanded my topics to include how science is managed. Given that American science is being managed abysmally, the writing struck a nerve. The loss of the edge over the rest of the World is something our managers don’t want to admit. Rather than take the critique, they took it out on the critic. So I wrote. Some of my essays were terrible, some were good, and a few were great. It was a good thing to do personally. Unfortunately, the critique and failures are not something Sandia could tolerate.

As I noted, Sandia is passive-aggressive culturally. When you get stabbed, it’s in the back. I know that now. Someone reported my blog to ethics. I’m pretty sure it was one of my managers. He could have simply told me to stop. That would have left fingerprints. The ethics people investigated. They focused on the idea that the blog was all about money. Was I making money from it? I wasn’t! The fact that I was doing it pro bono was foreign to them. It was a tell. I was cooked from the jump. Eventually, I was given a reprimand. I needed to stop the blog. My conclusion is that it was my critique of the national exascale program that did me in. What I said struck a nerve, and it was time to shut me up.

Perhaps, or definitely foolishly, I started it up again in 2024. I had already determined that retirement was an option. Sandia came for me again. It was more passive-aggressive behavior from managers. Fortunately, I was warned, and I ducked. They were still coming for me. I would not escape. So, I retired. In the end, the blog was the single best thing I did at Sandia. I could be accused of not learning my lesson back in 2018. I didn’t take the hint to shut the fuck up. In another view, I refused to be intimidated. I did not surrender. Nonetheless, it was my ultimate failure professionally. I was unfit for today’s Sandia. This was the wrong place for me to work, much less flourish.

The tattoos are the most obvious manifestation of my change in focus. The blog was the most obvious work-facing focus. Since I’m still writing the blog, clearly it has a value for me. I also shifted to more emphasis on my marriage, family, and friends. All of this was aided by Sandia’s excellent commitment to work-life balance. The shift in my foci was an implicit admission of the futility of professional success at Sandia. I knew it, but I also resisted. I still wanted it all. I would not fully accept my fate. The safety and security of my job and pension were the trade.

“To change yourself is not to cultivate yourself. Rather, it is to rob yourself of what you could have been as a means of becoming what you cannot.” ― Craig D. Lounsbrough

A huge change; A huge chance

In 2006, the Nuclear Explosives Code Development Conference was held in Los Alamos. One of my staff was the organizer. He was the same person who got fucked over by his ethics and calling out homophobia. I attended, as did some Sandians. The gateway was my friend Tim Trucano, whom I had met back in Washington DC in 1999. Tim and I interacted as part of the V&V program, where he was the voice of the pioneer. Along with Tim was Randy Summers, who was managing the ALEGRA code. I approached them in friendship, but also with curiosity about working at Sandia. They were interested. We hatched a plan for me to apply for a position.

“Man makes plans . . . and God laughs.” ― Michael Chabon

The plan unfolded. Los Alamos was under new management. This was an ensemble of different entities led by the University of California (UC) and Bectel. UC had managed Los Alamos since World War 2. Bectel was a disgusting corporation, and they dumped their toxic waste on Los Alamos. I was extremely unhappy with the new management due to them. The UC management was from Livermore: Mike Anastasio and Charlie McMillian. Mike and Charlie were quite good and competent. Charlie died in a tragic accident a few years ago. He was also close friends with a number of my friends and was a truly impressive man. The Bectel contingent was poisonous and gross. They were nothing but awful. I didn’t think the change was positive at all.

I interviewed at Sandia. They put me up in a terrible hotel near the Big I. My advice for Sandia was to never-ever put anyone in that hotel again. It was in a really shitty area near a truck stop next to the Big I. Lots of hookers and drugs with a sprinkling of homeless. What the fuck were they thinking? Aside from that, the interviews went great. The highlight was Bill Oberkampf. Bill and I had never met professionally. As I told Bill, we had met under some odd circumstances. Back when I was 23 years old, I was Bill’s son’s boss at McDonald’s. Bill was concerned about his son’s schedule, and we met on the topic. Bill’s son was an amazing worker, and I loved working with him. He also had a super hot girlfriend. She was also a really great employee, but Bill wasn’t fond of her. This was a great source of laughter. One of my best memories of a job interview ever.

I got the job and transferred to Sandia on February 19, 2007. It was Martin Luther King’s Day and a holiday in Los Alamos, but not at Sandia. A subtle sign of things to come.

“Every ending writes the first chapter of something new.” ― Shivanshu K. Srivastava

Trying to fit in: the foundation of the failure

This gets to a real vexing challenge in life. Do you work to fit in and change yourself to smoothly connect to a place? Or do you continue to hold on to your unique self? Unfortunately for myself, the nearly 18 years at Los Alamos had transformed me. I was brimming with confidence and knowledge, with ideas brought to life. As I would learn, these were all detriments to Sandia’s success. It would have been far better to enter into my time there with a subservient heart. Better to have ideas that are only small excursions from what Sandia does. So I lowered myself to their level, and the novelty of my work shrank. When you look at my publications in the Sandia years, this is obvious. Nothing in the environment encouraged excellence for me. It lowered my goals.

This is not a place for big things, but rather incremental progress on the things Sandia likes. Sandia is an engineering lab, and it wears this like a weight. Engineering is an applied science. There is much less science at Sandia. In many parts of the lab, they are creating miraculous things and engineering the fuck out of them. In computational science, Sandia plays third fiddle to Los Alamos and especially Livermore. In every part of computational physics they are less. The only place they compete is in the engineering of computers and software. Sandia does the best software engineering of the three labs. They engineer the computers themselves better, too (but that’s what the companies do). What they do on these computers with this software is less. Since this is where my career was all about, I was in the wrong place.

I’ll share with you one of the deepest ironies about my time at Sandia. The person I was before either of my crises that I spelled out in part one would have been far better suited to work at Sandia. He was far less confident and energized by science. He would have just been happy with the work there and put his nose to the grindstone and grind things out. Neither the person who revamped himself so that he could excel at school and get a Ph.D. nor the person who had balance in his life would have succeeded. The untransformed version of me was better suited for Sandia.

Unfortunately ,that was also the person who had the 3.16 grade point average, which, given Sandia’s s hiring practices, made me undesirable. Sandia always hired people who were very, very good students with high GPAs. These are those who were also conformist and rule followers. They would take their assignments and complete them dutifully. These are people who were excellent homework doers and test takers. They were a very different kind of people from those who did the research at Los Alamos and Livermore. Sandia carried this self-image to the extreme. They always felt second fiddle to those other labs and had a distinct lack of self-confidence. Sandia has a huge chip on its shoulder when it comes to Los Alamos and Livermore. This chip was always looming just out of sight, just under the surface, but reared up whenever the other labs were mentioned. I carried the Los Alamos identity too clearly.

One of the things that I had a misperception about going to Sandia was the role of the contractor. At the time, Sandia was run by Lockheed Martin and had been since 1994. This was over a decade before the takeover of Los Alamos and Livermore by the amalgam of corporate interests. I have been told by friends that the Sandia that was run by Bell Labs was a different and far better place. I believe it. The upshot is that the destruction of the institution had been going on for over a decade at Sandia. This preceded the destruction that happened at Los Alamos and Livermore under the new corporate governance. Rather than fix problems, this governance has powered the decline of these institutions.

“The best lack all conviction, while the worst are full of passionate intensity.” ― William Butler Yeats

Shock Physics at Sandia: A Model of Dysfunction

The worst thing that I stepped into when I hired on was the absolute shit show. This is Sandia’s shock physics efforts. There were two shock physics codes, CTH and ALEGRA. These two codes were basically at war with each other; it was a virtual Hatfields and McCoys. Unbeknownst to me, I was hired into the Hatfields under ALEGRA, and the CTH McCoys hated me immediately. One of the key aspects is that Sandia had treated CTH with enormous levels of unethical behavior. The response of CTH over time was to become unethical themselves. It was the epitome of horrible passive-aggressive conduct so evident at Sandia. As usual, it revolved around money and power, but also the self-critical public image.

“My biggest problem with modernity may lie in the growing separation of the ethical and the legal” ― Nassim Nicholas Taleb

Thus, the unethical behavior of the CTH manager that helped prompt my retirement was encoded into the culture years before. It had it roots in dumb management decisions. CTH was cast aside at the beginning of the ASCI program. The reason is superficial because it was a Fortran code, and Sandia was going to be a C++ shop. The wheels of dysfunction were put in place. The main unethical behavior that Sandia engaged in was to continually use CTH as marketing for ASC(I). Because CTH did stuff that was on par with what the other labs could do. At least, it looked like it. So CTH was used to defend funding that felt threatened. CTH didn’t receive anything in return. No wonder they were so pissed off.

Especially true when the CTH effort was existing in a hand-to-mouth manner. The code and its use survived for decades, building a loyal customer base in National security. Nonetheless, this was a difficult existence. The Sandia management had laid the foundation of generational dysfunction. The reasons were stupid and petty. This was simply another manifestation of the massive chip on the shoulder that Sandia had. Whenever they were compared to Livermore and Los Alamos, they felt inferior. CTH was blunting that edge. Meanwhile, with a deficit in funding, CTH began to reflect this inferiority objectively. The code was not refreshed technologically while shock physics modernized in the 1990’s and this Century. It was work I could have assisted immensely. Given the culture and dysfunction that was impossible.

I walked into this feud between the two codes like a lamb to the slaughter. I am guilty of not realizing that anything technical was completely and totally immaterial for how the interaction would go. For CTH, I was the enemy. They would treat me as such. This was mere foreshadowing for what happened recently. I was still the enemy. CTH was defensive, and any critique was treated as an assault. I can say that my greatest sin is not learning and recognizing this and modifying my behavior accordingly. The unethical behavior behind my departure was simply the latest incarnation.

When I step back and think about CTH, it completely speaks to the nature of Sandia as an organization. CTH is a brilliant, streamlined code that its users love. It is simple and runs fast. The user interface is elegantly simple. The shortcomings of CTH are primarily that it’s been around too long. A perfectly reasonable bit of code work for the early to mid-1980s. In 2026, it is antiquated and out of date. Yet it persists. The current version lacks innovation and adaptation to how technology has marched over the last few decades. The other aspect is a general lack of appreciation for the deep science and mathematics underpinning this type of code. This lack of content leads to all the problems. Combine this with dysfunction and ethical lapses one gets baked in mediocrity. The effort simply cannot escape it.

What happened to me was a political intervention to rescue technical shortcomings. The will and motive to fix the code’s shortcomings, to produce something that was actually worthy of a national laboratory, is absent. Also absent is the notion of responsibility to the Nation. Our national security needs the best science, but that is a vacant belief at Sandia. In CTH, you see both the strengths of Sandia and its greatest weaknesses manifested in one place. CTH has lots of loyal customers from second and third-rate organizations. These organizations cannot produce anything better. In place of nothing, CTH looks amazing. Their standards of acceptance, with a lack of scientific rigor, are even lower. Thus, CTH stands in an important position for a host of national security applications. God help us. It is the epitome of the USA’s broad decline in science and technology.

“Look on every exit as being an entrance somewhere else.” ― Tom Stoppard

Closure

My time at Los Alamos felt like I was in a continual evolution towards coherence and contribution. My time at Sandia felt like an incoherent, jumbled mass of disjointed work. Shock physics was a common theme spanning my time and a place for huge potential contributions. The nature of that community doomed it from the beginning. This dysfunctionality was ultimately my undoing. Everything else was just projects that were a way a way of filling my time card out. Nothing ever felt like it was actually going anywhere. There were no deeper accomplishments. There was nothing that created a lasting imprint. It was just passing time and something to do.

I worked on nuclear power (CASL), exascale computing, and continually on V&V. CASL was pointless. Exascale was deeply flawed and simply big money to blunt an unpleasant reality. V&V was an area in decline and has become a shell of its virtuous origin. I had seen work on machine learning and AI following this path. It was a retread of the exascale program. A waste of taxpayer money. V&V had become utterly toothless. Shock physics was the only place where I could make an impact. As I’ve noted above, that is totally fucked at Sandia. In the end, all of these were very unsatisfying. and left me feeling rather empty. This emptiness was in a place where fulfillment and achievement should be a natural outgrowth of one’s work.

This outcome for me was somewhat pre-ordained the moment I walk in the door. The things that I do and am very good at are not valued at Sandia. I was never going to stand out there. It was never going to be a success, and this incoherent, jumbled mess of 19 years simply was the outcome of that. Sandia doesn’t really value what I bring to the table. There is little value in the knowledge I have at this Lab. There’s little use for the expertise I possess. I came to accept this and finally just submitted to working for a pension. It saddens me to write that, but it’s the truth. Without a pension from Sandia, I probably would have given up and left.

I truly hope that Sandia can overcome this dysfunction. The Nation needs it to be better. It needs some better leadership that can jettison the past. The people who work in shock physics are genuinely quite talented. All of them are better than this. I am sure I was, too. It is an important area of achievement, but the management and the system at Sandia do not support it in the way that’s necessary. Shock physics is necessary in engineering the nuclear stockpile. It also has deep scientific and mathematical pieces that are necessary. Sandia needs to value these more. They don’t because this knowledge is damning of their efforts. Without valuing and empowering the work needed to be first-rate, it will continue to be mediocre.

“Never try to teach a pig to sing; it wastes your time and it annoys the pig.” ― Robert Heinlein

Postscript

I ran into a good friend while writing this. He commented on my writing.

He told me, “You know people read what you write.”

I said, “I know and hope they do.”

He went on, “Some of the stuff you say isn’t very nice.”

“It’s the truth,” I replied.

He then amplified, “I wouldn’t say these things; most of them are not going to listen.”

I concluded, “If they didn’t want me to say it, they should have acted decently and ethically.”

“Power does not corrupt. Fear corrupts… perhaps the fear of a loss of power.” ― John Steinbeck

It is clear to me that Sandia wants to launder its image. There doesn’t seem to be any effort or willingness to fix the problems. I articulated this reason as the nature of our modern super-connected World. It traces back to the internet. The desire to manage organizational images turns into toxic positivity. There is a complete loss of institutional transparency and honesty. The institutions are worried that any honesty will be used against them. Thus, problems are submerged. Managers only message positive things and endless accomplishments. More bluntly, they are bullshitting everyone, including themselves. Worse yet, they have bought their own bullshit. Problems just fester and grow rather than get solved. Shock Physics is a great example of this in practice.

While I was there, the internal message was “we are so awesome” and “our culture is excellence and nearly perfect.” There’s nothing that needs any fixing. They don’t want the truth out there for all to see. They won’t admit their problems even in private. It felt like madness to me; the problems were legion. I can point at the similarities to the subserviant and self congradulating Cabinet meetings in the White House. It is the same spirit. There are no problems, and the awesomeness is unbounded. When the delusional assessment is internal, there is an express train to catastrophe. This is where Sandia is. This is where the nation is.

My friend noted that the writing is probably cathartic. Indeed, it is. I’m trying to sort out and understand my own part in this. I made some conclusions about this. I gave up on Sandia when I got the reprimand for the blog in 2018. It was my professional demise. I kept on making foolish forays into doing the right thing. Near the end, I had a couple of good managers that me some hope. When they were replaced, that hope was dashed. They were replaced by inept and unethical ones.

Walt entreated me to get involved with Sandia shock physics again. He took my expertise seriously. In retrospect, this was a huge mistake and foolhardy. In the face of how fucked up this discipline is at Sandia, it was futile. Any thought that expertise and knowledge were useful for shock physics was madness. It is too broken, and my mastery of the topic was not respected at all. It was my end at Sandia. I was a fool to go down that road. I should have known better. I was guilty of looking past the problems and optimistically throwing myself back into the maw of the dysfunction I knew so well.

I had some really good managers there; they are genuinely good people. I’m thinking of Bruce, Walt, and Lauren in particular, who all stand out as some of the best of my life. Sandia needs more of them and fewer of those who stabbed me in the back. There seems to be a system in place that distorts and perverts good people into shitty managers. Andy, Erik, and Scott come to mind. Sandia made them worse people, too, with appalling ethics. Worse yet, a system that seems to support the bad far more than the good. There are other terrible managers I won’t name. I don’t know them well enough to know if they were ever decent people.

Yet in the final analysis, I am the one with the lion’s share of the blame. It was the wrong place for me, and I knew it very soon after I arrived. I stayed anyway.

“I am somewhat exhausted; I wonder how a battery feels when it pours electricity into a non-conductor?” ― Arthur Conan Doyle

References

Barlow, Andrew J., Pierre-Henri Maire, William J. Rider, Robert N. Rieben, and Mikhail J. Shashkov. “Arbitrary Lagrangian–Eulerian methods for modeling high-speed compressible multimaterial flows.” Journal of Computational Physics 322 (2016): 603-665. (218 Citations)

Alexander, Francis, Ann Almgren, John Bell, Amitava Bhattacharjee, Jacqueline Chen, Phil Colella, David Daniel et al. “Exascale applications: skin in the game.” Philosophical Transactions of the Royal Society A 378, no. 2166 (2020): 20190056. (127 Citations)

Robinson, Allen, Thomas Brunner, Susan Carroll, Richard Drake, Christopher Garasi, Thomas Gardiner, Thomas Haill et al. “ALEGRA: An arbitrary Lagrangian-Eulerian multimaterial, multiphysics code.” In 46th aiaa aerospace sciences meeting and exhibit, p. 1235. 2008. (196 citations)

Banks, Jeffrey W., T. Aslam, and William J. Rider. “On sub-linear convergence for linearly degenerate waves in capturing schemes.” Journal of Computational Physics 227, no. 14 (2008): 6985-7002. (140 Citations)

Rider, William, Walt Witkowski, James R. Kamm, and Tim Wildey. “Robust verification analysis.” Journal of Computational Physics 307 (2016): 146-163. (42 Citations)

Mattsson, Ann E., and William J. Rider. “Artificial viscosity: back to the basics.” International Journal for Numerical Methods in Fluids 77, no. 7 (2015): 400-417. (62 Citations)

Yanilkin, Yury V., Evgeny A. Goncharov, Vadim Yu Kolobyanin, Vitaly V. Sadchikov, James R. Kamm, Mikhail J. Shashkov, and William J. Rider. “Multi-material pressure relaxation methods for Lagrangian hydrodynamics.” Computers & fluids83 (2013): 137-143. (55 Citations)

Scovazzi, Guglielmo, John N. Shadid, Edward Love, and William J. Rider. “A conservative nodal variational multiscale method for Lagrangian shock hydrodynamics.” Computer Methods in Applied Mechanics and Engineering 199, no. 49-52 (2010): 3059-3100. (59 Citations)

Rider, W. J., E. Love, M. K. Wong, O. E. Strack, S. V. Petney, and D. A. Labreche. “Adaptive methods for multi‐material ALE hydrodynamics.” International Journal for Numerical Methods in Fluids 65, no. 11‐12 (2011): 1325-1337. (26 Citations)

Kieweg, Sarah L., Jaideep Ray, V. Gregory Weirs, Brian Carnes, Derek Dinzl, Brian Freno, Micah Howard, Eric Phipps, William Rider, and Thomas Smith. “Validation assessment of hypersonic double-cone flow simulations using uncertainty quantification, sensitivity analysis, and validation metrics.” In AIAA SciTech 2019 Forum, p. 2278. 2019. (24 Citations)

Love, E., and William J. Rider. “On the convergence of finite difference methods for PDE under temporal refinement.” Computers & Mathematics with Applications 66, no. 1 (2013): 33-40. (21 Citations)

“It is our misfortune, as a historical generation, to live through the largest expansion in expressive capability in human history, a misfortune because abundance breaks more things than scarcity.” — Clay Shirky

I’ve had great appreciation for the thoughts of Clay Shirky about the internet’s impact on society. He had some quite profound thoughts about what it means more broadly. Apparently, he moved into college administration more than a decade ago. His views have faded even as the internet writ large has even larger impacts. AI is a by-product of the internet, along with algorithmic innovation and a shitload of computing power. If anything, the changes in society have accelerated. Things are evolving so quickly that we can’t adapt. Everything is breaking. This includes a host of institutions on which the stability of society depends. This includes the National Labs where I worked. The result is that everything feels broken; everything is completely fucked up.

“A revolution doesn’t happen when society adopts new tools. It happens when society adopts new behaviors.”— Clay Shirk

“Institutions will try to preserve the problem to which they are the solution.”— Clay Shirky

I am having a great deal of difficulty with part 3 of my career retrospective. I’ll muse here a bit about the core of my difficulty. My difficulty is that the years at Sandia were bad for me. Sandia isn’t necessarily bad. Primarily, Sandia wasn’t a good fit for me. By most objective standards its a good place to work and a net benefit for society. This is also complicated by the details of the time we live in. We live in a transformational time for the USA and the World. American institutions of all types are straining under the pressure of today. Huge changes are afoot. We are living in the wake of huge changes of historical proportions. This time will be marked as especially turbulent when history is written. I don’t want to be unfair to Sandia. It has issues, but much is outside their control.

“The future is already here – it’s just not evenly distributed.”— William Gibson

My thesis is that the central element breaking society is the internet and all its related technology. I have heard it quipped that the internet rivaled the printing press in terms of disruption. The printing press created changes in society that drove decades if not centuries of war. It broke the stranglehold of the Catholic church in Europe and created the conditions for the Reformation. The democratization of information changed the dynamic of society then, and it has now. The internet created the opportunity for instant communication and destroyed the preceding mass media. That destruction is accelerating today. The smartphone was a huge lever arm for this. Suddenly, the internet was ubiquitous and penetrated every aspect of life. On the heels of this, we had social media. Now we have AI, which might dwarf all the rest. All of this was enabled by the internet. These changes have disrupted society. Every institution is reacting to this. Every institution is changing. Change like this, at this rate, really, really sucks!

“When we change the way we communicate, we change society.”— Clay Shirky

The thing to consider is what institutions have done in response to the internet. How have they responded to the ease of communication and information? I’ve seen a general increase in the transmission of information, and thus scandals like those I’ve encountered. Employees also have a potential voice via blogs, video, and social media. The institutions want to cut that out because that’s a source of power. This blog is a good example. At the same time, the executives and the power of the “top” of society have unparalleled power. Billionaires (and soon Trillionaires) abound. They wield vast power and influence due to their wealth. They engage in “rent seeking” behavior to amplify their power. The legal system gives them carte blanche to rule over their minions. So they crack down on the transparency that the internet could provide. It is both the source of their wealth and a threat to their power simultaneously.

Sandia squashed my voice. They want to control their image online. They want to control the narrative. I’ve seen a relative increase in the inappropriate classification of information. It’s about asserting control, ethics and truth be damned. Again, I am a personal example. The report that ushered in the end of my career was inappropriately restricted to hide it. We’ve seen an orgy of classification across the government in the Internet age. The reason for this? To hide information that might be embarrassing. The internet makes it possible to see much more, but the institutions shut that down. We have this information war in society. Into the vacuum of information, we see the proliferation of conspiracy theories.

There’s another force at work to amplify this. In the USA, there is close to unparalleled societal inequality. It rivals the “Gilded Age” and societal upheaval is the usual consequence. Two things have come together to drive this inequality. The past 40 years of neoliberal order has driven massive wealth into a small number of hands. The USA is very rich. Even the relatively poor people have a lot. What people see is their comparative wealth, and the bulkk of society has very little to those at the top. The rich are leveraging their wealth into power via “rent seeking” (Citizens United!). The law is simply a suggestion to them, not remotely a constraint.

“Tragedy of the Commons: while each person can agree that all would benefit from common restraint, the incentives of the individuals are arrayed against that outcome.”— Clay Shirky

All of this has come together in political strife and conflict. Trump is without a doubt, a consequence of these trends. This is true whether one believes he is good or bad. I would submit that he is the result of both inequality and information technology. Trump is a transformational leader. The USA will be a different country by the end of his reign. Institutions like NATO will not be the same. Meanwhile warfare is changing due to drones, missiles and AI. American institutions are being changed. Labs and science are under assault with science funding reduced. The USA is more isolated and separate from the rest of the World. The nature of the International order will be different and more conflict ridden.

“You realize that our mistrust of the future makes it hard to give up the past.”

― Chuck Palahniuk

No one really knows where this is going. Chances for disaster and catastrophe are definitely high. The economy could explode due to AI. Or it could implode. AI could drive massive unemployment or grow massive abundance. With all this uncertainty the institutional response is caution. They are protective instead of bold. The dangers are too high. Sandia is among these places exercising caution. I need to factor this into my career assessment. It still sucked for me, and nothing can change that.

“We’re collectively living through 1500, when it’s easier to see what’s broken than what will replace it.”

— Clay Shirky

tl;dr

The resolution of the crisis of my Spring grad school failure perfectly set me up to succeed at Los Alamos. Los Alamos was perfectly set up to grow me. It was a place for me to meet my potential. The heart of this was a spirit of trust and generosity. In a deep sense, this was the good part of the spirit (ghost) of Oppenheimer. My time at Los Alamos made the most of this. It ended as his dark side met events. The modern USA of the 2000s could not tolerate any of the echoes of Oppenheimer. It ruined his legacy and dismantled something unique and incredible for the Nation. I was just another casualty.

“No single act of generosity remains in isolation. The ripples are many.” ― Sarah Winman

The start of Los Alamos, the perfect place for a career to gestate.

As I mentioned before, I felt amazing to have the opportunity to work at Los Alamos. Getting the job in the first place felt like a miracle. I realize in retrospect that I was lucky to be looking for a job when I did. This was not a plan or mindful, just pure dumb luck. The key was that I was ready to take advantage of that luck. This all happened in the Spring of 1989, and as I said, interviewing was an adventure. I had six interviews. Three of them took plane trips. One to Idaho Falls and two to Virginia.

In terms of pure humor and great stories, the two interviews in Virginia were both catastrophes. Either of those jobs would have been awful, and the interviews definitely exposed that. I still got job offers from them, but the pay sucked, too. One of them became completely unveiled a few years later at a NASA conference on a manned Mars mission. It still stands as the most insane conference I’ve ever attended. It was 1992, and it included a visit from the NASA administrator (Dan Golden), automatic weapons fire, and trash cans full of cheap Midwest beer. This one contractor impressed me with their sheer incompetence. They were vastly less competent than I had measured in the interview in 1989. I thought they were morons, and I overestimated them. This was my first experience with the dangers of secrecy. They had been working on an SDI “black project”. They could tell me little then, but it felt like stupid bullshit. I learned that they were even dumber. It remains one of the most singularly incompetent things I’ve ever witnessed.

When I started at Los Alamos, my excitement was palpable. I did not realize how incredible an opportunity it was. The environment was ideal for growing me as a scientist. The Lab was the best incubator anyone could ask for. In retrospect, my attitude starting there was perfect for taking advantage of it. The equitable nature of the culture. Having a PhD didn’t make you special. You were just Bill or whatever your name was. People were curious, generous, and interested in assisting you. I started to learn immediately. What I didn’t know was that Los Alamos was in decline. It had fallen from the apex of the long, wide span of excellence. Still, the excellence lingered, and I would benefit immeasurably.

Writing like this is a mechanism of deep thinking. Along the way, you realize things that were lurking right below the surface. This essay is no different. The topic of generosity is top of mind in thinking about Los Alamos. There was a deep culture of sharing knowledge and time that benefited me. That sense of deep generosity seems gone today. When I arrived in 1989, Los Alamos was a more generous place than most. It exhibited a level of generosity that has largely disappeared today. This is true society-wide. We are now a selfish, self-centered society as a whole. The more I confronted this topic, the more this became self-evident. The last 25 years have killed generosity. We are poorer for it, and we will all pay.

Part of it links back to the destruction of trust. It will be a major part of the story for me. These are the “troubles” I’ve called it from 1999 to 2004 with multiple scandals. I will elaborate in depth later.

“There is no exercise better for the heart than reaching down and lifting people up.” ― John Holmes

N-12, Being an engineer

The labs have odd systems for naming organizations. LANL had letters to describe Divisions, with 100’s of people, and numbers for groups with 10’s of people. I started in N-12. “N” was for nuclear, and in this case reactors N-12 was the nuclear reactor analysis group. We did an analysis of nuclear reactors. I got there still in grad student mode, and little about the culture urged me to change. Shorts, sandals, and a T-shirt were still my summer uniform. I started on June 19, 1989.

The group was outside the inner circle of LANL, out at TA-52 on a mesa. I often describe Los Alamos looking like a hand with mesas being the fingers and the mountains as knuckles. In between the fingers were canyons. The canyons had interesting names like “acid canyon,” named for the shit they dumped there in WW2. My boss was a guy named Mike Cappiello, and I’ve got nothing but praise for him. He was an excellent first boss who helped to cultivate my enthusiasm. My first assignment was to learn how to use TRAC LANL’s reactor safety code. I did that, then sought to model a high-temperature gas-cooled reactor proposed to produce tritium for our nuclear weapons.

TRAC fucked it up. It was designed for water-cooled reactors. Gas reactor pumps are big fans with huge area changes. It solved an internal energy equation, and it led to huge errors. The old timers there said, “The kid is full of shit”. Thankfully, Dennis Liles, the author of the code, came to my rescue. He said I was right. Confidence was gained. I had my first victory. Soon, my interest in modern numerical methods got harnessed. I did a unique analysis of the solvers in TRAC. I had also started back at a PhD focused on these methods. I would finish that PhD by February 1992. I harnessed the hard work ethic I developed in my undergraduate years into an unstoppable force.

“The most truly generous persons are those who give silently without hope of praise or reward.” ― Carol Ryrie Brink

Along the way, I established the start of an essential collaboration for my future. I was working on a hair-brained scheme for transmuting nuclear waste into something less dangerous. It involved spraying 800 MeV protons into a high-Z target to create a shitload of neutrons and change material to less awful shit. One concept would use flowing lead as the target. It was a nasty free-surface problem. The experts for solving such problems were in T-3, Frank Harlow’s group. I approach a fellow young scientist, Doug Kothe, for advice. In keeping with LANL’s generous spirit, Doug invited me with open arms and mind. Over the years, this blossomed into a great collaboration. Later, we wrote a paper on interface tracking, which is my most cited article. That article was based on work that no project ever funded. It was merely me learning about an important technique and finding a new way to code it up. In addition, that very code is still being used in a LANL weapons code. Working with Doug also moved me closer to the Lab’s core mission. He also worked on a code that was on the Connection Machine, among other things.

Along the way, I put a modern method into TRAC to follow the solute used to shut the reactors down at Savannah River with unerring accuracy. I also got to see nuclear rockets and the artifacts of that program shut down after Apollo and Vietnam. Once I had my PhD, it was time to move on. I had bigger dreams. An ad was placed in the weekly lab paper, and I applied. Mike, my boss, agreed and actually brought me the ad too. I had already done it. I interviewed and moved. The next chapter was starting. I was moving from the periphery of the lab towards the center.

“It is not often that a man can make opportunities for himself. But he can put himself in such shape that when or if the opportunities come he is ready.” ― Theodore Roosevelt

C-3/CIC-19, National Science

The new job was really exciting. It was part of a national project including LANL, LLNL, and LBL. The leads were a couple of heavy hitters in modern methods, John Bell and Phil Colella. I would have a chance to get to know some luminaries from the literature firsthand. The project was to work on an exotic pulse reactor that involved shock waves and combustion. I would work on the compressible methods they developed, along with incompressible flow solvers. My boss was Jeff Saltzman, also well-known. I took to the job with energy and fervor.

It was a really important time in my life. My first child was born in mid-1994. My wife was finishing her Bachelor’s degree. In a sense, the work I was doing was almost a habilitation. I ended up writing another virtual thesis in verifying and understanding the incompressible flow methods. Along the way, I learned about linear solvers from dense methods to multigrid. I started to use multigrid to precondition Krylov methods. That seeded work later in my career with radiation transfer. I wrote a compendium of work on the various options for the approximate and exact projection methods for incompressible flow. These were coupled with modern methods for advection as well. I wrote several papers on the topics.

I continued and deepened my work with Kothe. In my “free time,” I wrote a code and a paper that now has 2500 citations. I coupled the interface tracking to incompressible flows and multigrid. I continued to learn about high-resolution methods, too. I also gained confidence in directly confronting Bell and Colella. This was something my peers thought was genuinely nuts. I did it and survived their pretty direct disagreement. It was far worse than any of my thesis defenses! I did things no one else thought were rational or wise. See a pattern?

Finally, I started to move to the core mission of LANL, nuclear weapons. In 1992, we stopped testing, and by 1995, the ASCI program was being hatched. I was part of those discussions. In the computing division building, there was a sub-rosa gym called “Bo’s gym”. I worked out there with other nuts. I would read on the stairmaster turned up to 11. A fellow nut at the gym noticed all the interesting shit I was reading. I would read a paper and toss it to the floor to dry off. My material was interesting. This gym goer was Len Margolin, my future boss. He was recruiting for the hydrodynamics group in the (in)famous X-Division. I was ripe for the picking.

It was time for me to get all the way to the core of the lab’s mission. I was a LANL guy now, and this was how to focus on what the Lab was made to do, nuclear weapons. It was also a new dawn; the ASCI program was the future. I would work in this program for the remainder of my career.

“Generosity is the most natural outward expression of an inner attitude of compassion and loving-kindness.” ― Dalai Lama

X-3, Becoming a weapons physicist

In late 1995, I moved to X-3. Len Margolin was my new boss. I shared Len’s passions for methods and codes. Len and I are still friends today. One of the things I value the most is how much we are able to disagree about things. Both of us hold some beliefs very closely that oppose each other. Nevertheless, we continue to engage and spar. This was true in 1995 and is true today, 30 years later. It is one of the things I value the most. Free exchange and combat of ideas wth the goal of understanding. This is science, and amongst my most deeply held beliefs. This is the way to do things.

“Give a bowl of rice to a man and you will feed him for a day. Teach him how to grow his own rice and you will save his life.” ― Confucius

Len gave me a lot of freedom to learn. I took it on myself to learn the business of X-Division. I learned the codes, methods, and weapons. I learned and implemented Lagrangian hydrocodes based on the Von Neumann-Richtmyer methods. I learned all the details of nuclear weapons and the physics associated with them. In many ways, I was pursuing a third PhD-level learning experience. It was another trip deep into the state of knowledge in deep areas. As part of this was the science of turbulence and mixing. A second part of this was verification and validation. The pursuit of both of these would shape much of my career.

In this time, I had that second crisis. I finally felt like I belonged at LANL. I was a fully fledged member of the Lab and deserved it. My time in X-3 was the richest and most integrated time of my career. Early on in my time, Len connected me with Jim Kamm. Jim and I connected as friends and colleagues. We worked together for nearly 20 years. It was an essential friendship and part of the magic that Len worked. Another thread of richness was the hiring of Dana Knoll, a friend from Grad School, plus Dana’s colleague Vince Mousseau. We leveraged our joint knowledge into a rich vein of research on radiation transport and multi-grid. My research life was beyond my wildest dreams. It was rich and varied. It would only get deeper and richer. My life and career were in full bloom.

Things go wrong. CCS-2/X-1, Finding a place to excel

Now that my career was flying, it was time for everything to go to shit. It wasn’t for me personally, but rather for Los Alamos. There was a series of scandals and events to rock the Lab. These came one after the other, shining a national spotlight on Los Alamos in a uniformly negative light. The first of these was a spy scandal starring Wen Ho Lee. Wen Ho was a truly mediocre scientist, but he did some truly huge things. He downloaded a lot of classified material at great personal effort. Why he did this remains unknown, although theories abound. I had an office next to his for around a year and a half. As I’ve said, when someone you know is in the headlines, it usually sucks. Definitely true here.

“You make all kinds of mistakes, but as long as you are generous and true and also fierce, you cannot hurt the world or even seriously distress her.” ― Winston Churchill

The whole scandal was a complete shitshow. Ultimately, it caused a bunch of changes at the Lab. All bad changes. Trust was crushed, and the shit flowed downhill. The government’s reaction fucked the lab up. The response started to break everything good at the Lab. It was a disaster for Los Alamos. The response was akin to pouring gasoline all over a fire. There were more problems ahead. The next was a forest fire, the Cerro Grande fire. It was a “controlled” burn by the forest service that got out of control. It burned 400 homes in Los Alamos and spurred an evacuation of the entire town. It also triggered scandal number two.

This was the disappearance of classified hard drives. Someone went to pick these discs up and take them to Sandia for safekeeping as the fire raged. They were not here. These hard drives were unaccounted for during the fire and about six weeks after. Once it was reported to the government, FBI agents descended on the Lab. It was a second disaster. This took place at the same time as Wen Ho was being tried for treason. The whole thing ended up as a massive cluster fuck where everyone looked like shit. They found the hard discs behind a printer, a couple of doors down from where they were supposed to be. Wen Ho got off as the government case went up in smoke. Worse yet, the two shit shows were connected awfully. FBI agents looked like assholes and got Nazi salutes (that they deserved!).

The Lab got even more fucked up. The disasters were not over. A third catastrophe was coming. Things started to come loose again. There was a new batch of missing classified hard discs (which never actually existed, an accounting error). An accident with a laser partially blinded a student. Now that Los Alamos had a raging asshole as director, the Lab was closed. The asshole was Pete Nanos, a retired Navy admiral. What a dick! He shut the whole place down. It was a lesson in how not to lead. In retrospect, Pete’s reign was also a harbinger of a different kind of leader; the kind our President is. Terror, fear, and intimidation were the tools of power and control. These were another way to separate the leaders from the led. Nanos was clueless about what happened at the working level.

Rumors abounded that Nanos’ predecessor was disconnected from real events. John Browne was a really great guy. He had impressed me when I worked underneath him (way down below). He was a good person, but he had been insulated from the working level. Maybe, maybe not. The events could have just happened anyway. He got canned because he just happened to be there. What I’ve seen over and over is leaders who don’t know what is happening. Each layer of management fails to inform them or just tells them good news. Any bad news is simply killed before it gets to them. Again, we can see this happening at the highest level. Our cabinet members bullshit and ass-kiss the President. No one tells the truth, and reality is just something they control. Power and control are absolute, and that power defines everything. The same with our corporate leaders who exist in a World utterly different from the rest of us. This difference in perspective is the handmaiden of catastrophe.

“Don’t sacrifice yourself too much, because if you sacrifice too much there’s nothing else you can give and nobody will care for you.”

— Karl Lagerfeld.

At the same time, I had a job offer from Livermore. I declined it. Why? The salary and cost of living there were combined to make it a truly dismal prospect for my family. I wonder greatly about how taking that would change my life. I also acted as a group leader at that time to help. I watched some serious shit go down. I watched my deputy group leader resign and retire in a single day as fear swept through the Lab. The Lab that gave me so much was dying right in front of me.

“Selfishness is not living as one wishes to live, it is asking others to live as one wishes to live.” — Oscar Wilde

Meanwhile, my professional life was in bloom. The most clear sign of that was a research project I led on turbulence modeling. One of the greatest things about Los Alamos was the courage and confidence it gave me. Turbulence is an incredibly complex and intimidating topic. I had avoided it like the plague. My commitment to the Lab and its mission gave me the impetus to pursue it. I learned it during the holiday break in 1999, and by 2003, I was leading research on it. That project was incredibly successful, with many well-cited papers and a book. It was merely one of several productive, great projects.

I wrote about 100,000 lines of code on modern shock capturing methods. I used the code to study important methods for Los Alamos and Livermore. I wrote many relatively important papers. I examined exciting ideas to improve methods. They’ve been less successful and influential than I would have liked. I also wrote my first book with Dimitis Drikakis. I still think they are good ideas. I also had the work on Krylov-multigrid, which was quite well-cited and successful. Finally, my work with Jim Kamm on V&V was influential. This is especially true at the Labs. I led a V&V project, and Jim led another. We made huge strides in the practice of verification at Los Alamos. This was the most successful and productive time of my career. All of it stemmed from the environment Los Alamos created. All of it came from the scientist it made me. Everything good about the Lab was being destroyed at the same time due to the scandals.

In the midst of all this, I was looking for solace. In the wake of the scandals, I was part of forming a new computational research division, CCS. I joined, leaving X-Division behind. I was in a good place, but it created new tensions. My collaborator Doug Kothe was my group leader. When he went up to the Division office, I applied for the management job. I didn’t get it because they said I was too “decisive”. It was a real WTF moment with echoes today. It was the impetus for seeking a position at Livermore. In retrospect, it was also the harbinger of management-leadership woes of today. Our leadership across society today suck! It also foresaw the end of my time in CCS. I would return to X-Division. Now that Los Alamos had turned to shit, I was moving toward the door, but hadn’t given up yet.

Can I manage?

I moved back to X-division. At the same time, a management wizard, Paul Hommert, had taken over. Paul had started at Sandia and had been the Lab director at AWE in the UK. He would eventually be the director of Sandia. Paul was vastly over-qualified for the job and replaced a real fuck up as X-division leader. I would say in retrospect that managing X-division is harder than managing either Sandia or AWE. It was enormously difficult. The designers of nuclear weapons work there, and these people are important and powerful. They are also arrogant, often for good reason. Some of them are enormously talented and accomplished. At that time, X-division also had domain scientists in physics, code developers, and computational physicists. Anyone who wasn’t a designer was a second-class citizen.

I had some freedom earned by my successful research in the 2000’s. This was counter-balanced by the damage all the scandals had done. The government’s reaction to these scandals was massively destructive to the Lab. They had deeply harmed the Lab’s ability to work. They had created a vast bureaucracy that was expensive and wasteful. Trust had been annihilated. Worse yet, the scandals kept coming. The latest ones in Los Alamos were amongst the dumbest yet. Someone took classified documents home on a thumb drive, and a meth addict boosted it. Someone bought a car with a P-Card. The result was more bullshit and less trust. Things were spiralling. I hadn’t given up yet. I kept doing my research, but I also wanted to see if I could manage people. I applied to be a deputy group leader in Paul’s new system. Hommert had installed a Sandia-like system in X-division. Now, deputy group leaders would be akin to department managers at Sandia. I got the job.

“Every man must decide whether he will walk in the light of creative altruism or in the darkness of destructive selfishness.” —Martin Luther King Jr.

This was my last act at Los Alamos. Being a manager sucked. In retrospect, I should have seen much more of Sandia in it than I did. My group leader was a big part of the sucking. He dumped work on his deputies so he could do research. Meanwhile, all of us were supposed to work half-time on technical work. The dumping meant we couldn’t, and our programs just had to suck it. So he was a terrible group leader and a selfish piece of shit. It should surprise no one that he’s been enormously successful. He rose through the ranks as a manager (they kept picking him for jobs). A slick British accent helps, too. He also got prestigious awards. Its another abysmal comment on leadership today. We pick too many fucking assholes to lead. He is a really good scientist, and that’s the job he should have stayed in. Instead, he was allowed to be an awful manager.

“There is nothing more frightful than ignorance in action.” — Johann Wolfgang von Goethe

There were a few more nails in the Los Alamos coffin. I can relay the episode that was probably the coup de grace. We had news that funding was short of what was needed to fund everyone. There might be a RIF. I had one person who couldn’t be funded. The why of this was repulsive. He had offended powerful people, primary designers. He used to sit with them at lunch, but they had begun making homophobic comments all the time. He called them on it. He was expelled from the clique. Now he was denied funding. It was completely out of my control or ability to influence. I protected his name, but felt the need to tell him what was happening. This was coming for him, and he was a pariah in X-Division. I went to him and let him know the situation. He was screwed and needed as much time to find something else as possible. It was powerfully emotional and difficult. He found a place to work and could keep his life.

He had also hosted a difficult classified conference. It was a very hard assignment and a minefield. He did a great job, but that meant nothing. It was also the meeting where Sandia recruited me, although I also sought them out.

References: My Top LANL Papers

Rider, William J., and Douglas B. Kothe. “Reconstructing volume tracking.” Journal of computational physics 141, no. 2 (1998): 112-152. (2426 Citations)

Grinstein, Fernando F., Len G. Margolin, and William J. Rider, eds. Implicit large eddy simulation. Vol. 10. Cambridge: Cambridge university press, 2007. (1179 Citations)

Drikakis, Dimitris, and William Rider. High-resolution methods for incompressible and low-speed flows. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. (320 Citations)

Margolin, Len G., and William J. Rider. “A rationale for implicit turbulence modelling.” International Journal for Numerical Methods in Fluids 39, no. 9 (2002): 821-841. (273 Citations)

Puckett, Elbridge Gerry, Ann S. Almgren, John B. Bell, Daniel L. Marcus, and William J. Rider. “A high-order projection method for tracking fluid interfaces in variable density incompressible flows.” Journal of computational physics 130, no. 2 (1997): 269-282. (747 Citations)

Rider, William, and Douglas Kothe. “Stretching and tearing interface tracking methods.” In 12th computational fluid dynamics conference, p. 1717. 1995. (283 Citations)

Margolin, Len G., William J. Rider, and Fernando F. Grinstein. “Modeling turbulent flow with implicit LES.” Journal of Turbulence 7 (2006): N15. (295 Citations)

Mousseau, V. A., D. A. Knoll, and W. J. Rider. “Physics-based preconditioning and the Newton–Krylov method for non-equilibrium radiation diffusion.” Journal of computational physics 160, no. 2 (2000): 743-765. (188 Citations)

Rider, William J., Jeffrey A. Greenough, and James R. Kamm. “Accurate monotonicity-and extrema-preserving methods through adaptive nonlinear hybridizations.” Journal of Computational Physics 225, no. 2 (2007): 1827-1848. (96 Citations)

Rider, William J. “Revisiting wall heating.” Journal of Computational Physics 162, no. 2 (2000): 395-410. (90 Citations)

Rider, William, Douglas Kothe, S. J. A. Y. Mosso, John Cerutti, and John Hochstein. “Accurate solution algorithms for incompressible multiphase flows.” In 33rd aerospace sciences meeting and exhibit, p. 699. 1995. (119 Citations)

Knoll, D. A., W. J. Rider, and G. L. Olson. “An efficient nonlinear solution method for non-equilibrium radiation diffusion.” Journal of Quantitative Spectroscopy and Radiative Transfer 63, no. 1 (1999): 15-29. (108 Citations)

Rider, William J. “Filtering non‐solenoidal modes in numerical solutions of incompressible flows.” International journal for numerical methods in fluids 28, no. 5 (1998): 789-814. (52 Citations)

Greenough, J. A., and W. J. Rider. “A quantitative comparison of numerical methods for the compressible Euler equations: fifth-order WENO and piecewise-linear Godunov.” Journal of Computational Physics 196, no. 1 (2004): 259-281. (78 Citations)

Rider, William J., and Len G. Margolin. “Simple modifications of monotonicity-preserving limiter.” Journal of Computational Physics 174, no. 1 (2001): 473-488. (49 Citations)

Kamm, James R., Jerry S. Brock, Scott T. Brandon, David L. Cotrell, Bryan Johnson, Patrick Knupp, William J. Rider, Timothy G. Trucano, and V. Gregory Weirs. Enhanced verification test suite for physics simulation codes. No. LA-14379. Los Alamos National Laboratory (LANL), Los Alamos, NM, 2008. (45 Citations)

tl;dr

How did this person get created? Why am I so opinionated and vocal? Where did this come from?

I aim to get to the answers to these questions. For my earlier years, the path was uneven and definitely non-standard. The key formative moments were a couple of very personal crises that were hard resets. I emerged from them different from how I entered. Before I got to Los Alamos, I was molded by a childhood as a military brat. It gave me many good and bad things. My young adulthood offered hard work and an early marriage. I learned to work very hard, but also suffered crushing disappointments. All of this led up to my first crisis and set the stage for later success. I was able to shrug off bad habits and begin a career with a positive trajectory. Luck also played a huge role in landing my job at Los Alamos. My newfound approach to life and work provided me with the tools to make the most of it.

This is the first of three parts.

This will be an orgy of self-reflection. Needed for me, but rather self-indulgent. I hope someone finds it useful or interesting. Doing it in the open is far different than writing a personal journal; I do that every morning. It is also focused on one part of my life. The boundaries of my career with the rest of my life are varied in form. As I move into retirement, the boundaries are naturally more porous

“We write to taste life twice, in the moment and in retrospect.”

—Anais Nin

A life measured in big events that shaped me

Most of this essay will be chronological, but not this opening section. I’m going to discuss a couple of big events that really changed me professionally as well as personally. These were crises about 9 years apart that caused me to change. One happened at the end of my first year of Grad School, and the second about 7 years into my time at Los Alamos. Both of them were extremely painful psychologically and that pain demanded action. My response made these transformative.

Often, we frame our lives in big events. I am no different. There are graduations, marriages, births, deaths, moves, illnesses, vacations, … I’ve experienced all of these. Most of you have, too. These are important, but commonplace. We share these events with each other. We talk about them too. They are memorialized on Facebook and Instagram. They are not personal and private. The two things I am about to describe are those. Maybe some of you have had something similar happen. I’d love to hear about it. It would probably be healthy to discuss these more openly.

“A career is wonderful, but you can’t curl up with it on a cold night” ― Marilyn Monroe

Grad school failures

“We cannot change what we are not aware of, and once we are aware, we cannot help but change.” ― Sheryl Sandberg

The second semester of grad school was a big one for me. I had a couple of classes that were important to me: incompressible fluid mechanics and computational physics. All semester, I joked about one class as “incomprehensible flow”. Randy Truman was the professor (we ended up being friendly years later). The other class was taught by a Los Alamos fellow, Jerry Brackbill. Jerry was a colleague of a hero of mine, Frank Harlow. Deeper down. These classes were what I wanted to do: computational fluid dynamics (CFD). I struggled with incompressible flow, but I stumbled along. Jerry’s computational physics class crushed me. I floundered. Eventually, I dropped the class mid-semester rather than fail.

With this defeat squarely in mind, I doubled down on the rest of my classes. This included the incompressible flow course. With some effort, I passed with a “B”. I remember getting the final back. I sat there, and my heart sank as I thought about it. I remember getting up to leave, and a thought came to me. I was letting myself down; my dreams were collapsing before my eyes. That is a huge weight to bear. I also knew I was smarter and more capable than my classmates. I simply was not able to apply myself. I had to change, or these failures would become permanent.

I spent the summer after retooling myself. I went back and really learned all the things I had just memorized. It was a mission to really learn all the important things from my undergraduate years. I changed how I took classes rather radically. I revamped how I took lecture notes and did homework. When the Fall came, I hit the ground running with all this in hand. During that semester, I took the PhD qualifying exam. This was a large part of my summer work. I aced it. I was different in all my classes. Professors noticed and had rebooted my academic self. Years later, I became acquainted with Jerry Brackbill and collaborated with Harlow’s group, where he was a member. By then, I was a completely different man from the person Jerry had met years before. It became a tale of personal redemption.

“Becoming fearless isn’t the point. That’s impossible. It’s learning how to control your fear, and how to be free from it.” — Veronica Roth

The imposter dies

The next crisis was far more jarring. It happened 7 years into my time at Los Alamos after the birth of my second child, Jack. I was confronted with a growing list of responsibilities on the home front. During my time at Los Alamos, I had worked with two groups. First, with nuclear reactor safety (N-12), while I simultaneously worked on my PhD. Due to other parts of my past, I worked monstrously hard, holding a staff position at LANL and being a full-time PhD student. The previous crisis had created a monster. I worked constantly. Reading and research filled all my time.

After the PhD, I moved to research at the Lab. I got a job in the computational science group (C-3). It was a National project led by Phil Colella and John Bell. It was the opportunity of a lifetime. Between working with these guys and Los Alamos in general, I had some serious “Imposter Syndrome.” I could work really fucking hard. That was my silver bullet. I would just work harder than others and overcome my talent gap.

My life was on a collision course. The impact was a series of panic attacks. I had never had one before. They scared the shit out of me. It all hit one weekend as I had work to do and a major household project. I needed to take off work. All of a sudden, time was closing in on me. I coped with the immediate panic and calmed myself. I received a bit of SRI meds my wife had and started to introspect. I needed to rebalance my life. Part of this was rejecting the imposter syndrome. I belonged at the Lab and had proven myself. I was more than good enough to stand toe-to-toe with the best. I didn’t need to compensate anymore.

“It’s so hard to forget pain, but it’s even harder to remember sweetness. We have no scar to show for happiness. We learn so little from peace.” — Chuck Palanuik

What happened to me before Los Alamos?

Like all of us, I arrived at my first real job with a history and a largely unfinished article. That background matters to all that happened to me later. I have freely admitted that getting the job at Los Alamos National Lab was mostly great luck and fortuitous timing. I’ve wondered what less luck would have meant for my life. I can state without a doubt that my path is unavailable to the modern version of me. Every single element in my life’s foundation has been destroyed by the modern USA. It is just part of the erosion of social mobility that defines our lives today. The USA has truly fucked the next generation(s) over.

“Don’t confuse having a career with having a life.” ― Hillary Rodham Clinton.

I grew up as a military brat. We moved a lot, although not as much as most. My father had a career in the US Army as an officer. He practiced field artillery and nuclear weapons. My life was largely created by nuclear weapons to a degree that boggles the mind. I was a literal Cuban Missile Crisis baby being conceived in the wake of that. My grandfather planned the never-executed invasion of Japan for 1945-1946. My dad retired to New Mexico to serve these weapons for DoD and DoE. My wife’s father served in the Army at Los Alamos after WW2. She is the product of his transferring to Albuquerque and Sandia base in 1947. Perhaps it was fate that my career ended up with nukes.

All of this led to my arriving in New Mexico in 1979 at the age of 15. There, I finished high school for my last three years. I played football and wrestled, plus grew toward adulthood. Football reached its apex in my Junior year when we won the state championship. This was mostly due to two (to five) future NFL players, including quarterback Jim Everett (if you know, you know). I was an otherwise unremarkable student. I was smart, and I knew it. I didn’t really have to apply myself to do well. I did just enough so my parents didn’t wise up to how much I was fucking off

“You can be a natural athlete with terrible work habits, and that ends up wasting your gifts.” ― Vernon Davis

Here, I should step back. All of this came from my earlier life. My father’s career and life shaped me for good and ill. He is nearing the end of his life being in hospice. His story was the backdrop for much of what was good, and bad about teenage Bill. I did leave high school with scholarships in hand. I was a National Merit scholar, and had a full ride from the Air Force. I would join ROTC at the University of New Mexico. On the flip side, I was headed for state school. In retrospect it was where I belonged. To go to a more competitive school I would have needed that first crisis to happen to 18 year old Bill, not my 24 year old self. One of my key lessons in life was that my dad’s life was ruled by fear. That was something I would not allow to govern my life, or my decisions. I’ve largely been successful on that, but it always looms over everything as a shadow.

My father graduated from high school in 1955, and with his cousin joined the Marine Corps. It was a terrible experience, but his fear of being drafted and having to serve as an enlisted man pushed him to join ROTC at college. There at college he met my mom, and afterwards embarked on being a commissioned officer. There he was part of that potential Cuban invasion force, as a forward Artillery observer. A mission with an extremely short life span. After that he was assigned to oversee a battery of 8-inch howitzers in Northern Greece. These howitzers could deliver a nuclear package. This is where he was when I was born.

Shortly thereafter while I was a toddler, my father applied for and was admitted to law school. This,opportunity was not taken, as my mother urged him to decline the offer. She did not want to be the wife of a graduate student with a small toddler, me. As a result my father was sent to Vietnam for a tour of duty that proved to be absolutely disastrous for his military career. This was probably the most pivotal event of his life. It changed everything. He and his boss hated each other and my dad’s fitness reports reflected that hatred.

When he returned after his tour of duty, he was depressed and now fearful of the path that his chosen career would take. My father’s crisis, and state of mind would cast a pall over my childhood. It shaped the rest of my existence as a child. He spent xix years in Lawton, Oklahoma, at Fort Sill. He was an instructor at the Field Artillery School, he worked hard to distinguish himself. When I say he worked hard it was 100-hour weeks, just working his butt off, and rebuilding his career. He was just trying to achieve at least one more promotion. That next promotion, if he received it, would allow him to work in the military all the way to retirement. Do I see a parallel with my own life here? Of fuck yes, I do.

This became the focus point and the obsession of his life at that time. It also condemned all of us in the family to be passengers on this trip. It ultimately corrupted him in a sense as the sacrifice he made would be something that he would take in the form of a crown of thorns later on in life. It is a bitter and harsh lesson that I truly hope I can learn from. I want to avoid being like that as I move towards old age.

“I must not fear. Fear is the mind-killer. Fear is the little-death that brings total obliteration. I will face my fear. I will permit it to pass over me and through me. And when it has gone past I will turn the inner eye to see its path. Where the fear has gone there will be nothing. Only I will remain.” — Frank Herbert

Bill Goes to University

I graduated from Eldorado High School in Albuquerque in May 1982. Right after I got a job at a local McDonalds as a burger flipper. Two weeks into that job I took a lunch break with a cute blonde gal who hired on at the same time. After a bit of retrospectively funny awkwardness we became good friends. She was my future wife, Felicia. She liked my sense of humor, fun sense, and intelligence. We were both military brats. We were both going to the University of New Mexico too. We would be taking a class together, ROTC. I gave up my Air Force scholarship because I realized that I didn’t fit in and I would not be happy there. That’s an understatement, I would have been miserable and a terrible choice. It would likely be a failure. Stunningly, later in my life I had so much confidence that I refused to see that same lesson at Sandia. In many ways my failure to learn this and embody this decision later in life wasted so much of my potential.

There were two very important things that happened in my undergraduate years:

1. Meeting my wife, getting married. It was us together forming new families to make up for the shortcomings and disappointments in our families of birth. We both wanted to escape from unhappy home lives, and found happiness together. This union has been key and drove my progress through life. It has been the greatest meaning I have found in anything.

2. The extent to which I put myself through school mostly on my own. Actually it was as a team with Felicia. I worked a job for the entirety of my undergraduate career. During that time I worked harder than I would ever work in my life, taking a full load of classes and holding down a full-time job. It led to legendary, 100+ hour weeks, exhaustion, and effort only a 20 year old could muster. After this, everything else I ever did was easy. I worked at McDonalds and became a manager. It was a huge life lesson. I also worked for the best boss of my life there, Brenda Adcock. I’ve had other great bosses, but Brenda was in a league of her own. She was hard on me, taught me a lot and gave me opportunity to grow. She’s had no equal.

I broke from the pattern my father set, and did not allow fear to drive me. As I have discovered fear is pernicious and enters into any nook or cranny. It is always lurking in the shadows waiting to overwhelm you. Still I remained conscious of it and pushed back against that tendency.

“What would you do if you weren’t afraid?” ― Sheryl Sandberg,

My undergraduate career was marked with some degree of mediocrity. This was based on some of the laziness that I got away with in my younger years, along with my very hard job. I had a need to support myself and Felicia (she pulled more than her own weight). She would drop out of school after two years and work full time. She got a job with good benefits and medical insurance. After I got my PhD, she went back to school and got her degree. Later on she got her Masters once she starting working at the University. The result of my mediocrity, in the end, was a stunning lack of prospects when I got my bachelor’s degree. I applied for a number of jobs, none of them even remotely prestigious, and received not one single interview, not one single bite. I was left with almost nothing. I felt like a real fuck-up.

The back-up plan was grad school and grad school at the same place that I was an undergraduate. Again the least prestigious way to go, but I went and entered into that first year and I did not change. I kept on being the person I was as an undergrad. This was setting myself up for the crisis a year later. My inaction and lack of response to the clear feedback from life was pretty contemptible. All of us was leading to the moment of that first crisis I described and my change as a person. I simply hadn’t let myself fuck up quite sufficiently yet.

Graduate school was a huge learning experience and laid out the platform for me to ultimately excel at Los Alamos. I started off following the lead of others, doing a master’s degree project that was simply a mindless extension of others’ work. It was in modeling space nuclear reactors. By the end of graduate school I had started to eagerly and ravenously eat up new topics. I learned the basics of computational fluid dynamics. One of my office mates in graduate school, DV, was a huge influence. DV was a graduate of IIT in India. He turned me on to the works of Suhas Patankar, who shapes much of mechanical engineering CFD, following along the work of Brian Spalding. This led me naturally to the work of Frank Harlow, who inspired Spalding and laid much of the groundwork for CFD. I devoured and starting implementing their work. I was eager to understand all of it.

Over time, I became increasingly dissatisfied with this approach to things and started to look for other ideas. In that time, I learned about the work of Jay Boris and flux corrected transport (FCT). Ultimately, I found that approach to be lacking. I was attracted to the work of Ami Harten and Bram Van Leer by the time I left school for Los Alamos. These interests shaped my PhD work at Los Alamos, and created much of what I have focused on for the remainder of my career. At the beginning of my time in Los Alamos and periodically throughout my time as a professional, I returned to nuclear engineering and space power. My original inspiration was the manned Mars mission originally scheduled for 1981. This manned Mars mission would have been rocketed by nuclear rockets developed at Los Alamos. These were something that I was able to see in person and learn about when I arrived at LANL in my first few years there. There was a short-lived interest in Mars again as the Cold War ended and the Soviet Union fell apart.

My growing self-confidence had a huge impact on me and ultimately propelled me to leave the university. In the end, Los Alamos would give me far more than any graduate school could have. In those years Los Alamos would be better than the best school imaginable. It was beyond Ivy League in quality and scope. We should truly mourn what we have lost in destroying these institutions. They used to be great and I felt myself living in their wake pulling me along.

The consequences of that change were borne out during my second year of graduate school when I received my master’s degree. Once I had become a different person, I gained a confidence and a strength. That strength made the person who could not longer tolerate my advisor’s behavior. I could no longer tolerate his behavior, or his way of managing people. I started to see him as a bully and I refused to be bullied. To some extent this was cultural on his part. Nonetheless, I witnessed things that I found unacceptable in how others were treated. I had rapidly learned a great deal. The last straw was my advisor’s inability to learn from me. He always had to dominate me. Even though I had a fully funded Ph.D. research project through NASA, I decided that I could not stay at school there.

It was time to leave and find a new path.

“Fear doesn’t shut you down; it wakes you up” — Veronica Roth

Bill gets a real job

I looked at other graduate schools but my poor grades, and unremarkable academic record made that impossible so I was looking for a job. It would have also meant a lot of debt. In those days that felt dangerous. This job hunt would completely change my life. It also was something of immense fortune that I looked for a job when I did. It was a peculiar time. There were visions of a new space race, and also the end of the Cold War, with views of changes in our nuclear weapons program. Somebody with my background was almost assured a job. There weren’t nearly enough of me’s to go around.

I’ve often joked that I had three things that were absolutely essential for getting a job:

1. I had a Master’s degree in nuclear engineering.

2. I was an American citizen.

3. I had a pulse.

The result was I applied for six jobs. I had six interviews, and six job offers. It was just a matter of taking the best of them and the best of those jobs was at Los Alamos National Lab. It was working with a nuclear reactor safety analysis group. It took some doing because the bureaucracy at Los Alamos is atrocious. They absolutely suck at it. They still do today. I also had a job offer from another National Lab in Idaho, but the prospect of living in Idaho Falls in those days seemed dismal, horrible. I’ve visited and its not quite as bad as I had thought. At that time Idaho Falls failed what I called the radio test. I would sit in my hotel room with the radio alarm. I would try to tune in the best radio station I could find. In Idaho Falls that station was playing the Osmonds!

I pushed Los Alamos and they delivered a job offer in time. The other jobs were all with the so-called Beltway Bandits. In some cases they had produced interview trips that were comical in their outcome. They were also professionally horrifying in what I learned about those companies. Thank God I didn’t end up there. I’d be a totally different person now.

I took the job at Los Alamos. I already knew that my good fortune was almost beyond reckoning. I entered with some degree of confidence and knowledge of how to work extremely hard and apply myself. I had started become enthusiastic about CFD. Los Alamos seemed like a veritable cathedral of science. It was one of the most famous places for science and especially for all things nuclear. I was offered something miraculous on a silver platter. It was an almost mythical opportunity. I was going to grasp it and work my ass off. In my time at Los Alamos, it also grew my belief in the patriotic service of working there. This is one of the things that I most firmly embraced and still believe in today. I could pursue my science passions with a sense of meaning and purpose.

“I’ve learned that making a ‘living’ is not the same thing as ‘making a life’.” ― Maya Angelou

tl;dr

Brute force computing power has become a one-size-fits-all plan for all computational progress. This is true for classical computational science and now AI. Computers market themselves to politicians and the business community. I’ll freely submit that more computing power is always good. These computers are so expensive. Plus, they are big and loud with lots of blinking lights, so idiots love them too. This approach follows the path of the exascale program. It was declared to be wildly successful!

The key is seeing what is not there. What you do with a computer matters more than the computers themselves. True for AI; true for computational science. We need to see what was not done and not invested in while focusing on hardware. This is domain knowledge, experiments and tests, mathematics, algorithms, V&V, UQ, and applications. All of these are subservient and diminished to serve the hardware focus. The hardware focus will eventually bring ruin.

“The reasonable man adapts himself to the world: the unreasonable one persists in trying to adapt the world to himself. Therefore all progress depends on the unreasonable man.”

— George Bernard Shaw

What We Focus On

I’ve spoken out about our obsession with computers before. For most of my professional life, computing hardware has been the emphasis. This emphasis is short-sighted, especially now. The benefits of hardware are becoming less and less, with more effort needed for fewer gains. This all stems from the death of Moore’s law in all its forms. This was the exponential growth in computing power from the 1960’s to about 2010. Our overemphasis on hardware was a dumb idea 30 years ago. It is even dumber now. The dumbness stems from a lack of balance. Computers are great and important. More computing power is always good. However, what you put on them matters even more. This priority has been lost in the mourning of progress for “free” with Moore’s Law.

This lack of balance has been present for a long time, and our deficit is huge. It has played a role in the setting of American scientific dominance. We have failed to make sensible investments in science for decades. Computing has been one of our biggest investments. This investment has been focused on fighting reality and physics. It is guilty of failing to recognize the breadth of the computing ecosystem. Thus, our idiotic strategy has been an accelerant to the decline. One of the key reasons for American decline. There is a fair amount of corporate welfare, too.

Computing folks always talk about things like it were an ecosystem, including software and hardware. It is like an ecosystem. Predator-Prey balance matters there and can wax and wane. Our current system is like the deer population in much of the USA. Not healthy and doing damage. In this analogy, the wolf packs and cougars are missing. The predators are like algorithms, physics, and applications here. They are difficult to deal with and strain human systems, but are essential. Without the balance, the ecosystem is out of synch. Worse yet, we are adopting the same ideas for AI. The strategy there is hardware-focused. The rest of the ecosystem has been slaughtered.

The last blog post talked about part of what was missing. That is V&V. Now I’ll talk about what is in its place. Hardware. Software that the hardware demands for basic functionality. Algorithms that depend on the hardware. Everything else is missing. As you get closer to the use of the hardware, the effort diminishes. As you move closer to applications, the work gets harder and more failure-prone. This is key! Without trust, those failures cannot be accepted. They become proof for the propriety of withdrawing trust. Failures are the epitome of learning. Research is all about learning. This is why American science is faltering.

“Part of the inhumanity of the computer is that, once it is competently programmed and working smoothly, it is completely honest.”

— Isaac Asimov

Without failure, knowledge stagnates. This is exactly what has been wrought. We need to recognize the stagnation. Worryingly, we’ve made the same choices with AI. We need to take a different path. We need to admit how badly we’ve fucked this up. Instead, it’s all a massive “success” as our leaders declare. It isn’t. We are wasting effort and money on hardware. It could be better invested in other parts of the endeavor. We need to learn from this massive failure. This is not about not investing in hardware. That needs to happen. What we need is a better balance and care for the entire ecosystem. We have fed the bottom of the ecosystem for decades and slaughtered and starved the top of the ecosystem.

“Computers are useless. They can only give you answers.”

— Pablo Picasso

Computers and Money

The emphasis on computing has been a constant feature during most of my professional life. We chose that path when nuclear testing stopped. We stopped the real-world tests. Then we invested in the part of the virtual world farthest from the testing. The sales pitch was that computers would replace the testing. It is not a rational or logical approach. The main reason is political. Back in the 1990’s, our leaders needed to sell “no testing” to the Nation. Two things made hardware sell: politicians can see and touch computers, and computers are bought from companies. Politicians can see computers, which are big with lights and make lots of noise. They cannot see codes, or algorithms, math, or physics. Moreover, companies have money, and our politics runs on money. Back then software was intangible. The internet was barely a thing. So they sold the computers.

“Growth for the sake of growth is the ideology of the cancer cell.”

— Edward Abbey

Within a few years, scientists identified the gaps in this plan. The hardware was great, but the science was missing. To have a credible virtual deterrence, the science needed to be “world-class”. There was a recognition that what the computers computed mattered. It was not enough to simply have super fast computers. A faster computer is not automatically better unless it also does things right. Furthermore, the reality needed to keep the computers honest and adhering to the physics was gone. That gap could not be filled with bits and bytes. It could only be filled with physics, math, and refined practice. They added things to the program to fill the gap. Science actually had a moment in the sun.

It was a short-lived sunny moment.

This did not last. Monied interests became even more powerful. Science continued to fade and decline. The hardware as the path to success narrative took hold again. Science is hard. Hardware also had the message of crisis. Moore’s Law had held for decades and progress in computing was sort of free. It just happened. Now that progress would take focus. Ultimately physics would take over and no amount of money would yield hardware progress. You just had to spend a shitload of money to buy more hardware. Computer companies love that! Their lobbyists were flush too and greased the skids for hardware.

“Remember the two benefits of failure. First, if you do fail, you learn what doesn’t work; and second, the failure gives you the opportunity to try a new approach.”

— Roger Von Oech

The Exascale Computing Program

This takes us to late 2014 and 2015. My blog was in its infancy. We got a new program to feed the Labs and sell comptuers. It was the push to make the first Exascale computer. This would be a computer that can work at an exaflop. Let’s just submit that the speed of computers is big dose of bullshit on the face of it. Let me explain. We don’t get an exascale on any application we give a fuck about.

The speed is measured with a benchmark called LINPAC which does the inversion of a dense matrix. It is almost always the best case scenario for hardware with lots of floating point operations per memory reference. Thus the benchmark gets great performance for computers in general. More importantly, it does not reflect what happens in the vast majority of applications. Especially our most important applications. So the benchmark is basically marketing, not science. It has distorted our view of hardware for decades. Someone should have called bullshit on this long ago. Its a fucking farce.

Progress in the power of hardware had started to wane. The curve of progress that is Moore’s law was bending downward. It was a crisis! We need an exascale computer to fix it. Computers by themselves are the core of our scientific and military deterrence. Plus science is even harder. The USA doesn’t do hard any more. Funding science doesn’t do shit for corporate interests. At least corporate interests in the next quarter. Science is only going to help the future and not a specific company. Science has no lobbyist. The future doesn’t either. So fuck science and the future.

The answer to the need to fuck science and the future is the Exascale Computing Program (ECP). It was a really huge waste of money. Of course, no one ever says this. No one ever admits what is really going on or why. This is simply the inevitable outcome. Sure we got faster computers, but we also hollowed out the ecosystem. In that analogy it was a slaughter of apex predators. In addition, we encouraged the deer to breed like flies.

It makes sense to explain this. How such a “successful” program could be such an ensemble of bad ideas. The stupidity was baked in from the jump. The whole program was designed to be unbalanced. It starved the science. The science part was already done, it was just a passthrough. The new computers would just magically make science better! No need for V&V either. All the calculations would magically be correct by the power of computers. No need to check the quality. V&V would just find the problems and no one wants that.

“We don’t really learn anything properly until there is a problem, until we are in pain, until something fails to go as we had hoped … We suffer, therefore we think.”

— Alain de Botton

It reflected a combination of naive and superficial views of what computational science is. It has misconceptions and outright fabrications about how to ensure quality. Alone, a faster computer will not produce quality results unless you do many things correctly. ECP just assumed all of that was in hand. Further, it assumed that the faster computer is all that was needed. The basic premise is that faster computers will naturally improve everything. It only funded things that were necessary with the new computers. The applications rather than being the focus of the work were simply marketing. They were examples of all the awesome shit the faster computer could do. Better science would just happen by osmosis. No domain scince was really needed.

ECP is done. ECP declared to be a “success”. So why belabor these points at all? We are taking the same approach with AI.

Fervor About AI

“The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.”

— Edsger W. Dijkstra

It’s hard to separate this trend from the general sense that the United States is overly focused on the industrial side of things. These computers have increasingly become large big-ticket purchases for industry and government. You might have noticed that computers and “data centers” are a huge focus recently for AI. NVIDIA is the richest company in the world by selling computer chips. It is clear that the funded path for improving AI is faster (bigger, more expensive) computers. There is almost nothing else on the map. ECP paved this road and its an even dumber road for AI.

This is true to a greater degree than ECP by a mile. While the scaling of value in computation with computing power was terrible in ECP, it is worse for AI. AI improves far more slowly with computing power than scientific applications. For ECP the most optimistic strategy needed more than an order of magnitude in computing to get double accuracy. For AI, the amount of computing needed for this is 100-1000X. All of this with Moore’s Law being dead. AI is running out of data too. Its already eaten the entire internet. In both cases there is a stunning lack of recognition for what drives progress. These are algorithms and domain science. This entire moment is driven by an algorithmic breakthrough, the Transformer. Computing was at a critical mass to take advantage, but not the reason for the phase change.

AI also needs domain knowledge especially for science. We also have a profound lack of understanding where answers come from. The pathology of correlation equaling causation is quite central to AI. False positives are a very real danger. Indeed this could be part of explaining hallucinations. Training of models and bias is probably some of this along with the bullshitting of models. All of this demands V&V. Approaching AI with profound doubt and questioning results would simply be common sense. There is a huge need for deep applied mathematics to help comprehend AI better. Applied math has been declining for decades. A horrible trend for computational science. It may be a fatal trend for AI.

With the major DOE program, Genesis, none of the healthy balance is seen. It simply amplifies the imbalances present under exascale. The whole program is bunch of stunt projects. Core science, algorithms, applied math and V&V are all absent. The whole thing smells just like ECP. The aroma is a stench.

“Each day we take another step to hell,

Descending through the stench, unhorrified”

— Charles Baudelaire

We have Failed in Advance

Earlier, I talked about failure. It is essential. We are engaged in systemic failure that provides no lessons. If one learns and improves on the basis of failure, success is the usual outcome. ECP is really just failure. Full stop. We are structuring our AI future just like ECP. It is a failure by construction. Within our current incentive and value system both are a success. This is simply because of money. These projects get funded and make people rich. Success is not knowledge, it is just funding. It is a value system that leverages funding without investing in the future. The deer are breeding like crazy and we are driving the predators to extinction.

“Someone’s sitting in the shade today because someone planted a tree a long time ago.”

– Warren Buffett

The future has no constituency. The only future we seem to care about is the next quarter. We’ve seen this with how climate change is being ignored. There inconvenient facts are simply ignored. The same is happening with all this computational stuff. The terrible scaling laws I mention above were ignored in ECP. The even worse scaling laws for AI are ignored. They are such a bummer. The difficult work needed to advance algorithms, understand technology plus find problems are all ignored. These are too hard. It is too likely that progress would be uneven. We cannot manage hard things that payoff in decades instead of months. We have failed in the worst way possible. We have failed at the starting line.

“Between stimulus and response there is a space. In that space is our power to choose our response. In our response lies our growth and our freedom.”

— Viktor E. Frankl

tl;dr

Verification and validation (V&V) is receding from focus. This has been happening in traditional computational science for the past 15-20 years. Now, attention is focused on AI. The problem with V&V is its attention to quality. Quality is something we don’t care about anymore. More importantly, V&V is finding failure, and failure is the engine of progress. We’ve learned that success is all marketing and messaging. Success can simply be declared. Why do the work? AI has none of the quality advantages of traditional computational science. AI hallucinates regularly. These hallucinations are actually lies or bullshitting. AI confidently provides answers when it knows nothing. V&V could detect this, but that wouldn’t look like success, so no V&V.

“We can judge our progress by the courage of our questions and the depth of our answers, our willingness to embrace what is true rather than what feels good.” ― Carl Sagan

V&V for AI?

This was not my first title. My first title was actually “Where the fuck is the V&V?” I found that this was probably too jarring even for me. The reduced readership would be bad, but it captures my thoughts about what’s going on. V&V is a truly important part of the quality of anything computational. It was first slowly, then rapidly disappearing. The consequences of this are profound and quite poor for the quality of anything computational and the progress in science. It is bad enough for “classical” computational science; for AI, it is malpractice. That same lack of quality and progress is now being embedded in work on AI.

I’ve written many times on the concept that V&V is really just applying the scientific method to computations. It follows that a lack of V&V is a lack of science. This is what is going on. Part of science is progress and the advancement of knowledge. Progress depends on failure. Failure is how we learn. V&V is about looking for failures and gaps. It is up to the programs to respond to these failures by improving and closing these gaps. For science and progress to proceed, this is not optional. It is the essence of what we are investing in. Somehow, we have decided that all the failure and learning is optional. Computational science still needs progress. It seems we’ve missed that. AI is even more immature. Somehow, we have decided that success can be had without the hard part. This is not objectively supportable.

Our leaders are truly fucked in the head.

“It is hard to fail, but it is worse never to have tried to succeed.” ― Theodore Roosevelt

They don’t want actual success; it has become too easy to just declare it. Somehow, we’ve all bought into this fantasy. We have become comfortable rewarding outright incompetence. I have seen it in person. That is where the money is, and money is all that matters. This is true for business and science. Reality will not look kindly on our choices. AI in particular will be harmed by the approach we are taking. For it to evolve and grow successfully, the critical feedback that V&V produces is essential.

The core of the problem is the incentives the leaders respond to. None of the incentives connect to quality and progress. Our leaders have learned that quality and progress are expensive and uneven. We can have success on the cheap if we simply declare it. Any practice of legitimate V&V is a threat to the declaration of success. The warning signs for AI are clear and obvious. The leadership benefits from avoiding the work of V&V (and saving $$$ and complexity). The simple route is defining victory without quality assurance. Who’s going to check? No one! That shit is expensive. We already have the most awesome technology, no progress needed. This is a recipe for mediocrity and decline.

In AI, we see a technology that needs checking and to be treated with significant doubt. V&V is a practice that reveals this doubt. In many cases, the V&V offers assurance of quality, too. AI needs this, especially if used for consequential purposes. In science and engineering, we can map a path to a more reliable AI. To get to reliability, we need to work out the faults and remove them. Instead, we simply see a technology that is being implemented and executed as if it were perfect (and almost magical). The reality is that it is far less perfect than what it claims to replace.

This is nuts. This is shortsighted. This is completely and utterly irresponsible. Judging by the way the leaders of our society act, we should expect irresponsibility. Irresponsibility is exactly what we are getting. We as a society will suffer over the long run from today’s foolish decisions.

“Have no fear of perfection – you’ll never reach it.” ― Salvador Dali

V&V is Regressing in Plain Sight

I’ve seen two successive major programs at the Department of Energy, both neglecting V&V. One was the Exascale program. Now we have the Genesis program. They would claim V&V was “baked in.” This claim is bullshit. In the current incentive system, V&V produces friction. The response to friction is rejection, and V&V gets jettisoned. It is only supported if the results confirm the success narrative. As soon as V&V needs to confirm a narrative, it ceases to be V&V. It becomes a bullshit factory. In the precursor program ASC, this is where V&V has evolved. Over the past decade, V&V has become defanged and toothless. All assessments now need to be positive. Those who are not are buried. One such burial led me to retire.

“Life is full of screwups. You’re supposed to fail sometimes. It’s a required part of the human existence.” ― Sarah Dessen

The role of V&V is to determine the correctness of the computational work that’s done. Part of determining the correctness is that, when there are issues or problems (and there always are), you have a plan to fix those things. Fixing shit is progress. Fixing shit is what scientists and engineers are good at. What the leadership has discovered is that the cheapest and easiest way to succeed is to simply declare it. Part of this is avoiding the whole V&V step altogether. This, in our money-driven world, is the most efficient way to do things. It’s really a stupid way to fuck everything up.

“We are all failures- at least the best of us are.” ― J.M. Barrie

The Cost of No V&V

The real process of science, which V&V is at its core, is messy, expensive, and time-consuming. These are all things the leaders would rather do without. It’s become much more efficient and cost-effective to simply declare success and be excellent by definition. I saw this in spades during the Exascale program, where V&V was nodded and winked at but rarely done. With that program being a “success: we see the same approach with Genesys, I fear exactly the same will be done. The leaders will declare and bullshit their way to glorious success. AI is too immature and dangerous for this level of abject irresponsibility. The deeper cost will be a stagnation of this important technology. Basically, we are giving up on the future.

As I’ve noted with AI, the role of V&V is more important. It still was with the sort of computational science done with Exascale-scale computing. That program failed to make progress aside from fast computers. With AI, there are no decided-upon models or methods to solve things that have rigorous connections back to physical and mathematical theories. There, it is the data that drives things, along with algorithms that manipulate that data. Algorithms that converge but only in some nebulous, unspecified sense. They are without any sort of guarantees that we’re used to in computational science. This makes everything harder with AI. The freedom it provides is an illusion. The result is something that can often give answers that are called hallucinations. This is the most generous way to put it. In many cases could be called outright lies or bullshitting. Our current AI practice is to give answers without guardrails or warnings with complete confidence.

Now we are trying to do science without V&V, which would unveil the bullshit. For AI to do science successfully, it needs to have guardrails and come with a “bullshit” detector. V&V is that bullshit detector. The program that has been unveiled is not science. Maybe if I’m generous, I could say it’s bad or weak science. Somehow, we have gotten comfortable with programs that are called science while being unscientific. This needs to stop. By avoiding failure in small ways as part of this program, we are failing massively.

“Success is not final, failure is not fatal: it is the courage to continue that counts.” ― Winston S. Churchill

Disappearing V&V

This has become an almost ever-present thought in my mind. I watched as the V&V programs became funded and important back in the late 90s, and then went through a zenith and decline. Now I’m watching the V&V programs dissipate, fall into uselessness, and become utterly feckless. In recent years, it has turned into a rubber stamp. Whenever V&V found a problem, management would just bury it and ignore it. Only positive news was accepted. The essence of toxic positivity. We are allowing management to act like children who live in a fantasy world.

V&V for modeling is essential. This is where we are solving well-known, well-understood, and well-accepted models. These models are solved with well-known, well-accepted discretizations using real geometries. It is still essential; it still finds problems. V&V is needed to manifest the full scientific method in these domains. Now we see AI coming to the fore. With AI, we see even less V&V, even where there are none of the advantages that classical computational science has. Even when AI has a known propensity to hallucinate (lie, BS,..). V&V is more needed with AI, and yet there is less.

“You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete.” ― Buckminster Fuller

The real tension is the notion that we have already created the technology breakthrough. Now it is simply a matter of showing what it can do (and make a shitload of money). The current programs have declared victory and eschew the need for progress. We just need to demo the awesomeness. This is a self-own. This is why there is no V&V, and it is a symptom of extreme weakness. They cannot stand to have any hard look at the current state of things. That is what V&V would do. It would do a great deal more. V&V would power progress by pointing to problems and weaknesses. These problems and weaknesses are where research and advances are needed. This is the very heart of the flywheel of progress.

Without the introspection that V&V provides, we have stagnation. My belief is that the technology (AI and computational science) is quite far from where it should be and needs serious attention. Certainly, we need to demonstrate the current state of AI. The key to progress is a stern examination of the quality of this work with a critical eye. V&V provides this and a map of where progress is needed. Without V&V, there are claims of false victory and stalled progress. Progress is grounded in failure because failure is learning. The sort of victory being planned now is hollow and feeble-minded. It is not how science is done, and the recipe for mediocrity. Science in the USA is already quite far along the road to mediocrity. Our current approach widens that road into a superhighway.

“Those who make peaceful revolution impossible will make violent revolution inevitable.” ― John F. Kennedy

This is my 400th post on the Regularized Singularity!

tl;dr

Few topics in computational physics are as polarizing as numerical dissipation. Dissipation is ubiquitous in nature and technology. Often, it is unwanted or a nuisance. Its absence is usually wishful thinking. Some schools of thought think they can model it effectively. For general numerical modeling, some sort of effective dissipation is essential to robust, reliable simulations. To understand the various viewpoints requires a far more nuanced perspective. Numerical dissipation or its absence is the direct result of different philosophies. Usually, the grounding philosophy is unstated and implicit. Here we explore this in depth.

“Whenever a theory appears to you as the only possible one, take this as a sign that you have neither understood the theory nor the problem which it was intended to solve.” ― Karl Popper

The Physics of Dissipation

The physics of dissipation is essential. The part of dissipation that is least important in current methodology is that which is well resolved. I mean no disrespect towards the types of physics appearing at the nano scale or in well-resolved areas with very exotic viscoelastic effects. The really important parts for nature and technology are where the dissipation is so small it can’t be resolved. These are challenging in the extreme. The truth is that there is a certain magic in dissipation at those scales, where the amount of energy and entropy evolve due to the non-linear impact of the hyperbolic parts of the system. These dynamics remain mysterious.

This sort of physics dominates shock waves and turbulence. If one is dealing with highly energetic physics of almost any kind in technology or nature, one is dealing with these sorts of physics. Moreover, detailed direct numerical simulation of this kind of physics is a pipe dream, and there’s no way that computers available in any of our lifetimes will be able to tackle this. It is completely out of scope. It is also the kind of physics where AI isn’t the way out. It requires deep understanding and mathematics that is often quite just beyond our reach. We need a focused exploration of the physics and mathematics of it. Something we are not doing as a society.

This is exactly the domain where numerical dissipation is essential for computational science, and all the controversy lives. There are two main schools of thought:

1. This is built into the dissipation to the numerics, effectively making it implicit or modeling it. The domain of Riemann solvers and high-resolution methods.

2. One of the more foolhardy aspects is that the physical modeling that we have today is actually up to the task of accurately depicting its effects.

The thing that’s often missing is an understanding of how numerical techniques like artificial viscosity are intimately related to the fundamental models. They are far more the same than different, and there lies the path ahead.

“In theory, there is no difference between theory and practice. But in practice, there is.” ― Benjamin Brewster

Shock Capturing and Dissipation

To understand numerical dissipation, its origins are essential. Artificial viscosity allowed shock-capturing methods to work, but I need to rewind a little. In World War 2 the USA built an atomic bomb. Part of the design and creation of the weapon was numerical simulations of shock waves. This was, to a large degree, the vision of John Von Neumann. It was brought to life in Los Alamos by Feynman and Bethe. Von Neumann had developed a numerical method for solving shock waves. The issue was that it failed spectacularly ( blowing up into horrible oscillations). I

Instead, a method designed by a cadre of the British mission developed a method that worked. Peierls and Skryme worked on ideas using shock tracking plus finite difference (well documented by Morgan and Archer). This method successfully computed the problem they set before them. They also puzzled over the failure of Von Neumann’s method. Peierls suggested that dissipation was the missing element, but the greats of Los Alamos moved on. After the war, as the Cold War was warming up, Robert Richtmyer returned to this problem. The work at Los Alamos had grown in complexity, and the methods of WW2 weren’t up to the task.

In 1947 and 1948, Richtmyer devised a numerical dissipation to add to Von Neumann’s method. It worked extremely well and was published to the World by him and Von Neumann in 1950. This method was called artificial viscosity. The derivation by Richtmyer was based on the physics of shock waves and the changes in entropy required for the correct solution. These asymptotics were embedded in the method, and Richymer’s method was not arbitrary. This method was then a proof of principle.

In short order, the use of dissipation made methods work, and many methods flourished. Harlow at Los Alamos could advance new ideas for methods and codes. Lax was inspired by Los Alamos and created a method where dissipation was implicit in the differencing method. There was no added viscosity. Instead, the viscosity was built into his Lax-Friedrichs method. Von Neumann took his ideas to Princeton (and the Institute for Advanced Study). There, he was interested in weather (and climate) modeling.

“It doesn’t matter how beautiful your theory is, it doesn’t matter how smart you are. If it doesn’t agree with experiment, it’s wrong.” ― Richard P. Feynman

In 1956, Norm Phillips did the initial calculations of a month of weather in the Eastern USA. All was well except for the appearance of those pesky oscillations by the end of the month. The follow-on work fell to Joseph Smagorinsky (that name should be familiar). Smagorinsky was going to move to 3-D and implement a suggestion to fix the oscillations (ringing). The suggestion was made by Von Neumann’s famous collaborator, Jules Charney. The work culminated with his 1963 paper, which was simultaneously the first LES calculation and global circulation model. The artificial viscosity was implemented, too. This was the first LES model, and it was just a trivial (naive) 3-D implementation.

Thus, the first LES model was simply Von Neumann-Richtmyer artificial viscosity!

This gets used to model as an alternative to numerical viscosity, implicit or explicit. It would be too much to call it bullshit to model it, but not by much. Modeling is a completely desirable and valid activity. The wrong thing is failing to see the basis of this effective model. There are some clear messages that we’ve failed to take. How is a method based on shock dynamics also an effective turbulence model? How much of the model is physics, and how much is numerical stability? Are the two concepts remotely separable?

Modeling and Dissipation

“It is the theory which decides what can be observed” ― Albert Einstein

The place where all of this collides most acutely is turbulence modeling. Turbulence modeling has three basic flavors: direct numerical simulation (DNS), large eddy simulation (LES), and Reynolds-averaged Navier-Stokes (RANS). These each come with limits and capabilities. By the same token, the state of the art is still lacking. I think the reasons for this flow through this topic.

Let us start with DNS. It is a useful practice where no model is used at all, other than the Navier-Stokes equations. The numerical solution is just an accurate method solved with a fine mesh. The resolution is largely a rule of thumb and common practice. Numerical error is rarely or never estimated. The solutions compute and don’t look like shit, and they are accepted. DNS is very limited. We struggle to compute “hard turbulence” with our biggest computers. The scaling with computing power is quite dismal as well.

Worse yet, it is canonically incompressible. I’ve noted that incompressibility is grossly unphysical in several respects. The largest issue is causality, where the sound speed is infinite, and thermodynamics is annihilated. Thus, this part of the simulation is divorced from the physics that could be the heart of the solution. I believe it is very likely that the solution to turbulence theory may well be found with thermodynamics and shock wave dynamics.. This would be in the opposite asymptotic regime to where it is usually focused on.

LES comes next, allowing more to be done. As noted, the classical model is the Smagorinsky dissipation, which in turn is just artificial viscosity. Its simple and naive form is its Achilles heel. There are none of the structural changes embedded in it that have been added to artificial viscosity. For example, artificial viscosity is turned off in adiabatic regions. These differences correlate strongly with the modeling suggested by scale similarity models. The origin of LES should be recognized along with all the aspects missed when the two uses are separated. There has never been a reintegration of the topic after its birth. Perhaps implicit LES (ILES) is a sort of this.

Finally, we have modeling with RANS. It comes with modeling approaches starting with simple eddy viscosity models all the way to very elaborate moment closures. These models are supposed to look at statistical ensembles of flows averaged in some manner. The models are designed to capture the average behavior of flows. In general, these are essential to the engineered application of systems. Typically, these have issues and requirements for things like boundary layers, where numerical resolution is demanding. They are also integrated by methods that usually have a great deal of implicit built-in dissipation.

This is our next stop.

“There is only one kind of shock worse than the totally unexpected: the expected for which one has refused to prepare.” ― Mary Renault

Implicit Dissipation

“Any sufficiently advanced technology is indistinguishable from magic.” – Arthur C. Clarke

Now we turn to the built-in dissipation of methods. I touched on this with the work of Lax. The canonical method with implicit dissipation is upwind differencing. This method is most cleanly and broadly described by Godunov’s method, where the Riemann problem is employed to determine the upwind propagation. In many quarters, upwind differencing and dissipation are treated with absolute disdain and ridicule.

As I found in my work on ILES, the issue with upwind methods is the order of accuracy. The ridicule should be confined to the first-order version of the method. We discovered that the combination of second-order accuracy and conservation form yielded a different conclusion. This combination converts the truncation error for quadratic nonlinearities to something “magical”. The form of the nonlinear error changes energy and responds to the physics of the flow. The form in 3-D conforms to the scale similarity model from LES. If one then adds selective dissipation via upwind (Riemann solvers), the method acts like a smart LES model. This recipe of techniques is present in most ILES examples. It is relatively obvious that it is the core of the success that many turbulence researchers find so annoying.

As I have and will write, the modern methods have serious gaps and issues. I recently wrote about issues around evolving adiabatic flows. The methods have a host of pathologies, mostly known due to their broad and extensive use. High-order and high-resolution are still being sorted out. The ultimate efficiency and effectiveness of the methods are still being worked on. The field requires new directions and breakthroughs. Still, these methods have an amazing track record of success, and they are key bits of modern computational technology.

“The essence of science is that it is always willing to abandon a given idea for a better one; the essence of theology is that it holds its truths to be eternal and immutable.” ― H.L. Mencken

References

VonNeumann, John, and Robert D. Richtmyer. “A method for the numerical calculation of hydrodynamic shocks.” Journal of applied physics 21, no. 3 (1950): 232-237.

Margolin, Len G., and K. L. Van Buren. “Richtmyer on Shocks:“Proposed Numerical Method for Calculation of Shocks,” an Annotation of LA-671.” Fusion Science and Technology 80, no. sup1 (2024): S168-S185.

Mattsson, Ann E., and William J. Rider. “Artificial viscosity: back to the basics.” International Journal for Numerical Methods in Fluids 77, no. 7 (2015): 400-417.

Morgan, Nathaniel R., and Billy J. Archer. “On the origins of Lagrangian hydrodynamic methods.” Nuclear Technology 207, no. sup1 (2021): S147-S175.

Lax, Peter D. “Hyperbolic systems of conservation laws II.” Communications on pure and applied mathematics 10, no. 4 (1957): 537-566.

Harlow, Francis H. “Fluid dynamics in group T-3 Los Alamos national laboratory:(LA-UR-03-3852).” Journal of Computational Physics 195, no. 2 (2004): 414-433.

Smagorinsky, Joseph. “General circulation experiments with the primitive equations: I. The basic experiment.” Monthly weather review 91, no. 3 (1963): 99-164.

Smagorjnsky, Joseph. “The beginnings of numerical weather prediction and general circulation modeling: early recollections.” In Advances in geophysics, vol. 25, pp. 3-37. Elsevier, 1983.

Grinstein, Fernando F., Len G. Margolin, and William J. Rider, eds. Implicit large eddy simulation. Vol. 10. Cambridge: Cambridge university press, 2007.

Godunov, Sergei K., and Ihor Bohachevsky. “Finite difference method for numerical computation of discontinuous solutions of the equations of fluid dynamics.” Matematičeskij sbornik 47, no. 3 (1959): 271-306.

Margolin, Len G., and William J. Rider. “A rationale for implicit turbulence modelling.” International Journal for Numerical Methods in Fluids 39, no. 9 (2002): 821-841.

Here are some thoughts on more scientific or technical posts and those that are less so, along with a short map of what lies ahead. I’m also going to explain why I give so much attention to the issues of leadership.

Despite my tendency to focus on technical things, my writings are often drawn to the failings of our current leadership at all levels. The basic thought is that none of these scientific issues can be addressed without improvements in how the leadership acts. It is born out of the frustration that I felt growing year upon year in my career. This is that all the good technical work in the world that I could do, that others could do, would amount to nothing unless the leaders showed greater integrity, and focus on technical excellence. I had seen science in general fade from importance and priority. These were replaced by other concerns that continually undermined the technical world. By the end of my professional career, the leadership’s behavior became so fucked up that I could no longer stand to work at what, by all accounts, is a premier institution.

I find that I have many readers who seem to share my observations and also provide their own perspective. The same issues are present where they are. Still a constant need in retirement is for me to tack towards joy and exploration of the technical work. It is where I would so like to focus on. There are the traditional things I’ve worked on in numerical methods, computational physics, and computational science that continue to need effort. Interspersed with this is the new focus on AI that has burst forth onto the scene with the massive success of LLMs.

Again my mind is drawn to the failings of leadership in this time. How toxic and poisoning the current leadership is towards the successful roll out of AI to society. I think it is a very clear worry given what I saw in terms of the shallow technical approach to AI on the part of the scientific community as expressed with federal research. The AI efforts that were announced lacked all nuance and technical depth and were yet another set of stunt efforts that were only geared towards securing more funding. It is the same completely fucked up pattern that I saw the last decade at Sandia.

I find myself drawn to this problem because it seems so fundamental. Without changes in leadership I don’t think we can succeed at AI, nuclear weapons, or science in general as a nation. Here, leadership is focused on everything, but the elements of success in any of these endeavors. With all the value being put into money and the appetite for greed, the decisions will surely be poor technically and harmful to society as a whole.

I do promise that my next two posts will be technical:

1. Stepping back to the ever-controversial and lightning rod of numerical dissipation.

2. Then probably to some aspect of AI as I attempt to use and understand it in a way that is better than the sort of bullshit I heard from my leaders at the laboratory and has been reported to me by friends at other laboratories.

tl;dr

We now live in a World with both nuclear weapons and AI. Watching our country abdicate its responsibilities to nuclear weapons gives me pause. Our national infrastructure is in decay, and our leadership is inept. This is promoted by an awful incentive structure. Lack of nuclear testing means raising our game; we lowered it. The great responsibility of this technology is not met with seriousness. It fills me with fear to think of how irresponsibly we are approaching AI. We also do not realize how much these technologies empower our Nation to act as it wishes. Often, they provide the power to dominate others and get away with murder (literally at times). We seem to be unwitting in how we sell the possession of nukes to everyone else. This is yet another form of irresponsibility in action. Our lack of maturity is a threat to mankind.

Nukes are Still Central; We are Not Taking Care of Ours

“The Manhattan District bore no relation to the industrial or social life of our country; it was a separate state, with its own airplanes and its own factories and its thousands of secrets. It had a peculiar sovereignty, one that could bring about the end, peacefully or violently, of all other sovereignties.” — Richard Rhodes

For nearly 40 years, I worked at nuclear weapons Labs, Los Alamos and then Sandia. My time at the national laboratories taught me many things. I tapped into a vast reservoir of knowledge at Los Alamos. I also embraced the mission of the Lab and accepted the responsibility that came with it. I wish those values were embraced by the Labs today. I fear they are not. Furthermore, the nation seems to have lost its responsibility associated with nuclear weapons. This loss of responsibility is transferring to science, technology, and engineering as a whole. The advent of AI as a key technology merely amplifies and raises the stakes of these developments. My nation is endangered by these developments.

One of them is the incredible responsibility of caring for nuclear weapons. This requires extreme competence in a vast array of science and engineering disciplines. In my time, I have witnessed a decline in virtually every area of competence. Only computing has grown in knowledge, and only in hardware. Computing is far more than hardware. What goes on with that hardware and how it is used matters greatly. The use of these weapons is primarily to maintain the peace and, ultimately, to ensure that the world never sees their use. This is not my area of expertise, but it is a matter of deep moral and ethical concern. Nuclear weapons are holistic because of their power, ultimately being a relentlessly political technology.

A key episode that demonstrates the danger in our current philosophy is plutonium aging. There was a concerted study to look at this, where both Los Alamos and Livermore weighed in. I personally don’t know the answer to any of this and wouldn’t say anything if I did. The most notable aspect that undermines this study is the positions taken by each lab. Los Alamos took the position that the aging was bad. Livermore took the position that the aging was not. Again, I don’t know what the right answer is. The positions that each lab took were completely correlated with what was in the best financial interest of each laboratory. Los Alamos had a distinct benefit in terms of money for there to be a problem. Livermore, conversely, had the opposite view. I can only imagine what sort of pressures were exerted behind the scenes. Maybe there was none, but given my experience, I sincerely doubt it. The financial benefits of the technical work cast doubt on the overall outcome. The reality is that the only way to be completely sure would be to begin testing these weapons again. Instead of that, we should have unbiased and technical work of the highest quality rather than financially conflicted studies.

During my time at Los Alamos, I learned all about the full scope and breadth of nuclear weapons. The science that is needed to support them is breathtaking in scope. At the same time, I saw a country take steps that ultimately are verging on complete abdication of responsibility. I fear their care is diminishing below the standards needed. First and foremost among these was a change in the management philosophy. At the start of my career, it was intelligent care and concern for proper stewardship. Now, there is a flawed belief that money is the only thing that managers should focus on. Now, a belief that the proper care of programs financially leads to the best outcomes. This was an invocation of a business philosophy for managing the work of the government. This philosophy was adopted without thought or proper modification for science. This reflects a general trend across society.

The same period of time as I watched this philosophy usher in the end of American dominance in science. It has declined to be replaced by dominance by China, an adversary. While China has moved forward their dominance is more our failure than its success. We had a lead and squandered it. I watched this happen from the inside. Both Los Alamos and Sandia were premier institutions. Were. They are both shadows of their former glory. We did this to ourselves. We did this without any eye toward the responsibilities for our nukes or the impact on the future. Much of our power and wealth is founded on science and technology. It will not hold up in the future.

It is my belief that nuclear weapons are the most fearsome and horrible weapons developed by man. They should never ever be used in armed conflict. Our irresponsibility threatens that outcome. I also believe they are a technology that cannot be put back in the bottle. The genie is out and must be tamed. For this to be true, moral and ethical leadership is needed. It needs to be provided by the nation. We should have nuclear weapons that all others are absolutely certain will work as designed and intended. This confidence is necessary for proper stewardship. That said, the United States has moved far too long along the path where we can no longer be entirely certain that this is reality. We have allowed our experts and expertise to degrade and become a mere shadow of what they once were.

“The practice of science was not itself a science; it was an art, to be passed from master to apprentice as the art of painting is passed or as the skills and traditions of the law or of medicine are passed.” — Richard Rhodes

Being More Responsible

“The nuclear arms race is like two sworn enemies standing waist deep in gasoline, one with three matches, the other with five.” ― Carl Sagan

With every passing day, the steps to fix this and the consequences of our decline become more dire. I believe that I am also correct to be worried about the moral and ethical standing of those who lead us. The United States does not acknowledge how well they market nuclear weapons to other Nations. Nuclear weapons, to be blunt, allow your nation to be complete assholes and get away with it. Does anyone really believe that Russia would have invaded Ukraine if it did not have nuclear weapons? That Ukraine would have been invaded if it had nuclear weapons? Nuclear weapons undergird the actions of Israel and the USA against Iran, even as they work to deny Iran its own acquisition. Israel and the USA provide evidence to the Iranians that possessing nuclear weapons would be enabling. They would unlock their power in the region and give them a source of invincibility and immunity from consequences. Both Russia and the USA (Israel too) demonstrate this over and over.

Once a nation becomes nuclear-armed, nobody really fucks with them any longer. They join the top of international leadership (see India). The basic technology is old, going back to 1945. Even eighty years on, nuclear weapons have a huge impact on human affairs. Internationally, they are always in the room. Superpowers refuse to acknowledge that they are walking advertisements for possessing nuclear weapons. Lesser states are always given a litany of reasons why possessing nuclear weapons would improve their national standing. Nuclear weapons are also still the biggest physical stick in the world.

We have a President who has alluded to testing again. Is this necessary? Is this wise? This is all worth discussing. At the same time, we have a new technology that’s often compared to nuclear weapons: AI. How will AI and nuclear weapons interact, and what’s the path of wisdom for both AI and a world where both exist? Highly enriched uranium and plutonium are very expensive to obtain. It requires a vast investment by a society to achieve. It is also very hard to hide. It takes time to get there, too. The leading countries have a great deal of desire to keep countries from getting them. It is dangerous, but it also reduces their power to bully “lesser” nations. This is the truth.

Even eighty years on, nuclear weapons have a huge impact on human affairs. Internationally, they are always in the room. Superpowers refuse to acknowledge that they are walking advertisements for possessing nuclear weapons. Lesser states are always given a litany of reasons why possessing nuclear weapons would improve their national standing. Nuclear weapons are also still the biggest physical stick in the world. We have a President who has alluded to testing again. Is this necessary? Is this wise? This is all worth discussing. I do not know the answer to this either; I am deeply conflicted. At the same time, we have a new technology that’s often compared to nuclear weapons: AI. How will AI and nuclear weapons interact, and what’s the path of wisdom for both AI and a world where both exist?

“You can’t be a real country unless you have a beer and an airline – it helps if you have some kind of football team, or some nuclear weapons, but in the very least you need a beer.” ― Frank Zappa

Nukes and AI

“Bohr proposed once that the goal of science is not universal truth. Rather, he argued, the modest but relentless goal of science is “the gradual removal of prejudices.” — Richard Rhodes

The parallels between AI and nuclear weapons are stronger than people feel. In both cases, being an AI superpower is similar in terms of resource allocation to nuclear weapons. The investment in facilities and electricity for creating nuclear material necessary for a weapon is similar to what’s required to lead in AI. In both cases, to succeed as a nation, one needs a vast industrial base and a multitude of scientists and experts who serve that industrial base’s products. It is also similar in terms of its technical depth and sophistication. Additionally, both have good and bad sides. With nuclear weapons, you have nuclear power. With AI, you can use it to benefit society, but it is a powerful tool for warfare and surveillance. We live in a world now where both of these technologies are lurching to the fore of world events and have an outside influence on the future of mankind.

Nuclear power is underutilized and over-feared by the public. It is not trusted. It has inherited the peril of nuclear weapons. It could be a green technology to combat climate change. By the same token, AI has similar light and dark polarities. It can be used to propagandize, kill, and surveil people. By the same token, it can be an incredible assistant to all of us and produce massive productivity gains. It could be a means of great wealth and abundance for society. Right now, it will just bring wealth to a few people and impoverish the masses. In both cases, we are failing to recognize the truly dire harm that these technologies could produce. We are also failing to recognize the truly beneficial good for society that each can do. Our leadership in both is completely failing.

The Bottom Line

“Are you ready for nuclear Armageddon?” ― Michael Parker

Every year, the directors of the three labs sign a letter stating the status of the stockpile. This letter goes to the President with advice on what to do. Every year, they have asserted that the stockpile is in good shape. Testing weapons again is not required. The question that I ask myself is: what would happen if one of the directors declined to state that the stockpile was in good shape? My assertion is that this director would be immediately replaced without explanation. If the director of the lab does not have the liberty to not sign the letter in the affirmative, do they really have the liberty to sign it at all? Ultimately, is the assessment of the stockpile not a technical or scientific question but rather a political one? For example, if the president had decided to test again, would they all sign in the negative? Would they join in? Again, these are questions I think need to be asked, and the answers are not ones that I know. They are questions we should be asking.

“Now, I am become Death, the destroyer of worlds.” ― J. Robert Oppenheimer

tl;dr

Across society, our leaders today are liars. Even the most truthful are consummate bullshitters. Not just the President, but almost all of them. Why? It works! People reward the liars and bullshitters. They choose to follow and effectively believe them. Eventually, reality will punish them, but most get away with it. This all seems to be a product of our increasingly online world. This combined with greed and inequality of wealth drives lying and BS. There is a lack of oracles and arbiters of truth. In the long run, we will all suffer. The debts to truth will come due.

“Management is doing things right; leadership is doing the right things.” ― Peter Drucker

A reasonable conclusion is that we are neither managed, nor led today.

Leaders Today

Today our leaders have a conflicted and ambiguous relation to the truth. At the same time the level of trust in society is plunging to all-time lows. This would seem to be a vicious cycle headed for disaster. As I’ve stated before reality will always assert itself, and when it does the results are undeniable. The twin issues of lack of trust and wishful thinking seems to be combining to supercharge this behavior. We see it every day from our National leadership. I saw it with my management at work. Leaders lie because it benefits them. It is the road to success. As long as we reward the lies and bullshit, we will get more of it.

My own departure from work and retirement was triggered by this dynamic. I had leaders who did not trust the system enough to accept the truth and respond to an objective reality that required a response. Instead they engaged in unethical practices that were effectively a cover-up. It was a case where someone did high quality work with results they didn’t like. Rather than take that information, and respond to the results, they censored and covered it up. I was working in an institution that green-lighted their incompetence as the right response. My own responsible actions were viewed as unacceptable. In terms of National security, the leaders actions were irresponsible and incompetent. Yet, it was also the path of least resistance. They chose the easy, cheap path that leads to willful ignorance. They are the epitome of modern leadership.

I remember the last time I engaged with the Director of Sandia. It was a forum on AI. I asked her a question online about our information environment. As I’ve noted before Sandia has a very restrictive, “do not share information” culture. The impact of this on information technology is profoundly negative. As a consequence functions like search are crippled. Given this track record, and AI’s dependence on training data, how would we avoid this mistake from crippling AI? Her response was “that was a harsh question.” There was no willingness to take evidence and respond to it. Certainly, no confidence is any action to recognize the problem, much less remediate it. The evidence was rejected as harsh. With leadership like this is it any wonder why my managers would be any such pathetic cowards? Seemingly not, her example set the bar.

We will get this from our leaders as long as we accept it. We will get it as long as they suffer no ill from its effects. Avoiding the damage from the resistance to objective reality is an illusion. It will be obvious and catastrophic. The damage is already done; it is just not evident enough to prompt a strong enough response.

“Do you want to know who you are? Don’t ask. Act! Action will delineate and define you.” ― Thomas Jefferson

Motivations are all Wrong

“The mark of a great man is one who knows when to set aside the important things in order to accomplish the vital ones.” ― Brandon Sanderson

A core problem is that our leadership has no allegiance to the truth. What they have allegiance to is money, profit, shareholder value, … At least if our time scale is short and all the leadership is short term focused. In this case, the truth is the enemy of all these things and our leaders are basically really good liars. It is worse that most are bullshitters. They don’t care about the truth, and chose whatever suits them best. The lying and bullshit serves to increase the value of what they care about and the truth isn’t it. We see it everywhere.

Corporate interests are a the canonical example. This has become the model and framing for society as a whole. The core of the attitude is the maxim of maximizing shareholder value as the sole purpose of corporations. This attitude has been adopted by politics and other organizations. My personal experience is thick with organizations like National Labs and universities. There, this principle of leadership is simply ill-suited to their purpose and actively damaging. For corporations this principle can be argued to be appropriate. That said, it produces a focus that is relentlessly short term. As those effects become evident the shareholders simply divest and move on to their next victim. While profitable and driving the stock market, it hollows the future out. Often this profit is done in ways that damage our society. The classic example is dumping toxic waste without any conscious. Today, no example is more apt today than social media. These companies are worth a huge amount of money all based on preying on the rest of society.

The force of this philosophy has created vast swaths of wealth. It has also created income and wealth inequality on a scale unequaled in United States history. Today’s billionaires are worse than the robber barons of the 19th Century. Furthermore, it is being adopted across the leadership spectrum. The government has decided that it is the model for things they fund. Politicians too. The Laboratories managing science and national security are examples. I saw this close up. The result is a primal focus on money above all else. The money becomes a stand in for quality of work and technical excellence. More insidiously, the behavior of the management is distorted. We see the same lying and bullshitting as corporate leaders. All of it links back to the chosen priorities.

I’ve point to Boeing corporation as a cautionary example. Reality has visited their business and showed its failures. Planes crash and doors fall off with evidence pointing back to corporate decisions. The corporation worked to maximize short-term value at the cost of quality. Technical excellence is costly and they curtailed that. We can see the same thing setting up with AI. Sam Altman of OpenAI is bullshitting his way through the investment bubble. He is trying to get his company to its IPO with as much value as possible. This value is being powered by bullshit and sleazy behavior. We can see how Boeing fucked itself. Will OpenAI fuck itself too? or will they get to their massive payday. Ultimately, all this behavior is in service of creating billionares. They are created on the backs of the rest of us. They also don’t give a single fuck about the country, or their citizens.

God help us, this is the model of leadership across the whole of society.

“The greatest leader is not necessarily the one who does the greatest things. He is the one that gets the people to do the greatest things.” ― Ronald Reagan

It is Effective

The obvious issue is that current models of leadership are viewed as effective. It is successful. Donald Trump is an exemplar of it. He’s been elected President twice. His constant lying and bullshit seems to benefit him. There is no seeming penalty for it. In all likelyhood the impacts of his behavior will come due when he is out of office (or dead). The same goes for other leader whether it is the CEO of Boeing or the Director of a Lab. Someone else will have to clean up their mess. The current leader will get rich and enjoy power. The future is something they have no responsibility for. This should not be our model for leadership.

The core of the issue is time scale. The leadership is focused on tomorrow (or the next quarter). We see this in the quarterly review so popular in corporate governance and adopted everywhere. The lens for it is money. This drives stock price and corporations work to engineer the quarterly review to drive stock value. In this system, the future is lost. The long term health of any of these systems has no vote. This was evident at the Labs where I worked. The long term prospects of the Labs declined, and declined with the short term focus. At the same time every program was declared a great success. In almost every case this success was bullshit.

Just as the long term is sacrificed, the impact of society has no vote. This has clarity in the behavior of social media where vast profits have been made by preying on people. We might guess that AI will do more of the same. Society would benefit from an honest AI that operated with humility. Profit demands that AI acts confident in all answers, and shows mastery where there is none. We see the lines of conflict set up where lying, hallucinations and bullshit line the pockets of tech billionaires. Society would be better off with an honest AI that shows humility. It would respond with genuine doubt and warn the users of sketchy answers. This would be far more responsible, but negatively impact the (short term) bottom line. In this, we can see how the incentives are arrayed against responsible long term health.

“Efficiency is doing the thing right. Effectiveness is doing the right thing.” ― Peter F. Drucker

It Won’t Change Until It Blows Up

“Being responsible sometimes means pissing people off.” ― Colin Powell

The core of the problem is that this way of doing things works. It creates wealth. It is the standard set by society for organizations. All things are measured in money. All of the measurement is short term. Any other measure shrinks into being meaningless. If we measured the long term health, we would see the problem. We don’t. All sorts of important things are ignored. Excellence and quality are disregarded, unless it fits into the finances. They rarely do. Both are expensive, and when the opposite works in the short term, they are jettisoned. Generally excellence and quality matter in the long term (see Boeing). Their disregard takes years to become evident. I witnessed a similar decline at the National Labs.

“Advertising is legitimised lying.” ― H.G. Wells

Today’s leaders are not communicating reality to us. Almost everything they say is merely marketing of what they wish were true. It is advertisement of their success, “cherry picked” to only mention success. Problems and failures are simply ignored or spun into a success. Too often the leaders offer zero humility. Their messages show little vulnerability. I do think the internet and social media can be blamed for a great deal of this. They act as if any weakness or failure will be used against them in an instant. This is part of the absence of trust. The viscous cycle is driven as the trust-destroying nature of their actions only makes things worse. It feels like we cannot escape this dynamic. Meanwhile AI is appearing as a lying trust-annihilating technology to amplify this trend.

While the problems are evident, nothing is changing. We are societally careening toward multiple crises. When problems are ignored, they fester. The problems grow larger as they rarely moderate or disappear without focus. I would call this approach optimistic pessemism. There optimism is expressed with pessimism about our ability to make things better. I personally prefer pessimistic optimism. There the problems are discussed and identified with optimism about our ability to solve them. I know one thing, we won’t solve anything without identifying the problems. This is a necessary first step and the origin of success.

Social media has taken all of this to the overdrive. Not only is social media powered by the maximizing shareholder value motive for leadership, but it’s created a world where leaders feel the need to define their reality before the reality is defined for them. The leader works to define the reality that suits them. They worry that any problem will impact their short term prospects. It will lessen their wealth or impact the funding negatively. This is just spiraled. In addition, the voices of insiders who know better are typically silenced by fear. See me as an example of this. In today’s world, we have less and less voice instead of more and more. Social media is there simply to sell us things.

“Good leadership requires you to surround yourself with people of diverse perspectives who can disagree with you without fear of retaliation.” ― Doris Kearns Goodwin

Postscript

I realize that my more technically oriented posts do a lot better in terms of readership. I could simply focus on that. On the other hand, the issues that I discuss in these more managerial to political posts are the barriers that I saw while working to actually execute the technical work successfully. These leadership issues discussed here, for example, are precisely the things that make the technical work completely pointless. Without leadership that recognizes our problems and works to actively solve them, all the good technical work in the world will amount to nothing. We have a number of rather profound issues and problems to solve today. The nuclear stockpile remains something of acute interest. With the advent of AI bursting onto the scene in the last few years, there are incredibly difficult problems at the boundary between political, managerial, and technical that must be navigated.