Those who deny freedom to others, deserve it not for themselves

― Abraham Lincoln

I’d like to be independent empowered and passionate about work, and I definitely used to be. Instead I find that I’m generally disempowered compliant and despondent these days. The actions that manage us have this effect; sending the clear message that we are not in control; we are to be controlled, and our destiny is determined by our subservience. With the National environment headed in this direction, institutions like our National Labs cannot serve their important purpose. The situation is getting steadily worse, but as I’ve seen there is always somewhere worse. By the standards of most people I still have a good job with lots of perks and benefits. Most might tell me that I’ve got it good, and I do, but I’ve never been satisfied with such mediocrity. The standard of “it could be worse” is simply an appalling way to live. The truth is that I’m in a velvet cage. This is said with the stark realization that the same forces are dragging all of us down. Just because I’m relatively fortunate doesn’t mean that the situation is tolerable. The quip that things could be worse is simply a way of accepting the intolerable.

What is going on, and how did we get here?

When you read management theory, and I do, you would think that good management would do the opposite. I certainly like the feeling of being empowered and valued, it makes me feel like coming to work and doing my best. It is good to feel a real sense of purpose and value in work. I have had this experience and it is incredible. When I am creative, my voice is heard and my actions lead to positive outcomes, work is a real joy. I have definitely experienced this, but not recently. If working well, a management system would strive to engage people in this manner. The current management approach acts are pretty much completely opposite to this end. The entire system seems to be geared to putting us into a confined and controlled role. Our actions are limited because of fear, and the risk that something “bad” might happen. We are simply members of a collective and our individuality is more of a threat than a resource.

Today as always, men fall into two groups: slaves and free men. Whoever does not have two-thirds of his day for himself, is a slave, whatever he may be: a statesman, a businessman, an official, or a scholar.

― Friedrich Nietzsche

Why are we managed in such an inherently destructive short-sighted and inhumane manner?

Star Trek introduced us to the Borg, a race of semi-robotic aliens who simply absorb beings (people) into a hive where their basic humanity and individuality is lost. Everything is controlled and managed for the good of the collective. Science Fiction is an allegory for society, and the forces of depersonalized control embodied by the Borg have only intensified in our world. Even people working in my chosen profession are under the thrall of a mindless collective. Most of the time it is my maturity and experience as an adult that is called upon. My expertise and knowledge should be my most valuable commodity as a professional, yet they go unused and languishing. They come to play in an almost haphazard catch-what-catch-can manner. Most of the time it happens when I engage with someone external. It is never planned or systematic. My management is much more concerned about me being up on my compliance training than productively employing my talents. The end result is the loss of identity and sense of purpose, so that now I am simply the ninth member of the bottom unit of the collective, 9 of 13.

Disobedience is the true foundation of liberty. The obedient must be slaves.

― Henry David Thoreau

Increasingly, the forces that have demoralized the blue collar working class world and propelled White Nationalism to the forefront of American politics have worked their way to me. The forces doing this are relentless and bipartisan both the right and left are doing this, but in different ways. Conservatives prize control and order with a horrid authoritarian streak naturally leading to Trump. Fear is a political tool wielded like a scalpel, enslaving the population to the security state. Generally speaking, the rise of the management class at work comes from this side of the spectrum along with their devaluation of the rank and file people. We see a tendency toward command-driven management, and being told what to do. Workers are simply meaningless details interchangeable and disposable. The management class is the heart of importance, and value. The rest of us aren’t really worth much effort simply being necessary cogs to get the work done.

The left has their own crimes to answer for. Much of the right-ward movement is a reaction to the systematic over-reach of the bureaucratic state. Political correctness and the thought police also serve to undermine societal confidence and tolerance in the “elite”. Management is part of this elite so derided to today and each subgroup within the elite has their own axe to grind. The big crime of the left is that they seem to think that every ill and danger can be regulated out of existence. Little or no thought is put into the cost of the regulation or the opportunity lost in the process. This is similar to the behavior of the right with respect to the National Security state. In the process, the individual is lost; the individual is not valued; the individual is not trusted. The value of work and the dignity of labors toward support of the family and the good of society is not honored. Work becomes a complete waste of time. Productivity and meaning in work ceases to be prioritized. Life is too precocious to waste doing this.

A big part of the overall problem is the value of my time. For every single thing I do, I trade it against doing something else. Increasingly, my time is spend doing unproductive and useless things. Every useless thing I have to do displaces something else. Time is a valuable resource, and today my management, my institutions treat my time with flagrant disregard and outright disrespect. This is the rotten core of the problem, the disregard for the cost of making me do stupid useless things. We engage it pointless, wasteful box checking exercises rather than reject pointless activities. It is not the stupid things as much as the valuable things they displace. Almost all the time at work I could spend doing something more valuable, or more gratifying, or more satisfying, or simply something that brings me happiness and joy. I could create, solve problems, learn and find meaning and value. Instead I am enslaved to someone’s idea of what I should do. I am saddled with numerous “terms of employment” based tasks that have no value or meaning. Those saddling me always have the excuse of “it is a good idea to do this”. This sentiment is valid except it completely and utterly discounts what that time could be spent doing that is better.

The difference between technology and slavery is that slaves are fully aware that they are not free

― Nassim Nicholas Taleb

I spend complete days doing nothing, but bullshit. It is mostly what other people think is a good idea, or worse yet some sort of ass covering exercise. I can spend an entire day doing nothing productive at all, and yet I’m doing exactly what I supposed to do. This is a huge problem! Managers do this almost every day. They rarely do what they need to do, actually manage the work going on and the people doing the work. They are managing our compliance and control, not the work; the work we do is mere afterthought that increasingly does not need me any competent person would do. At one time work felt good and important with a deep sense of personal value and accomplishment. Slowly and surely this sense is being under-mined. We have gone on a long slow march away from being empowered and valued as contributing individuals. Today we are simply ever-replicable cogs in a machine that cannot tolerate a hint of individuality or personality.

All over the place, from the popular culture to the propaganda system, there is constant pressure to make people feel that they are helpless, that the only role they can have is to ratify decisions and to consume.

― Noam Chomsky

Work place education exemplifies all of these trends. My training is almost 100% compliance oriented. Nothing I am ever trained on is job related, it is all telling me what I shouldn’t do. This training is a good avatar for priorities, and my actual work is not a priority at all. All the training that develops a person is management related. For the rank and file personal development is completely optional and hardly prioritized. We are there to get our stuff done, and the stuff we do is increasingly shit. They have lots and lots of training, and from what I see use almost none of it. It is full of the best theory that cannot be applied to the workplace. Their training would tell them to harness my passion and empower me, yet none of that ever happens. The entire system is completely oriented toward the opposite. The training system signals very clear values to all of us, the rank and file need to comply and submit, managers are the only employees’ worth developing even if the development is all delusional.

The smart way to keep people passive and obedient is to strictly limit the spectrum of acceptable opinion, but allow very lively debate within that spectrum…

― Noam Chomsky

The management literature is full of the gospel of the value of human talent. It sounds great, and I believe in it. Management should be the art of enabling and working to get the most out of employees. If the system was working properly this would happen. For some reason society has removed its trust for people. Our systems are driven and motivated by fear. The systems are strongly motivated to make sure that people don’t fuck up. A large part of the overhead and lack of empowerment is designed to keep people from making mistakes. A big part of the issue is the punishment meted out for any fuck ups. Our institutions are mercilessly punished for any mistakes. Honest mistakes and failures are met with negative outcomes and a lack of tolerance. The result is a system that tries to defend itself through caution, training and control of people. Our innate potential is insufficient justification for risking the reaction a fuck up might generate. The result is an increasingly meek and subdued workforce unwilling to take risks because failure is such a grim prospect.

People get used to anything. The less you think about your oppression, the more your tolerance for it grows. After a while, people just think oppression is the normal state of things. But to become free, you have to be acutely aware of being a slave.

― Assata Shakur

One of the key things that drives the system is a complete lack of cost-benefit analysis

. The cost of a given measure to control a risk is rarely accounted for. The TSA is a prime example. One asshole tries to blow up a shoe, and forever we can’t take toothpaste on a plane. It is patently absurd on the face of it. We give up freedom, we give up time and we expend enormous effort to control minuscule risks. In the process, we have made a wonder of technology and the modern world, something to be hated. So much of the wonder of the modern world is being sacrificed to fear designed to control risks that are so small to be ridiculous. In the process, the vast benefits of modernity are lost. The vast benefits of easy and convenient air travel are overrun by a system designed to control irrational fears. Our fears are things that are completely out of control, and the vast opportunity cost is never considered. The result is a system that destroys our time and productivity in a disproportionate manner.

If one is forever cautious, can one remain a human being?

― Aleksandr Solzhenitsyn

The same thing is happening to our work. Fear and risk is dominating our decision-making. Human potential, talent, productivity, and lives of value are sacrificed at the altar of fear. Caution has replaced boldness. Compliance has replaced value. Control has replaced empowerment. In the process work has lost meaning and the ability for an individual to make a difference has disappeared. Resistance is futile, you will be assimilated.

To be given dominion over another is a hard thing; to wrest dominion over another is a wrong thing; to give dominion of yourself to another is a wicked thing.

― Toni Morrison

 

The law that entropy always increases holds, I think, the supreme position among the laws of Nature. If someone points out to you that your pet theory of the universe is in disagreement with Maxwell’s equations — then so much the worse for Maxwell’s equations. If it is found to be contradicted by observation — well, these experimentalists do bungle things sometimes. But if your theory is found to be against the second law of thermodynamics I can give you no hope; there is nothing for it but to collapse in deepest humiliation.

— Sir Arthur Stanley Eddington

AS USUAL WORD PRESS’ LaTeX is annoying.  I need to post and go to bed.

Rather than continue to talk about global issues I’ll get back in the weeds this week and get into a technical conversation. I don’t really know where this is going, so this is a bit of stream of consciousness in thinking about a topic and developing a new idea. The inspiration for this came from my talk at the Multimat 2017 meeting, and considering how to fix problems I’ve seen with rarefactions. As a reminder, I had seen that some solvers produce solutions with small, but consistent violations of the second law of thermodynamics in their solution of expansions (e.g. rarefactions). Nothing catastrophic is observed, but it is a troubling failure from nominally robust solvers. This study was itself motivated by the observation of a systematic failure of these solvers to produce convergent solutions to very strong rarefactions, and examine what sort of character the solutions have under more ideal circumstances.

A few points are worth making about the solvers used and how they have been tested in the past. Mostly I’ve worked with finite volume codes, sort of the gold standard of production codes for fluid dynamics. These codes are very reliable, and well understood.  For the most part, the focus of test problems has been shock waves where bad methods can result in catastrophic instability for the codes. Rarefactions are far less studied and tested because they are generally benign, and don’t threaten the stability of the code. As a result, the rarefaction focused test problems are mostly missing. We do know that expansions can produce unphysical solutions for Eulerian codes at critical points (where the characteristic speeds go to zero, and numerical dissipation may vanish). Bad solutions can arise with strong rarefactions, but no one has pointed out that these solutions actually violate the second law of thermodynamics before. The end result is a relative ignorance about shortcomings of the code, and a potentially important outlet for improvement of the methods.

Von Neumann told Shannon to call his measure entropy, since “no one knows what entropy is, so in a debate you will always have the advantage.

― Jeremy Campbell

One of my suggestions about examining this problem is examining the solution to these problems with a wider variety of codes. This would include codes that do not use pure finite volume methods.  One example are methods based on flux differencing where the code can go to formally high-order accuracy for nonlinear problems. Control volume codes are limited to second-order accuracy and the leading nonlinear truncation error can produce the entropy-condition violating energy transfer in expansions, . For almost every control volume code these terms are dissipative in shock waves, thus providing additional stability to the codes in this dangerous configuration. The opposing reaction in expansions can go unnoticed because any imperfections in the solution are modulated by the physics of the problem. For this reason, the failing has gone completely unnoticed for decades.  A reasonable question to explore is whether codes based on different design principles exhibit the same problems, or produce solutions that satisfy the second law of thermodynamics more uniformly.

An important technique in defining flux difference schemes of high-order accuracy is flux splitting (more than second-order accuracy). The core idea is that approximating the fluxes to high order can produce higher formal accuracy then the variables. The question is does this produce solutions of a fundamentally different character with respect to entropy. Simply put, a flux splitting is a decomposition of the fluxes being differenced into negative and positive moving contributions. These fluxes are then differenced and then recomposed into the total flux. The splitting techniques add a directionality to the approximation needed for numerical stability associated with upwinding the approximation. The flux splitting techniques are closely related to Riemann solvers, but here to fore only include a small number of simple linearized Riemann solutions. I’d like to explore some greater generalization of this concept including flux splittings based on exact Riemann solvers.

The Riemann problem is the exact solution to the interaction of two discontinuous states described by hyperbolic equations. This analytic information can be used to develop numerical methods that encode this physically relevant information into the solution. In terms of numerical methods, the Riemann solution is a generalization of the principle of upwinding, where the physical direction of propagation is taken into account. The first person to describe this approach to numerical methods was SK Godunov in 1959. Godunov’s method was first-order accurate and used the exact solution to the Riemann problem. It was soon realized that one only needed to approximate the Riemann solution. This became a key development in the methods over time and allowed great progress. Over time it was realized that it also allowed great flexibility too.

In science if you know what you are doing you should not be doing it. In engineering if you do not know what you are doing you should not be doing it. Of course, you seldom, if ever, see the pure state.

– Richard Hamming

A simple Riemann solver can be defined by linearizing the problem, $ ( u_r – u_l ) $. The quantity is the nonlinear flux, are the states to the left and right of the interface. The dissipation is defined by the eigen-decomposition of the flux Jacobian, . This decomposition is contained of the right and left eigenvectors and the eigenvalues, . These eigenvalues are the characteristic velocities, which for gas dynamics are being the velocities and the sound speeds, . This basic decomposition is the basis of flux splitting techniques.

The basic flux splitting takes the flux and decomposes it into right and left moving pieces, . One was to do this is choose a velocity, , and create contributions where and . A simple choice of creates the Lax-Friedrichs flux, the simplest (and most dissipative) Riemann solver. For the general linearized Riemann solver the flux splitting is and . The choice of the left and right states to evaluate the flux Jacobian defines the flux splitting. For example, if the states are evaluated using Roe’s recipe, we get the Roe flux splitting. If we evaluate the eigenvalues in a bounding fashion we can get the local Lax-Friedrichs method.

Another approach to generating a flux splitting does not use the variables in the expression of splitting, and only uses the fluxes. In this case the expressions are developed in terms of the sign of the eigenvalues/characteristic velocity. The splitting then works only as a scaling by eigenvector decomposition of the flux Jacobian. The expressions are somewhat simplified, as and $ f^- = \frac{1}{2} ( f – R \mbox{sign(\lambda) L ) f$. We not in passing that the smooth or soft version of the sign function might be extremely useful in this type of splitting and introducing a continuously differentiable function (https://williamjrider.wordpress.com/2017/03/24/smoothed-operators/ https://williamjrider.wordpress.com/2017/03/24/smoothed-operators/). By the same token, the absolute value used in the usual flux splitting approach could also be smoothed to similar effect. We need to take care in our choices to assure that the accuracy of the resulting numerical method is not negatively impacted. We get into some very big problems when we want to generalize to other Riemann solvers. Examples of these solvers are the HLL family of solvers, and the most classical Riemann solver, the exact solver or close approximations to that approach (e.g., a single iteration of the nonlinear Newton’s method used in the exact solver). How can these important methods be utilized in flux splitting methods? For very strong wave interactions these classes of methods are extremely valuable and not presently possible to be used effectively in flux splitting.

 Nature not only suggests to us problems, she suggests their solution.

—Henri Poincare´

We can start with the simpler case of the HLL type of flux, which has an algebraic description. The HLL flux is defined using the space-time diagram by integrating the equations to derive a flux. The simplest form of the flux uses bounds for the wave speeds and neglecting all of the structure inside the Riemann fan resulting in a simple closed form expression for the flux, $f_{lr} = \left[a_r f_l – a_l f_r + a_l a_r \left( u_r – u_l \right)\right]/(a_r – a_l)$. The flux is quite simple, but dependent on the estimates for the smallest and largest wave speeds in the system. The left wave speed, is the smallest wave speed and needs to be bounded at zero (i.e., it is negative). The right most wave speed is and is bounded below by zero. The HLL flux has the benefit of reducing to simple upwind flux for the system if all the wave speeds are either negative or positive. For a flux splitting we need to take this apart into negative and positive moving pieces for the purposes of splitting nearby fluxes as we did with the Roe, or flavors of Lax-Friedrichs.

The flux splitting can be defined almost by inspection. The positive flux is $ f^+ = (a_r f – a_l a_r u) / (a_r – a_l) $. The negative flux is $ f^- = (- a_l f + a_l a_r u) / (a_r – a_l) $. This is a wonderfully simple result, and meets all the basic requirements for a flux splitting. Unfortunately, the HLL flux is extremely dissipative, thus lacking some degree of practical utility. Still we expect this flux splitting to be quite robust especially for strong waves with the proviso that the wave speed estimates bound the physical wave speeds. This is a much more delicate estimate than usually recognized. The case of a reflected wave can produce wave speeds nonlinearly that exceed the wave speeds in the initial data.

The harder case is the class of exact Riemann solvers that are defined algorithmically and do not have a closed form. After using an exact Riemann solver we do have a set of initial left and right states, and the resolved state at the centering point . If we desire a flux splitting, it needs to be defined in terms of these variables. The trick in this endeavor is choosing an algebraic structure to help produce a workable flux splitting technique. We build upon the experience of the HLL flux partially because we can incorporate the knowledge arising from the exact solution into the algebraic structure to good effect. In particular, the nature of the one-sided differencing can be reproduced effectively. This requires the wave speed bounds to use the interior states of the solution.

The exact flux is different than the HLL flux, and this will be defined by changing the dissipation vector in the flux. Our chosen structure is a flux defined by $ f_{lr} = \(a_r f_l – a_l f_r – D  \left( u_r – u_l \right)) / (a_r – a_l) $. If we can derive the form for our work will be done. The positive flux is $ f^+ = (a_r f + D u) / (a_r – a_l})$. The negative flux is $ f^- = (- a_l f – D u) / (a_r – a_l) $. Now we just have a little bit of algebra to arrive at our final expression. The math is nice and straightforward, $ D = (a_r f_l – a_l f_r – (a_r – a_l) f_{lr} ) / (u_r – u_l) $. A couple comments are needed at this point. When the states become equal, the solver becomes ill defined, . Fortunately, this is exactly where the linearized flux splitting approaches or HLL would be ideal.

The secret to being wrong isn’t to avoid being wrong! The secret is being willing to be wrong. The secret is realizing that wrong isn’t fatal.

― Seth Godin

Godunov, S. K. “A finite difference method for the computation of discontinuous solutions of the equations of fluid dynamics.” Sbornik: Mathematics 47, no. 8-9 (1959): 357-393.

Van Leer, Bram. “Flux-vector splitting for the Euler equations.” In Eighth international conference on numerical methods in fluid dynamics, pp. 507-512. Springer Berlin/Heidelberg, 1982.

Harten, Amiram, Peter D. Lax, and Bram Van Leer. “On upstream differencing and Godunov-type schemes for hyperbolic conservation laws.” In Upwind and High-Resolution Schemes, pp. 53-79. Springer Berlin Heidelberg, 1997

Shu, Chi-Wang, and Stanley Osher. “Efficient implementation of essentially non-oscillatory shock-capturing schemes, II.” Journal of Computational Physics 83, no. 1 (1989): 32-78..

Jiang, Guang-Shan, and Chi-Wang Shu. “Efficient implementation of weighted ENO schemes.” Journal of computational physics126, no. 1 (1996): 202-228.

Quirk, James J. “A contribution to the great Riemann solver debate.” International Journal for Numerical Methods in Fluids 18, no. 6 (1994): 555-574.

Science is what we have learned about how to keep from fooling ourselves.

― Richard Feynman

Last week was another trip to the Multimat conference, a biannual meeting of scientists who solve the equations of multiple material flows under highly energetic and compressible conditions. I’ve always greeted the meeting with great enthusiasm and returned to work bristling with new ideas and inspiration. In many ways this community is the tip of the intellectual spear for modeling and simulation capability.  It also marks an anniversary of sorts, four years of blogging.  My very first post here was about the San Francisco edition of the meeting that coincided with my 50^th birthday (https://williamjrider.wordpress.com/2013/09/13/thoughts-about-multimat2013/). Two years ago we had a wonderful meeting in Wurzburg Germany (https://williamjrider.wordpress.com/2015/09/11/multimat2015-a-biannual-festival-on-computing-compressible-multiple-materials/). Every meeting was wonderful and this was no exception, except in one very important and perhaps essential regard; the meeting seemed devoid of the usual exciting intellectual inspiration. What happened to the big ideas that flowed so easily in every previous meeting? Is it my imagination, or have the exciting new ideas dried up?

Do stuff. be clenched, curious. Not waiting for inspiration’s shove or society’s kiss on your forehead. Pay attention. It’s all about paying attention. attention is vitality. It connects you with others. It makes you eager. stay eager.

― Susan Sontag

This assessment might seem rather harsh, but upon reflecting on the previous meetings, it holds up under considerable scrutiny. Each previous meeting was full of moments where you are watching someone else’s talk and thinking, “I wish I’d thought of that, this is brilliant”. This is exactly what makes conferences so wonderful and important to attend; you get to cherry pick people’s best ideas accumulated at great effort all at once. In the moment these ideas seem like Athena springing fully formed from Zeus’ brow! Your colleagues get to look like the geniuses they are and present their most creative and ingenious thoughts in an intellectual banquet (https://williamjrider.wordpress.com/2014/06/13/why-do-scientists-need-to-attend-conferences/, https://williamjrider.wordpress.com/2014/10/27/a-holistic-view-of-attending-conferences/). The reason for attending conferences isn’t to give talks; it is to learn new things taught by the smartest people you know. It is to meet and let ideas breed openly over laughter, food and drinks. You give talks as an act of repayment for the knowledge you are granted by being in the audience. Giving talks is pretty low on the list of reasons, but not in the mind of our overlords, which starts to get at the problems I’ll discuss below. Given the track record of this meeting my expectations were sky-high, and the lack of inspiring ideas left me slightly despondent.

A few more thoughts about the meeting are worth pointing out before getting to the dialog about fresh ideas, their importance and postulates for their recent absence. The meeting is attended by a collection of computational scientists (mathematics, physics, engineering,…) dominated by the nuclear “club”. This means American, French and British with a smattering of Russians and Chinese – who couldn’t come this year for undisclosed reasons. These scientists for the most part work at their nation’s respective nuclear weapons’ labs. Occasional others attend like Israelis (an unacknowledged member of the club) along with a handful of Czechs, Italians, and Germans. As such the meeting serves as a proverbial checkup on the intellectual health of this important area of science at the West’s nuclear weapons Labs. This year’s checkup should give everyone pause, the state of health is declining. There is a real lack of creative energy surrounding the heart of our most important codes. Many important codes are built around a powerful hydro-solver that produces accurate, physically relevant solutions to the multi-material “hydrodynamic” equations. Previous meetings have seen a healthy resurgence of new ideas, but that upswing seems to have come to a staggering halt. These labs have also provided a deep well of inspired research that has benefited the broader scientific community including weather, climate, astrophysics and a broad swath of engineering use of computation.

In my opinion the reasons for this halt in creative energy are simple and straightforward. The foolhardy worldwide push for exascale computers is sucking the air out of the room. It is gobbling up all the resources and attention leaving nothing for new ideas. This completely obsessive and unwise focus on the hardware is attempting to continue – the already dead – Moore’s law. This push is draining the community of vitality, resources and focus. The reasons for the push are worth considering because they help define the increasingly hostile nature of the modern world toward science. The computers being build for the future are abysmal to use and the efforts to move our codes to them are sucking all the energy from the Labs. Nothing is left of creative work; nothing is left for new ideas. Simply put, the continued use of old ideas is hard enough if you add these generally unusable computers to the mix. The reason is simple; the new computers completely suck. They are true monstrosities (in the classic definition of the word) and complete pieces of shit as scientific hardware. They are exactly the computers we don’t want to use. The price of forcing them down our throats is the destruction of research that isn’t associated with simply making these awful computers work. Worse yet, the return on the massive investment of effort will be vanishingly small in terms of added modeling and simulation capability.

As noted this whole direction is a foolish attempt to breathe life into the already rigid corpse of Moore’s law. Now dead at every scale of computing and already a decade deceased at the level of computer chips – note the death of Moore’s law and the ascendency of cell phones is strongly correlated, and that probably is not a coincidence. The truth of our real performance on computers is far more dire and damning of this entire effort. We have been getting an ever-lower proportion of the potential performance on our computers for 25 years. Each computer has a peak performance measured on silly hardware friendly benchmarks that no one gives a flying fuck about (the dense linear algebra LU decomposition, Linpac). This silly and useless benchmark is how we crown the fastest computer! Our actual code performance on these machines is truly atrocious and gets worse every year. The dirty little secret is that its been getting ever worse every year. It was god-awful 20 years ago, and it has just gotten worse. Zero is a pretty good approximation to the proportion of the performance we get – generally much less than one percent. We mindfully ignore the situation just like one would ignore a cancer threatening to devour our lives. The attitude is generally, “look away, nothing to see here”. The exascale program is that cancer metastasized.

Part of the discussion about exascale needs to acknowledge the nature of choices and priorities in research. In isolation, the exascale program is an unambiguous good; it would be genuinely awesome to have – usable – exascale computers (https://williamjrider.wordpress.com/2014/09/19/what-would-we-actually-do-with-an-exascale-computer/). This good needs to be weighed in terms of its cost and the impact of alternatives. It needs to be viewed through the lens of reality too. If one looks at the raw cost, the opportunity cost and collateral damage, and under this examination we can see that the exascale program is a massively negative force in science (https://williamjrider.wordpress.com/2016/06/27/we-have-already-lost-to-the-chinese-in-supercomputing-good-thing-it-doesnt-matter/, https://williamjrider.wordpress.com/2016/05/04/hpc-is-just-a-tool-modeling-simulation-is-what-is-important/, https://williamjrider.wordpress.com/2016/10/19/why-china-is-kicking-our-ass-in-hpc/, ). In isolation without considering anything else, it is a clear positive. In the context of lost opportunities and effective use of available resources, the program is an unmitigated disaster. We will all be poorer for it as it lays waste to potential breakthroughs we will be denied in its wake. In today’s world we talk about things in isolation, free of nuance and trade spaces that would make for a more robust and responsible conversation. Our leaders are irresponsible in the extreme for taking down this path with no real discussion, or any debate taking place. The message in the trenches is “do what you’re paid to do and quit asking questions”.

The really dirty secret is that chasing exascale as a route to scientific discovery is simply bullshit of the highest and most expensive order. We would be far better served by simply figuring out how to use the hardware we already have. Figuring out how to efficiently use hardware we have had for decades would be a difficult and worthy endeavor. The punch line is that we could get orders of magnitude in improved performance out of the hardware we’ve been using for decades. By simply figuring out how to get our codes working more efficiently on the computers already existing would meet most scientific goals without eviscerating the rest of computational science in the process. Instead we chase goals that are utterly meaningless. In the process we are destroying the research that has true and lasting value. The areas being ignored in the push for exascale have the capacity to provide far more scientific capability than even the most successful exascale program could possibly deliver. This brings me back to the meeting in Santa Fe and the lack of energy and exciting ideas. In the past the meeting has been a great survey of the active work from a creative and immensely talented group of people. As such this meeting is the proverbial canary in the coalmine. The ideas are dying right in front of our eyes.

This outcome is conflated with the general lack of intellectual vigor in any public discourse. The same lack of intellectual vigor has put this foolish exascale program in place. Ideas are viewed as counter-productive today in virtually every public square. Alarmingly, science is now suffering from the same ill. Experts and the intellectual elite are viewed unfavorably and their views held in suspicion. Their work is not supported, nor is projects and programs dependent on deep thinking, ideas or intellectual labor. The fingerprints of this systematic dumbing down of our work have reached computational science, and reaping a harvest of poisoned fruit. Another sign of the problem is the lack of engagement of our top scientists in driving new directions in research. Today, managers who do not have any active research define new directions. Every year our manager’s work gets further from any technical content. We have the blind leading the sighted and telling them to trust them, they can see where we are going. This problem highlights the core of the issue; the only thing that matters today is money. What we spend the money on, and the value of that work to advance science is essentially meaningless.

Effectively we are seeing the crisis that has infested our broader public sphere moving into science. The lack of intellectual thought and vitality pushing our public discourse to the lowest common denominator is now attacking science. Rather than integrate the best in scientific judgment into our decisions on research direction, it is ignored. The experts are simply told to get in line with the right answer or be silent. In addition, the programs defined through this process then feed back to the scientific community savaging the expertise further. The fact that this science is intimately connected to national and international security should provide a sharper point on the topic.  We are caught in a vicious cycle and we are seeing the evidence in the hollowing out of good work at this conference. If one is looking for a poster child for bad research directions, the exascale programs are a good place to look. I’m sure other areas of science are suffering through similar ills. This global effort is genuinely poorly thought through and lacks any sort of intellectual curiosity.

Moving our focus back to exascale provides a useful case study of what is going wrong. We see that programs are defined by “getting funding” rather than what needs to be done or what should be done. Arguments for funding need to be as simple as possible, and faster computers are naïve enough for unrefined people to buy into. It sounds good and technically unsophisticated people buy it hook line and sinker. Computers are big loud and have lots of flashing lights to impress managers, politicians and business people who know no better. Our scientists have been cowered into compliance and simply act happy to get money for doing something. A paycheck beats the alternative, and we should feel happy that we have that. The level of inspiration in the overall approach has basically fallen off a cliff, and new ideas are shunned because they just make things complicated. We are left with the least common denominator as the driving force. We have no stomach for nuance or subtlety.

Priority is placed on our existing codes working on the new super expensive computers. The up front cost of these computers is the tip of the proverbial cost iceberg. The explicit cost of the computers is their purchase price, their massive electrical bill and the cost of using these monstrosities. The computers are not the computers we want to use, they are the ones we are forced to use. As such the cost of developing codes on these computers is extreme. These new computers are immensely unproductive environments. They are a huge tax on everyone’s efforts. This sucks the creative air from the room and leads to a reduction in the ability to do anything else. Since all the things being suffocated by exascale are more useful for modeling and simulation, the ability to actually improve our computational modeling is hurt. The only things that benefit from the exascale program are trivial and already exist as well-defined modeling efforts.

Increasingly everything is run through disconnected projects that are myopic by construction. The ability to do truly unique and groundbreaking science is completely savaged by this approach to management. Breakthroughs are rarely “eureka” moments where someone simply invents something completely new. Instead, most good research is not made through connections to other good research. Conferences are great incubators for these connections. Well-defined and proven ideas are imported and redefined to make contributions to a new area. This requires people to work across discipline boundaries, and learn about new things in depth. People need to engage deeply with one another, which is similarly undermined today by project management and information security focus. The key thing is exposure to new and related areas of endeavor and basic learning. The breakthroughs come episodically and do not lend themselves to the sort of project management in vogue today.

It isn’t like I came back with nothing. There were a couple of new things that really fall into the category of following up. In one case there was a continuation of a discussion of verification of shock tube problems with someone from Los Alamos. The discussion started in Las Vegas at the ASME VVUQ meeting, and continued in Santa Fe. In a nutshell, we were trying to get cleaner verification results by dividing the problem into specific regions associated with a particular solution feature and the expectation of different rates of convergence for each. We found something unexpected in the process that doesn’t seem to follow theoretical expectations. It’s worth some significant follow-up.  A mysterious result is always something worth getting to the bottom of. The second bit of new intellectual blood came in direct response to my talk. I will also freely admit that my contribution wasn’t the best. I haven’t had any better luck with a good free energy at work to energize my work. The same exascale demon is sucking my intellectual lifeblood out. I simply reported on a here-to-fore unreported structural failing of solvers. In summary, we find systematic, but small violations of the second law of thermodynamics in rarefactions for modern and classical methods. This shouldn’t happen and violations of the second law lead to unphysical solutions. All of this stems from identifying a brutal problem (https://williamjrider.wordpress.com/2017/06/09/brutal-problems-make-for-swift-progress/ ) that every general-purpose code fails at – what I call “Satan’s shock tube” with 12 order of magnitude jumps in density and pressure approximating propagation of waves into a vacuum.

We cannot live only for ourselves. A thousand fibers connect us with our fellow men; and among those fibers, as sympathetic threads, our actions run as causes, and they come back to us as effects.

― Herman Melville

Before closing I can say a thing or two about the meeting. None of the issues dulled the brilliance of the venue in Santa Fe, “the City Different”. While I was disappointed about not enjoying the meeting in some exotic European venue, Santa Fe is a fabulous place for a meeting. It is both old (by American standards), yet wonderfully cosmopolitan. There is genuine beauty in the area, and our hotel was nearly perfect. Santa Fe boasts exceptional weather in the fall, and the week didn’t disappoint. It has a vibrant art community including the impressive and psychedelic Meow Wolf. It was the Drury Plaza hotel placed in a remodeled (and supposedly haunted) old hospital. Two short blocks from the plaza, the hotel is enchanting and comfortable. We all shared two meals each day catered by the hotel’s exceptional restaurant. Having meals at the conference and together with the participants is optimal and makes for a much-improved meeting compared to going out to restaurants.

We had a marvelous reception on the hotel’s rooftop bar enjoying a typical and gorgeous New Mexico early autumn sunset with flowing drinks, old friends and incredibly stimulating conversation. American laws virtually prohibit government funds paying for alcohol, thus the drinks were courtesy of the British and French governments. One more idiotic prohibition on productivity and common sense that only undermines our collective efforts especially creatively and collaboratively. These laws have only gotten more prescriptive and limiting. We no longer can pay for meals for interview lunches and dinners, much less business meetings. None of this is reflective of best practice for any business. The power of breaking bread and enjoying a drink to lubricate human interactions is well known. We only hurt our productivity and capacity to produce valuable work by the restrictions. We are utterly delusional about the wisdom of these policies. All of this only serves to highlight the shortcomings in the creative energy evident from the rather low level of vibrancy exhibited by the lack of exciting new ideas.

Never underestimate the power of human stupidity.

– Robert A. Heinlein

 

The greatest enemy of knowledge is not ignorance, it is the illusion of knowledge.

― Daniel J. Boorstin

All knowledge hurts.

― Cassandra Clare

Science is an important source and process for generating knowledge for humanity. Much of science is a core of well-known and well-tested knowledge about the universe. Most of the activity for working scientists is at the boundaries of our knowledge working to push back our current limits on what is known. The scientific method is there to provide structure and order to the expansion of knowledge. We have well chosen and understood ways to test proposed knowledge. A method of using and testing our theoretical knowledge in science is computational simulation. Within computational work the use of verification, validation with uncertainty quantification is basically the scientific method in action (https://williamjrider.wordpress.com/2016/12/22/verification-and-validation-with-uncertainty-quantification-is-the-scientific-method/ ). One of the key activities in the accomplishment of our understanding of theory is the determination of uncertainties.

Unfortunately what we call “uncertainty quantification” is only a small piece of what uncertainty needs to be evaluated in testing knowledge. Too often people only do this narrow part of uncertainty quantification and falsely believe this is sufficient for science.

The basic premise is that we can test our knowledge via the systematic understanding of uncertainties. If we examine the uncertainty in an honest and complete manner, the limits of knowledge can be explored. Some uncertainty can be reduced via greater computational effort, some uncertainty can be reduced with improved modeling and some uncertainty is irreducible. It is absolutely essential to understand the nature of what we do and don’t know systematically. Careful and honest study is clear, and the strong tendency of people is to view all uncertainty as bad. This is not necessarily true. Uncertainty is completely unavoidable, and understanding the degree to which this is true can be a great unburdening. If an uncertainty is unavoidable, one can dispense with attempting to reduce it and simply figure out how to live with it.

If the uncertainty is irreducible and unavoidable, the problem with not assessing uncertainty and taking an implied value of ZERO for uncertainty becomes truly dangerous (https://williamjrider.wordpress.com/2016/04/22/the-default-uncertainty-is-always-zero/). In this case there is an uncertainty that should be there, and instead of building this knowledge into our work, we mindlessly ignore it. Sometimes it is actually mindfully ignored, which is utterly contemptible. This situation is so common as to be laughable, but actually provides the source for tragedy. Looking at weather and climate provides innumerable situations where ignorance of uncertainty may prove deadly in rather commonly encountered situations. As systems become more complex and energetic, chaotic character becomes more acute and common. This chaotic character leads to solutions that have natural variability. Understanding this natural variability is essential to understanding the system. Building this knowledge is the first step in moving to a capability to control and engineer it, and perhaps if wise, reduce it. If one does not possess the understanding of what the variability is, such variability cannot be addressed via systematic engineering or accommodation.

Courage doesn’t happen when you have all the answers. It happens when you are ready to face the questions you have been avoiding your whole life.

― Shannon L. Alder

This entire issue is engaged frequently. In the case of experiments for complex systems, the problem arises because lack of repeated experiments. Often such systems are complex and expensive, thus tests are carried out once. Even though any thoughtful examination of the situation would conclude that the results of the experiment are likely –almost certainly – highly variable, the experiment is treated as a unique event. Computational simulations of the experiment are viewed the same way; the calculation should try to reproduce this single experiment. This is potentially a recipe for disaster. A healthier point of view would be looking at this experiment as a single instance of drawn from a probability distribution. If the experiment were repeated there would be different results. A computational simulation if truly predictive would do exactly the same thing. Of course the simulations themselves are designed to compute the average response of such an experiment (based on mean field equations). All of this conspires to create big problems should the experiment actually draw from a low probability outcome (i.e., the tails of the distribution).

To address this systemic issue we need to reframe both the experimental and theoretical practice. If an experiment fails to give repeatable results, we need to work to unveil the statistical nature of the results especially for complex, high consequence systems. Theoretical models need to have the same properties more mindfully rather than producing the variability by happenstance (when mean field models produce variability almost serendipitously). Computational simulations follow the theory by construction and great benefits to our knowledge and understanding by more structurally and mindfully building in the variability to the theory. Failure to address this issuesystematically is an ever-growing limit for science. We have a major scientific gap open in front of us and we are failing to acknowledge and attack it with our scientific tools. It is simply ignored almost by fiat. Changing our perspective would make a huge difference in experimental and theoretical science, and remove our collective heads from the sand about this matter.

Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less.

― Marie Curie

At a deeper and more fundamental level the whole exploration of the true uncertainty is the search for the understanding. We seek to define our level of precision for the modeling of something by systematically examining the levels of certainty (by proxy of studying uncertainty). We need to understand the quality of our knowledge, and a complete survey of uncertainty is a path to this end. For computational modeling there are three broad categories for the uncertainty, the model itself, the model’s numerical solution, and the experimental fidelity used to grant confidence to the model. Each of these uncertainties can in turn be broken down into more detailed pieces. For

example we must compare to the model itself rather than the error in the solution of the model. It is important to choose some structure for the uncertainty and commit to an estimate of all portions of the structure. One should never take a zero magnitude for the uncertainty of any structural element by ignoring it.

Any fool can know. The point is to understand.

― Albert Einstein

One of the clearest ways to undermine this quest for understanding the boundaries of our knowledge is ignoring a key uncertainty. There are several usual suspects for the willful uncertainty ignorance. Probably the most common uncertainty to be willfully ignorant of is numerical error. The key numerical error is discretization error that arises from the need to make a continuous problem, discrete and computable. The basic premise of computing is that more discrete degrees of freedom should produce a more accurate answer. Through examining the rate that this happens, the magnitude of the error can be estimated. Other estimates can be had though making some assumptions about the solution and relating the error the nature of the solution (like the magnitude of estimated derivatives). Other generally smaller numerical errors arise from solving systems of equations to a specified tolerance, parallel consistency error and round-off error. In most circumstances these are much smaller than discretization error, but are still non-zero.

Experimental observations are only experience carefully planned in advance, and designed to form a secure basis of new knowledge.

― Sir Ronald Fisher

A second category of uncertainty that is highly prone to being ignored is the experimental variability. Often this is the direct consequence of only doing a single experiment. Rather then know the physics of the problem well enough to make the conclusion that the experiment will be highly variable, this is ignored and we will endeavor to model the single experiment as a unique well-determined event. The result of this set of unjustified assumptions is wholesale ignorance of systematic and irreducible uncertainty. This is truly scientific malpractice. Addressing this shortcoming should be the focus of significant effort experimentally, as well as in modeling and its numerical solution. It is a very large and largely unaddressed issue in science.

In addition to ignoring the intrinsic variability in the experiments, the more classical and even less excusable uncertainty often ignored is measurement error. This error is always present even in cases where the experiment is well posed and utterly reproducible. Measurements are always finite precision and have some degree of error and uncertainty. This finite value should always be reported as part of the experimental comparison even when the uncertainty is small. In a deep sense the small uncertainty is more important because it lends credence to the sense that the data is high quality. Not reporting the uncertainty simply leaves this vague and undefined.

The last area of uncertainty is the modeling uncertainty. In the vast majority of cases this will be the largest source of uncertainty, but of course there will be exceptions. It has three major components, the choice of the overall discrete model, the choice of models or equations themselves, and the coefficients defining the specific model. The first two areas are usually the largest part of the uncertainty, and unfortunately the most commonly ignored in assessments. The last area is the most commonly addressed because it is amenable to automatic evaluation. Even in this case the work is generally incomplete and lacks full disclosure of the uncertainty.

Today in examining modeling uncertainty we most often attack the least important one systematically, and the more important modeling uncertainties are ignored. The “easy” uncertainty to attack is the coefficients in the model. This can be achieved using well-developed methods such as MCMC (Markov chain Monte Carlo). One can define a set of parameters to be varied and ranges for the variation. The calculations can berepeated using values drawn to efficiently sample the probability space of the calculation and produce the uncertainty. This sampling is done for a very highly dimensional space, and carries significant errors. More often than not the degree of error associated with the under sampling is not included in the results. It most certainly should be.

The other two uncertainties are generally larger and thus more important to characterize. Unfortunately neither is amenable to the sort of turnkey black box approach the parametric uncertainty allows. As a result these uncertainties are usually completely ignored. These two areas of uncertainty are closely related. Any complex problems can be modeled in a variety of ways. An analyst ends up making innumerable assumptions and choices in the course of modeling a complex problem. One choice is the code used for the analysis and the specific settings within the code. Beyond this there are choices on how the problem is meshed, boundary conditions, initial conditions, submodels to close the equations, and analysis of results. Each and every one of these choices can produce changes in the results. It is very uncommon to see a problem solved in different or remotely independent ways. As a result the uncertainty from the modeling and analysis is usually completely hidden.

Science, my boy, is made up of mistakes, but they are mistakes which it is useful to make, because they lead little by little to the truth.

― Jules Verne

To truly test our knowledge in a topic we must be open to a full and honest evaluation of the uncertainties. Knowledge and uncertainty are two sides of the same coin. If you don’t know the uncertainty, you don’t know the extent of your knowledge. Too often we only do the assessment that is easy. In this assessment strategy we also implicitly choose uncertainty estimates of ZERO for information we know is uncertain, but difficult to assess. This is a pernicious and dangerous practice. Due diligence and responsibility should dictate that some sort of uncertainty be estimated for all sources. If we cannot estimate these uncertainties in a credible and knowledgeable manner, we have no business in modeling and our experiments are not yielding their full value. The only responsible act in this case would be to produce work that would make such a bounding assessment possible.

Negative results are just what I want. They’re just as valuable to me as positive results. I can never find the thing that does the job best until I find the ones that don’t.

― Thomas A. Edison

Your number-one mission as a speaker is to take something that matters deeply to you and to rebuild it inside the minds of your listeners. We’ll call that something an idea.
― Chris J. Anderson

Every September my wife and I attend the local TeDx event here in Albuquerque. It is a marvelous way to spend the day, and leaves a lasting impression on us. We immerse ourselves in inspiring, fresh ideas surrounded by like-minded people. It is empowering and wonderful to see the local community of progressive people together at once listening, interacting and absorbing a selection of some of the best ideas in our community. This year’s event was great and as always several talks stood out particularly including Jannell MacAulay (Lt.Col USAF) talking about applying mindfulness to work and life, or Olivia Gatwood inspiring poetry about the seeming mundane aspects of life that speaks to far deeper issues in society. The smallest details are illustrative of the biggest concerns. Both of these talks made me want to think deeply about applying these lessons in some fashion to myself and improving my life consequentially.

That’s part of the point of TeD, the talks are part of the gospel of progress, part marketing of great ideas and part performance art. All of these things have a great use to society in lifting up and celebrating a drive to be better and progress toward a better future. Humanity has immense power to change the world around them for the better. We can look across the globe and witness the collective power of humanity to change their environment. A great deal of this change is harmful or thoughtless, but much of it is a source of wonder. Our understanding of the World around us and the worlds within us has changed our biological destiny.

We have transitioned from an animal fighting for survival during brief violent lives, to beings capable of higher thought and aspiration during unnaturally long and productive lives. We can think and invent new things instead of simply fighting to feed us and reproduce a new generation of humans to struggle in an identical manner. We also can produce work whose only value is beauty and wonder. TeD provides a beacon for human’s best characteristics along with a hopeful forward-looking community committed to positive common values. It is a powerful message that I’d like to take with me every day. I’d like to live out this promise with my actions, but the reality of work and life comes up short.

There was a speaker from my employer this year, and there always is. There wasn’t anyone from my former employer, the other major scientific Lab in our state (what was once one of the premier scientific institutions in the World, but that’s a thing of the past). Also noticeable is the lack of support for the local TeD organization by either employer. I’ll grant you that Los Alamos has supported it in the past, but no longer. There’s probably some petty and idiotic reason for the withdrawal of support. My employer, Sandia, doesn’t support it, and hasn’t ever. It looks like our local University doesn’t support it either. I know that Los Alamos did their own local TeD conference and perhaps they thought that was enough TeD for them. That’s the sad best-case scenario, and I don’t know what the full story is.

For Sandia it’s not particularly surprising as it’s not exactly a progressive, idea-centered place, and these days no place is anyway. The University should be, but the lack of financial support from the state could explain it (its a common characteristic of GOP governance to eviscerate universities). It is quite hard for me to express my level of disappointment in these institutions’ lack of civic support for progressive thought. It is stark testimony on the current state of affairs where two National Laboratories and a University cannot be supportive of a major source of progressive thought in the community they are embedded within. An active progressive and intellectual community in the areas where these institutions are located should be beneficial for recruiting and retention of progressive and intellectual staff. It is one sign that this sort of long view isn’t at work. It is a sign of the times.

TeD talks are often the focus of criticism for their approach and general marketing nature strongly associated with the performance art nature. These critiques are valid and worth considering including the often-superficial nature of how difficult topics are covered. In many ways where research papers can be criticized increasingly as merely being the marketing of the actual work, TeD talks are simply the 30-second mass market advertisement of big ideas for big problems. Still the talks provide a deeply inspiring pitch for big ideas that one can follow up on and provide the entry to something much better. I find the talk is a perfect opening to learning or thinking more about a topic, or merely being exposed to something new.

Control leads to compliance; autonomy leads to engagement.

– Daniel H. Pink

One prime example is one of my favorite talks of all time by Daniel Pink (https://www.ted.com/talks/dan_pink_on_motivation). This talk is basically a pitch for the book “Drive” and touches only superficially on the topic. The book itself is a distillation of very complex topics. All of this is true, but none of this undermines the value in the ideas. TeD provides a platform to inspire people to do more and get closer to the actual application of the ideas to their lives (not just buy Pink’s book, the true cynics take on the purpose). Interestingly, the managers at work were also reading Pink’s book and discussing the ideas therein. The rub was the observation that I could not identify a single thing recommended in Pink’s book that made it to the workplace. It seemed to me that the book simply inspired the management to a set of ideals that could not be realized. The managers aren’t really in charge; they are simply managing the corporate compliance instead of managing in a way that maximizes the performance of its people. The Lab isn’t about progress any more; it is about everything, but progress. Compliance and subservience has become the raison d’etre.

For artists, scientists, inventors, schoolchildren, and the rest of us, intrinsic motivation the drive do something because it is interesting, challenging, and absorbing is essential for high levels of creativity.

– Daniel H. Pink

Intrinsic motivation is conducive to creativity; controlling extrinsic motivation is detrimental to creativity.

–Daniel H. Pink

This deep frustration isn’t limited to TeD talks; it is almost every source of great advice or inspiration available. Almost every manager I know reads the Harvard Business Review. I read it too. It is full of wonderful ideas and approaches to improving the way we work. It is impossible to see anything ever done with all the great advice or inspiration. My workplace looks like all the “before” cases studies in HBR and more like it every day, not less. Nothing ever recommended happens at work, nothing is tried, nothing changes in the positive direction; its like we are committed to moving backwards. HBR is progressive in terms of the business world. The problem is that the status quo and central organizing principle today is anti-progressive. Progress is something everyone is afraid of, and the future appears to be terrifying and worth putting off for as long as possible. We see genuinely horrible lurch toward an embrace of the past along with all its anger, bigotry, violence and fear. Fear is the driving force for avoiding anything that looks progressive.

Management isn’t about walking around and seeing if people are in their offices, he told me. It’s about creating conditions for people to do their best work.

– Daniel H. Pink

Now that I’ve firmly established the lack of relevance of TeD and progressive thought in my workplace, I can at least appreciate and apply it at a personal level. I’d love for work to reflect a place for genuine progress, but this seems a bridge too far today. Work is a big part of life and these observations are rather dismaying. Ideally, I’d like a workplace that reflects my own values. The truth of the matter is that this is nearly impossible for a progressive-minded person in America today. Even the bastions of progressive thought like Universities are not working well. Society at large seems to be at war with elites and progressive thought far more under siege than whites, or Christians. I can ask the serious question, how many atheists are in Congress? How much well proven and accepted science does our government reject already? Don’t get me started on our judicial system, or the war on drugs both of which focus far more on oppressing minorities than crime or drug abuse. The bottom line is the sense that we are in a societal backlash against change; so more progress seems to be impossible. We will be fighting to hold onto the progress we’ve already made.

Still I can offer a set of TeD talks that have both inspired me and impacted my life for the better. They have either encouraged me to learn more, or make a change, or simply change perspective. I’ll start with a recent one where David Baron gave us an incredibly inspiring call to see the total eclipse in its totality (https://www.ted.com/talks/david_baron_you_owe_it_to_yourself_to_experience_a_total_solar_eclipse). I saw the talk concluding that I simply had to go, and then I showed to my wife to convince her. It did! We hopped into the car at midnight the day of eclipse and drove eight hours to get from Northern Idaho to Eastern Oregon. We got off I-82 atDurkee finding a wonderful community center with a lawn and watched it with 50 people from all over the local area plus a couple from Berlin! The totality of the eclipse lasted only two minutes. It was part of a 22-hour day of driving over 800 miles, and it was totally and completely worth every second! Seeing the totality was one of the greatest experiences I can remember. My life was better for it, and my life was better for watching that TeD talk.

Another recent talk really provoked me to think about my priorities. It is a deep consideration of what your priorities are in terms of your health. Are you better off going to the gym or going to party, or the bar? Conventional wisdom says the gym will extend your life the most, but perhaps not. Susan Pinker provides a compelling case that social connection is the key to longer life (https://www.ted.com/talks/susan_pinker_the_secret_to_living_longer_may_be_your_social_life ). This gets at the disparity between men and women since women tend to connect in long life affirming friendships with greater ease than men. The talk is backed up by data, and by visiting places where people live long lives. These people live in communities where they are entangled in each other’s lives almost by design. It gets to the priorities associated with health care and self care along with the benefit of actions. Focusing on your social life is a genuinely beneficial act to prolonging your life.

Our modern computing world is a marvel, but it also has some rather pronounced downsides. In many ways our cell phones are making us far unhappier people. The phones and their apps are designed to grab, demand our attention. They can become sources of deep and pervasive anxiety. This is exactly what they are designed to do. As Adam Alter explains, an entire industry is set up to get as much of our attention as possible because our attention equals money, big money (https://www.ted.com/talks/adam_alter_why_our_screens_make_us_less_happy). He also explains that it doesn’t have to be like this. The same social engineering that has gone into making the phones so demanding could be harnessed to help us be better. If we balanced the naked profit motive with some measure of social responsibility, we might turn this problem into a benefit. This is a wonderfully inspiring idea; it is also terribly progressive and dangerous to the unfettered capitalism fueling this growing societal crisis.

Love rests on two pillars: surrender and autonomy. Our need for togetherness exists alongside our need for separateness.

– Esther Perel

The power of TeD extends to far deeper personal matters as well. A couple of talks by Esther Perel speak to reframing our love lives (https://www.ted.com/talks/esther_perel_the_secret_to_desire_in_a_long_term_relationship, https://www.ted.com/talks/esther_perel_rethinking_infidelity_a_talk_for_anyone_who_has_ever_loved ). Perel defies conventional thought on love, marriage and infidelity providing a counter theory to all these matters. Her first talk is an accompaniment to her first book and tackles the thorny issue of keeping your long-term relationship hot and steamy. It is a challenge many of us have tackled, and no doubt struggled with. This struggle is for good reasons, and knowing the reasons provides insight to solutions. Perel powerfully explains the problem and speaks to working toward solutions.

The thornier issue of infidelity is the second talk (and her brand new book). Like before, she tackles the topic from a totally different perspective. Her approach is unconventional and utterly refreshing. The new perspectives provide an alternative narrative to handling this all too common human failing. Explaining and understanding the complex root of this all-to-common relationship problem can improve our lives. It is an alternative to the moral perspective that has failed to provide any solutions. Among the threads to concentrate on is the relatively new character of modern marriage in the history of humanity, and the consequences of the deep changes in the institution. One of the beauties of TeD is the exposure to fresh perspective on old ideas along side completely new ideas.

The very ingredients that nurture love mutuality, reciprocity, protection, worry, and responsibility for the other are sometimes the very ingredients that stifle desire.

– Esther Perel

Truth and courage aren’t always comfortable, but they’re never weakness.

– Brene Brown

The last talk I’ll highlight today is truly challenging to most of us. Brene Brown is a gifted and utterly approachable speaker presenting a topic that genuinely terrifies most of us, vulnerability (https://www.ted.com/talks/brene_brown_on_vulnerability). Begin vulnerable is an immensely valuable characteristic that almost everyone struggles with. Vulnerable often equates with being weak, but also open and honest. That openness and honesty is the key to being a better person and developing better relationships. In many cases the weakness and honesty is shared only with yourself. In either case vulnerability provides an avenue to connection and an embrace of humanity that both frees you and allows deeper relationships to flourish. The freedom you give yourself allows you to grow, learn and overcome bad experiences.

What would you be glad you did–even if you failed?

– Brene Brown

I always wish that I could focus on most of what I hear at a local TeD event, but one must make choices, time and effort are limited. While I do plan to more mindfully apply mindfulness to my life, right now I’ll hedge toward the artistic side of things, if for no other reason that I usually don’t. I will close by honoring the inspirational gift of Olivia Gatwood’s talk on poetry about seeking beauty and meaning in the mundane. I’ll write a narrative of a moment in my life that touched me deeply.

The Best Gift

A night of enchanting companionship was drawing to a close,

and I was longing for one last kiss before parting

Those early autumn nights are so welcoming,

 

the crisp nights promised, but not yet arrived,

summer still alive, but fading

I hadn’t even bothered to fully dress for the goodbye,

 

Conventions and neighbors be damned

It was a warm evening and my skin wanted to drink it in,

drink her in too, one last time

 

We slowly made our way out to my driveway

talking, still flirting, our banter unabated

The moon full, bright, and peeking between the gaps in the single cloud

 

adorning the sky as it illuminates the night

It will light her way home as a warm beacon

“Good,” I think, “you’ll be safe” on your long drive home

 

We draw close to each other, pressing hard while

savoring the time spent together fun and friendship

with a depth that was unexpected, but welcome

 

You ask, “What would you like for your birthday?”

My mind goes to my elaborate tattoo to adorn me soon,

“I’m already getting what I want for myself”

 

“I always ask for more time,” she said longingly

Her words cut me to the core,

of course, what else would she want?

 

My head spins with the truth revealed by her breathtaking honesty,

with words failing me for a breath or two, … or three

My mind opens with the realization of her precious offering

 

“I just want good memories”

Realization washes over me, she just gave me the best gift I could have hoped for

We kiss deeply and parted until we next renew making good memories

 

 

You are not special. You’re not a beautiful and unique snowflake. You’re the same decaying organic matter as everything else. We’re all part of the same compost heap. We’re all singing, all dancing crap of the world.

– Chuck Palahniuk

This post was inspired by twin events: a comment from a dear friend, and watching the movie “Fight Club” again. This is my 300^th blog post here. Its been an amazing experience thanks for reading.

If you consider the prospect of retirement and you feel that your place of work does not need you and would not suffer from you departure, you aren’t alone. This is an increasing trend for work today. You are an imminently replaceable cog in the machine, which can be interchanged with another person without any loss to the workplace. Your personal imprint on the products of work is not essential and someone else could do exactly what you do. If you work in one of the many service industry jobs, or provide the basic execution of tasks, the work is highly prescribed and you versus someone else doesn’t matter much. If you are reliable, show up and work hard, you are a good worker, but someone else with all the same characteristics is just as good.

What’s measured improves

–Peter F. Drucker

I didn’t used to feel this way, but times have changed. I felt this way when I worked at McDonalds for my first job. I was a hard worker, and a kick ass grill man, opener, closer, and whatever else I did. I became a manager and ultimately the #2 man at a store. Still I was 100% replaceable and in no way essential, the store worked just fine without me. I was interchangeable with another hard working person. It isn’t really the best feeling; you’d like to be a person whose imprint on the World means something. This is an aspiration worth having, and when your work is truly creative, you add value in a way that no one else can replicate.

When I started working almost 30 years ago at Los Alamos, this dynamic felt a lot different. People mattered a lot, and an individual was important. Every individual was important, unique and worth the effort. As a person you felt the warm embrace of an incubator for aspiring scientists. You were encouraged to think of the big picture, and the long term while learning and growing. The Lab was a warm and welcoming place where people were generous with knowledge, expertise and time. It was still hard work and incredibly demanding, but all in the spirit of service and work with value. I repaid the generosity through learning and growing as a professional. It was an amazing place to work, an incredible place to be, an environment to be treasured, and made me who I am today.

Never attribute to malevolence what is merely due to incompetence

–Arthur C. Clark

It was also a place that was out of time. It was a relic. The modern World came to Los Alamos and destroyed it, creating a shadow of its former greatness. The sort of values that made it such a National treasure and one of the greatest institutions could not coexist with today’s culture. The individuals so treasured and empowered by the scientific culture there were relabeled as “butthead cowboys,” troublemakers, and failures. The culture that was generous, long term in thought, viewing the big picture and focused on National service was haphazardly dismantled. Empowerment was ripped away from the scientists and replaced with control. Caution replaced boldness, management removed generosity, all in the name of formality of operations that removes anything unforeseen in outcomes. The modern world wants assured performance. Today Los Alamos is mere shadow of itself, stumbling forward toward the abyss of mediocrity. Witnessing this happen was one of the greatest tragedies of my life.

People who don’t take risks generally make about two big mistakes a year. People who do take risks generally make about two big mistakes a year.

–Peter F. Drucker

Along with assured performance we lose serendipity and discovery. We lose learning and surprises, good and bad. We lose the value in the individual, and the ability to have one person make a positive difference. All of this is to keep one person from making a negative difference or to avoid mistakes and failures. The removal of mistakes and failures removes the engine of learning and real scientific discovery from table as well. Each and every one of these steps is directly related to the fear of the bad things happening. Every good is a flip side of a bad thing, and when you can’t accept the bad, you can’t have the good either. In the process the individual has been removed from importance. Everything is process today and anything bad can be managed out of existence. No one looks at the downside to this, and the downside is sinister to the quality of the workplace.

Let’s be clear about what I’m talking about. This isn’t about being cavalier and careless. It isn’t an invitation to be dangerous or thoughtless. This is about making a best earnest effort at something, and still failing. This is about doing difficult things that may not succeed, putting your best effort forward even if it falls short. In many ways we have lost the ability to distinguish between the good and bad failure with all failure viewed as bad, and punished. We have made the workplace an obsessively cautious and risk adverse place that lacks the soul it once embraced. We have lost the wonder and power of the supremely talented person in the prime of their creative powers to create game changing things or knowledge.

The core problem is the willingness to deal with the inevitable risks and failures with empowering people. Instead of seeing the risks and failures and a necessary element in enabling success, we have fallen victim to the fiction that we can manage the risk and failure out of existence, all while assuring productivity. This is utterly foolish and antithetical to reality. The risks are necessary to strive to achieve difficult and potentially great things. If one is working at the limit of their capability the result is frequently failure, and the ensemble of failures paves the way for success. It tells us clearly what does not work, and provides the hard lessons that educate us. Somehow we have allowed the delusion that achievement can be had without risk and failure to creep into our collective consciousness.

Instead of encouraging and empowering our people to take risks while tolerating and learning from failure, we do the opposite. We steer people away from doing risky work, punish failure and discourage lesson learning. It is as if we had suddenly become believers in the “free lunch”. True achievement is extremely difficult, and true achievement is powered by the ability to try to do risky almost impossible things. If failure is not used as an opportunity to learn, people will become disempowered and avoid the risks. This in turn will kill achievement before it can even be thought of. The entire system would seem to be designed to disempower people, and lower their potential for achievement.

The other aspect of this truly viscous cycle is the dismantling of expertise. Expertise is built on the back of years and years of failure. Of course this happens only if the failures are actively engaged as educational opportunities that empower the expert to engage in more thoughtful risks. These thoughtfully engaged in risks still need to fail and perhaps fail most of the time. Gradually the failures of today begin to look like the achievements of yesterday. What we see as a failure today would be a monumental achievement a decade ago. This is completely built on the back of seeing the failures of yesterday in the right light, and learning the lessons available from the experience.

When we empower people to take risks and grow them into experts, they also provide the knowledge necessary to mentor others. This was a key aspect of my early career experience at Los Alamos. At that time the Lab was teeming with experts who were generous with their time and knowledge. All you had to do was reach out and ask, and people helped you. The experts were eager to share their experience and knowledge with others in a spirit of collective generosity. Today we are managed to completely avoid this with managed time and managed focus. We are trained to not be generous because that generosity would rob our “customers” of our effort and time. The flywheel of the experts of today helping to create the experts of tomorrow is being undone. People are trained to neither ask, nor provide expertise freely.

What we are moving toward is a system that is less than the sum of its parts. What I started with was a system that added great value to every person, and effectively was far greater than the sum of its parts. The generosity that characterized my early career added immense value to every hour spent at work. Today this entire way of working is being torn apart by how we are managed. People can’t be generous if they have to account for all their time and charge it to a specific customer. The room for serendipity, discovery and the addition of personal value to activities is being removed to satisfy bean counters and small-mined people. We have allowed an irrational fear of one misspent dollar to waste billions of dollars and the productive potential of people’s lives. Worse yet, the whole apparatus erected to produce formal operations are ripping the creative force from the workplace and replacing it with soulless conformity. It matters less and less who we are each day; we are simply replaceable parts in a mindless machine.

I might be temped to simply end the discussion here, but this conclusion is rather dismal. It is where we find ourselves today. We also know that the state of affairs can be significantly better. How can we get there from here? The first step would be some sort of collective decision that the current system isn’t working. From my perspective, the malaise and lack effectiveness of our current system is so pervasive and evident that action to correct it is overdue. On the other hand, the current system serves the purposes of those in control quite well, and they are not predisposed to be agents of change. As such, the impetus for change is almost invariably external. It is usually extremely painful because the status quo does not want to be rooted out unless it is forced to. The circumstances need to demand performance that current system cannot produce, and as systems degrade this becomes ever more likely.

At the time, my life just seemed too complete, and maybe we have to break everything to make something better out of ourselves.

–Chuck Palahniuk

The current system is thoroughly disempowering and oriented toward explicit control of people’s actions. Keeping order and people in line while avoiding risk and failure are the core principles. The key to any change is enabling trust for the individual to move to centrality in the system. The upside to the trust is the degree of efficiency and effectiveness that is born from trust; the downside is the possibility of failure, poor performance and various human failings. The system needs to be resilient to these inevitable problems with people. The negative impact of trying to control and manage these failings results in destroying most of the positive things individuals can provide. Empowerment needs to trump control and allow people’s natural inclination toward success to be central to organizational design.

In most cases being a good boss means hiring talented people and then getting out of their way.

–Tina Fey

We need to completely let go of the belief that we can manage all the bad things away and not lose all the good things in the process. Bad things, bad outcomes and bad behavior happen, and perhaps need to happen to have all the good (in other words “shit happens”). Today we are gripped with a belief that negative outcomes can be managed away. In the process of managing away bad outcomes, we destroy the foundation of everything good. To put it differently we need to value the good and accept the bad as a necessary condition for enabling good outcomes. If one looks at failure as the engine of learning, we begin to realize that the bad is the foundation of the good. If we do not allow the bad things to happen, let people fuck things up, we can’t have really good things either. One requires the other and our attempts to control bad outcomes, removes a lot of good or even great outcomes at the same time.

An expert is someone who knows some of the worst mistakes that can be made in his subject, and how to avoid them.

– Werner Heisenberg

So to sum up, let’s trust people again. Let’s let them fail, fuck up and do bad things. Let’s let people learn from these failures, fuck up’s and painful experiences. These people will learn a lot, including very painful lessons and get hurt deeply in the process. They will become wise, strong, and truly experts at things. People who are entrusted are empowered and love their work. They are efficient, productive and effective. They have passion for what they do, and give their work great loyalty. They will take risks in a fearless manner. They will be allowed to fail spectacularly because spectacular success and breakthroughs only come from these fearlessly taken risks.

May I never be complete. May I never be content. May I never be perfect.

–Chuck Palahniuk

 

 

Sometimes the hardest thing any of us can hope for is finding the courage to be honest with ourselves.

― Kira Saito

Today I’m writing about dealing with the unfortunate practice of failing to address uncertainty, and implicitly setting its value to zero, the smallest possible value. This approach is pernicious, and ubiquitous in computational science (and a lot of other science). It is a direct threat to progress and far too acceptable in practice.  I wrote about this at length decrying this standard practice, but it remains the most common practice in uncertainty quantification (https://williamjrider.wordpress.com/2016/04/22/the-default-uncertainty-is-always-zero/). In a nutshell when someone doesn’t know what the uncertainty is they simply assign a value of zero to it. We can do something better, but first this needs to be recognized for what it is, systematic and accepted ignorance.

The reasons for not estimating uncertainties are legion. Sometimes it is just too hard (or people are lazy). Sometimes the way of examining a problem is constructed to ignore the uncertainty by construction (a common route to ignore experimental variability and numerical error). In other cases the uncertainty is large and it is far more comfortable to be delusional about its size. Smaller uncertainty is comforting and implies a level of mastery that exudes confidence. Large uncertainty is worrying and implies a lack of control. For this reason getting away with choosing a zero uncertainty is a source of false confidence and unfounded comfort, but a deeply common human trait.

If we can manage to overcome the multitude of human failings underpinning the choice of the default zero uncertainty, we are still left with the task of doing something better. To be clear, the major impediment is recognizing that the zero estimate of uncertainty is not acceptable (most “customers” like the zero estimate because it seems better even though its assuredly not!). Most of the time we have a complete absence of information to base uncertainty estimates upon. In some cases we can avoid zero uncertainty estimates by being more disciplined and industrious, in other cases we can think about the estimation from the beginning of the study and build the estimation into the work. In many cases we only have expert judgment to rely upon for estimation. In this case we need to employ a very simple and well-defined technique to providing an estimate.

Learning is not the accumulation of knowledge, but rather, one thing only: understanding

― Donna Jo Napoli

The best way to explore estimates is using the time-honored approach of bounding the uncertainty. One should be able to provide clear evidence that the uncertainty is both smaller and larger than certain known values. This provides bounds for the magnitude of uncertainty.  Depending on the purpose of the study, these magnitudes can be used to more appropriately use the results. This can then be used to provide some sort of reasonable and evidence based uncertainty to energize progress and underpin credibility. If the estimate of the smallest possible uncertainty is that ubiquitous zero, the estimate should be rejected out of hand. The uncertainty is never ZERO, not ever. Nothing is known with absolute certainty. If the uncertainty is very small there should be very strong evidence to support the bold assertion. We do know some things extremely well like Planck’s constant, but it still has an uncertainty of a finite size.

The flip side to the lower bound is the upper bound for the uncertainty. Generally speaking, there will be a worst case to consider or something more severe than the scenario at hand. Such large uncertainties are likely to be quite uncomfortable to those engaging in the work. This should be uncomfortable if we are doing things right. The goal of this exercise is not to minimize uncertainties, but get things right. If such bounding uncertainties are unavailable, one does not have the right to do high consequence decision-making with results. This is the unpleasant aspect of the process; this needs to be the delivery of the worst case. To be more concrete in the need for this part of the bounding exercise, if you don’t know how bad the uncertainty is you have no business using the results for anything serious. As stated before the bounding process needs to be evidence based, the assignment of lower and upper bounds for uncertainty should have a specific and defensible basis.

Belief can be manipulated. Only knowledge is dangerous.

― Frank Herbert

Once the bounds for the uncertainty are established along with associated evidence, some choices need to be made to use the information. To a large extent the most conservative choice is the easiest to defend meaning that the upper bound for uncertainty should be used. If the work is being engaged in an honest sense this would be a pessimistic perhaps in the extreme. If one thinks about things in a probabilistic sense, the bounds should establish an interval for the potential uncertainty. This interval is most likely to be defensibly treated with a uniform distribution. For most cases using a midpoint averaging the lower and upper bounds is a reasonable choice. If the application associated with the decision-making is extremely important, the upper bound or something skewed in that direction is probably advisable.

To some extent this is a rather easy lift intellectually. Cultural difficulty is another thing altogether. The indefensible optimism associated with the default zero uncertainty is extremely appealing.  It provides the user with a feeling that the results are good. People tend to feel that there is a single correct answer. The smaller the uncertainty is the better they feel about the answer. Large uncertainty is associated with lack of knowledge and associated with low achievement. The precision usually communicated with the default, standard approach is highly seductive. It takes a great deal of courage to take on the full depth of uncertainty along with the honest admission of how much is not known. It is far easier to simply do nothing and assert far greater knowledge while providing no evidence for the assertion.

Uncertainty is a discomforting concept for people. Certainty is easy and comfortable while uncertainty is difficult and carries doubt. It is problematic to consider the role of chance in events, and the fickle nature of reality. A great many important events occur largely by chance and could have quite easily turned out quite differently. Consider how often you encounter a near miss in life, something where danger seemed far to close and just missed you. When these events turn out disastrously they can be tragedies. How often have similar tragedies been barely averted? This same dynamic plays out in experiments that are repeated. An attempt is made to make the experiment reproducible. Occasionally something completely different unfolds. The repeated effects are never exactly the same; there is a small variation. These variations are the uncertainty and depending on the experiment, they have a magnitude.

What happens when you do the experiment exactly once? The simplest thing to do is consider this experiment to be a completely determined event with no uncertainty at all. This is the knee jerk response of people is the consideration of this single event as being utterly and completely deterministic with no variation at all. If the experiment were repeated with every attempt to make it as perfect as possible, it would turn out slightly differently. This comes from the myriad of details associated with the experiment that determine the outcome. Generally the more complex and energetic the phenomenon of being examined is, the greater the variation (unless there are powerful forces attracting a very specific solution). There is always a variation, the only question is how large it is; it is never, ever identically zero. The choice to view the experiment as perfectly repeatable is usually an unconscious choice that has no credible basis. It is an incorrect and unjustified assumption that is usually made without a second thought. As such the choice is unquestionably bad for science or engineering. In many cases this unconscious choice is dangerous, and represents nothing more than wishful thinking.

to hope was to expect

― Jane Austen

 

 

 

The purpose of life is not to be happy. It is to be useful, to be honorable, to be compassionate, to have it make some difference that you have lived and lived well.

― Ralph Waldo Emerson

As one gets older and enters into the heart of mid-life, it is natural to contemplate ones place in the World. I’m deep into such contemplation. I’ve been blessed with work with meaning for much of my adult life, but that meaning seems to have leaked away recently. Part of my thinking is the decision of whether this is a local or global condition. Are things worse where I am, or better than the average? For most of my adult life, I’ve had far better conditions than average, and been able to find great meaning in my work. Is the steady erosion of the quality of the work environment a consequence of issues local to my institution or organization? Or is it part of the massive systemic dysfunction our society is experiencing?

If the problem is local, I could leave for another organization, or another institution that is functioning better. If it’s a global issue, then its not something I can likely influence (much), and its time to ride the storm out the best I can. Right now my money is on the issue being global, and we ought to all be ready for the shit to hit the fan. My guess it is already happened, the shit storm is in effect and we are headed into deep trouble as a Nation and the World. We have repugnantly dysfunctional National government, led by an incompetent narcissistic conman without a perceptible moral compass. Racial tensions, and a variety of white supremacist/right wing ultra-Nationalists are walking the streets. Left wing and anarchist groups are waking up as well. Open warfare may soon be upon us making us long for the days where sporadic terrorist attacks were our biggest worry. A shit storm is actually a severe understatement; this is a fucking waking nightmare. I hope this is wrong and I could simply find a better place to work at and feel value in my labors. I wish the problem was simple and local with a simple job change fixing things.

Work is an important part of life for a variety of reasons. It is how we spend a substantial portion of our time, and much of our efforts go into it. In work we contribute to society and assist in the collective efforts of mankind. As I noted earlier, I’ve been fortunate for most of my life, but things have changed. Part of the issue is a relative change in the degree of self-determination in work. The degree of self-determination has decreased over time. An aspect of this is the natural growth in scope of work as a person matures. As a person grows in work and is promoted, the scope of the work increases, and the degree of freedom in work decreases. Again this is only a part of the problem as the system is working to strangle the self-determination out of people. This is control, fear of failure and generic lack of trust in people. In this environment work isn’t satisfying because the system is falling apart, and the easiest way to resist this is controlling the little guy. My work becomes more of a job and a route to a paycheck every day. Earning a living and supporting your family is a noble achievement these days, and aspiring to more simply a waking dream contracting in the rear view mirror of life.

Creative autonomy is essential for the work I do to be satisfying. It is essential to the work being effective. I can’t be an effective problem solver if most of my best options are off the table. We exist in a system where the solutions are dictated in advance. No one is trusted to solve any real problems, just work toward the solutions that have been pre-ordained. Autonomy is threatening to the system because the trust in people is so intrinsically low. The result is the leaking away of meaning in work. The control that exists only calms the deep fears of a system that is failing. Inside the model where we are teetering on the edge of a societal shit storm, the attempt to control makes sense. The system is desperately trying to hold onto whatever control it has, fearing the unraveling about to unfold. Fear makes us do stupid things, and the fear is simply throwing fuel onto the fire by making everyone simply hate life.

The purpose of life is a life of purpose.

― Robert Bryne

I’m trying to grapple with what is happening in my own experience through the lens of the bigger picture. We see a contraction of the trust and autonomy necessary for me to enjoy work. This is in direct reaction to the fears unleashed by the changes in society, and the terror these changes have induced in much of the population. The old world is coming to an end, but not without a fight. People are genuinely frightened by change, and for most people the most comfortable place is the past. They are holding onto the past with a fervent passion, but the future is unstoppable. In between the two is conflict and pain. For someone like myself who demands work that makes progress, I might have to take a break and simply resign myself to defending the progress that has already been made. No new progress can happen without trust in an environment dominated by fear. We are simply trying to maintain the progress that has already been won.

Imagine what our story would look like if, rather than succumbing to the insistent voices of family or culture, we determined that our vocation was to be a better human.

― James Hollis, Ph.D.

The domination of fear has an extremely large impact on the appetite for risk; there isn’t any. Part of the fearful environment is the inability to accept anything that looks, smells or even hints at failure. Without failure you don’t have learning or achievement. Research depends on failure because research is basically learning in its rawest form. Let me be clear that I’m talking about good failure where you try your best, making a best effort and coming up short. Most of the time a failure leads to learning something new. You tweak your approach or knowledge on the basis of the experience and grow. Without failure you short-circuit expertise. We need to energize failure in many small things to engage success in big things. All of this requires the sort of deep trust that our current World is almost devoid of. A combination of courage and trust can unleash people’s full potential through allowing them to fail spectacularly and then fully support the next step forward. Today, cowardice and mistrust dominate and even marginal failure results in punishment. It is corroding the foundation of achievement. It makes work simply a job and life more survival than living.

Since our current World is so deeply arrayed against personal success and growth, it might be wise to seek other avenues of fulfillment. Perhaps work is most healthily viewed as simply a task of mere survival. The current environment is so rife with fear, and patently incompetent that no one can really reach their potential. This isn’t a conclusion I like reaching, but the evidence seems overwhelming. Fear and mistrust have led to overarching control issues that remove any degree of personal control for achievement, or at least control while staying inside the rules. If one is willing to completely ignore the rules, success can be had. If one plays by the rules, success is absolutely impossible. The rules of the game are written to avoid all of the acts necessary for success because these involve risk and danger. Fundamental to success is trust, and trusting someone is beyond our collective ken.

The purpose of life is to contribute in some way to making things better.

― Robert F. Kennedy

 

Leadership is fundamentally about credibility.

― Rick Crossland

Under the best of circumstances we would like to confidently project credibility for the modeling and simulation we do. Under the worst of circumstances we would have confidence in modeling and simulation without credibility. This is common. Quite often the confidence is the product of arrogance or ignorance instead of humility and knowledge. This always manifests itself with a lack of questioning in the execution of work. Both of these issues are profoundly difficult to deal with and potentially fatal to meaningful impact of modeling and simulation. These issues are seen quite frequently. Environments with weak peer review contribute to allowing confidence with credibility to persist. The biggest part of the problem is a lack of pragmatic acceptance of modeling and simulation’s intrinsic limitations. Instead we have inflated promises and expectations delivered by over confidence and personality rather than hard nosed technical work.

When confidence and credibility are both in evidence, modeling and simulation is empowered to be impactful. It will be used appropriately with deference to what is and is not possible and known. When modeling and simulation is executed with excellence and professionalism along with hard-nosed assessment of uncertainties, using comprehensive verification and validation, the confidence is well grounded in evidence. If someone questions a simulations result, answers can be provided with well-vetted evidence. This produces confidence in the results because questions are engaged actively. In addition the limitations of the credibility are well established, and confidently be explained. Ultimately, credibility is a deeply evidence-based exercise. Properly executed and delivered, the degree of credibility depends on honest assessment and complete articulation of the basis and limits of the modeling.

When you distort the truth, you weaken your credibility.

― Frank Sonnenberg

One of the dangers of hard-nosed assessment is the tendency for those engaged in it to lose confidence in the work. Those who aggressively pursue credibility assessment tend to be cynics and doubters. They are prone to pessimism. They usually project doubt and focus on limitations of the modeling instead of confidence where it may be used. One of the hardest tricks of credibility assessment is pairing excellence in the execution of the work with an appropriate projection of confidence. The result is a mixed message where confidence is projected without credibility, and credibility is projected without confidence. Neither serves the purpose of progress in the impact of modeling and simulation.

One of the major sins of over-confidence is flawed or unexamined assumptions. This can be articulated as “unknown knowns” in the famously incomplete taxonomy forwarded by Donald Rumsfeld in his infamous quote. He didn’t state this part of the issue even though it was the fatal flaw in the logic of the Iraqi war in the aftermath of 9/11. There were basic assumptions about Hussein’s regime in Iraq that were utterly false, and these skewed the intelligence assessment leading to war. They only looked at information that supported the conclusions they had already drawn or wanted to be true. The same faulty assumptions are always present in modeling. Far too many simulation professionals ignore the foundational and unfounded assumptions in their work. In many cases assumptions are employed without thought or question. They are assumptions that the community has made for as long as anyone can remember and simply cannot be questioned. This can include anything from the equations solved, to the various modeling paradigms applied as a matter of course. Usually these are unquestioned and completely unexamined for validity in most credibility assessments.

This is an immensely tricky thing to execute. The standard assumptions are essential to managing complexity and making progress. That said, it is a remarkably difficult and important task to detect when the assumptions become limiting. More succinctly put, the limitations of the standard assumptions need to be thought-through and tested. Usually these assumptions can only be tested through removing everything else from the field and doing very hard work. It is so much easier to simply stay the course and make standard assumptions. In many cases the models have been significantly calibrated to match existing data, and new experiments or significantly more accurate measurements are needed to overturn or expose modeling limitations. Moreover the standard assumptions are usually unquestioned by peers. Questions are often met with ridicule. A deeply questioning assessment requires bravery and fortitude usually completely lacking from working scientists and utterly unsupported by our institutions.

Another manner for all of this to unfold is unwarranted confidence. Often this is couched in the form of arrogant perspectives where the proof of credibility is driven by personality. This proof by authority is incredibly common and troubling to dislodge. In many cases personal relationships to consumers of simulations are used to provide confidence. People are entrusted with the credibility and learn how to give their customer what they want. Credibility by personality is cheap and requires so much less work plus it doesn’t raise any pesky doubts. This circumstance creates an equilibrium that is often immune to scientific examination. It is easier to bullshit the consumers of modeling and simulation results than level with them about the true quality of the work.

The credibility of the teller is the ultimate test of the truth of a proposition.

― Neil Postman

More often than not honest and technically deep peer review is avoided like a plague. If it is imposed on those practicing this form of credibility, the defense of simulations takes the personal form of attacking the peer reviewers themselves. This sort of confidence is a cancer on quality and undermines any progress. It is a systematic threat to excellence in simulation, and must be controlled. It is dangerous because it is effective in providing support for modeling and simulation along with the appearance of real World impact.

One of the biggest threats to credibility is the generation of the lack of confidence honesty has. Engaging deeply and honestly in assessment of credibility is excellent at undermining confidence. Almost invariably the accumulation of evidence regarding credibility endows the recipients of this knowledge with doubt. These doubts are healthy and often the most confident people are utterly ignorant of the shortcomings. The accumulation of evidence regarding the credibility should have a benefit for the confidence in how simulation is used. This is a problem when those selling simulation oversell what it can do. The promise of simulation has been touted widely as transformative. The problem with modeling and simulation is its tangency to reality. The credibility of simulations is grounded by reality, but the uncertainty comes from both modeling, but also the measured and sensed uncertainty with our knowledge of reality.

The dynamic and tension with confidence and credibility should be deeply examined. When confidence is present without evidence, people should be deeply suspicious. A strong culture of (independent) peer review is an antidote to this. Too often these days the peer review is heavily polluted by implicit conflicts of interest. The honesty of peer review is hampered by an unwillingness to deal with problems particularly with respect to modification of the expectations. Invariably modeling and simulation has been oversold and any assessment will provide bad news. In today’s World we see a lot of bad news rejected, or repackaged (spun) to sound like good news. We are in the midst of a broader crisis of credibility with respect to information (i.e. fake news), so the issues with modeling and simulation shouldn’t be too surprising. We would all be well served by a different perspective and approach to this. The starting point is a re-centering of expectations, but so much money has been spent using grossly inflated claims.

Belief gives knowledge credibility.

― Steven Redhead

So what should we expect from modeling and simulation?

Modeling and simulation is a part of the scientific process and subject to its limits and rules. There is nothing magic about simulation that unleashes modeling from its normal limitations. The difference that simulation makes is the ability to remove the limitations of analytical model solution. Far more elaborate and accurate modeling decisions are available, but carry other difficulties due to the approximate nature of numerical solutions. The tug-of-war intellectually is the balance between modeling flexibility, nonlinearity and generality with effects of numerical solution. The bottom line is the necessity of assessing the uncertainties that arise from these realities. Nothing releases the modeling from its fundamental connection to validity grounded in real world observations. One of the key things to recognize is that models are limited and approximate in and of themselves. Models are wrong, and under a sufficiently resolved examination will be invalid. For this reason an infinitely powerful computer will ultimately be useless because the model will become invalid at some resolution. Ultimately progress in modeling and simulation is based on improving the model. This fact is ignored by computational science today and will result wasting valuable time, effort and money chasing quality that is impossible to achieve.

Bullshit is a greater enemy of the truth than lies are.

—Harry Frankfurt

In principle the issue of credibility and confidence in modeling and simulation should be based on evidence. Ideally this evidence should be quantitative with key indicators of its quality included. Ideally, the presence of the evidence should bolster credibility. Instead, paradoxically, evidence associated with the credibility of modeling and simulation seems to undermine credibility. This is a strong indicator that claims about the predictive power of modeling and simulation has been over-stated. This is a nice way of saying this is usually a sign that the quality is actually complete bullshit! We can move a long way toward better practice by simply recalibrating our expectations about what we can and can’t predict. We should be in a state where greater knowledge about the quality, errors and uncertainty in modeling and simulation work improves our confidence.

If you can’t dazzle them with brilliance, baffle them with bullshit!

– W.C. Fields

Part of the issue is the tendency for the consumers of modeling and simulation work to not demand evidence to support confidence. This evidence should always be present and available for scrutiny. If claims of predictive power are made without evidence, the default condition should be suspicion. The various sources of error and uncertainty should be drawn out, and quantified. There should be estimates based on concrete evidence for the value of uncertainty for all sources. Any uncertainty that is declared to be zero or negligible must have very specific evidence to support this assertion. Even more important any claims of this nature should receive focused and heavy scrutiny because they are likely to be based on wishful thinking, and often lack any evidentiary basis.

One of the issues of increasing gravity in this entire enterprise is the consumption of results using modeling and simulation by people unqualified to judge the quality of the work. The whole enterprise is judged to be extremely technical and complex. This inhibits those using the results from asking key questions regarding the quality of the work. With the people producing modeling and simulation results largely driven by money rather than technical excellence, we have the recipe for disaster. Increasingly, false confidence accompanies results and snows the naïve consumers into accepting the work. Often the consumers of computational results don’t know what questions to ask. We are left with quality being determined more by flashy graphics and claims about massive computer use than any evidence of prediction. This whole cycle perpetuates an attitude that starts to allow viewing reality as more of a video game and less like a valid scientific enterprise. Over inflated claims of capability are met with money to provide more flashy graphics and quality without evidence. We are left with a field that has vastly over-promised and provided the recipe for disaster.

We now live in a world where counter-intuitive bullshitting is valorized, where the pose of argument is more important than the actual pursuit of truth, where clever answers take precedence over profound questions.

― Ta-Nahisi Coates