I have always found it quaint and rather touching that there is a movement [Libertarians] in the US that thinks Americans are not yet selfish enough.

― Christopher Hitchens

The irrational fear of Ebola has thrust the competence of our government into the spotlight. While some conservative voices would point at the failing of government, I believe their aim is both spot on, and completely wrong. We don’t have a failure of government, we have a failing of governance both private and public. The problems with Ebola are exemplars of incompetence from both government and business with both contributing greatly to the debacle in Dallas.

The greater issue is the general crisis in governance in our country. No one seems to be able to do anything right. Government is ineffective and wasteful. Business is amoral and unethical. Neither should be acceptable. The only thing we are doing with any competence is directing more and more of our societal wealth into the hands of a very select few. This is being done in an intrinsically amoral and unethical manner despite its explicit legality since the laws are basically for sale.

It might be nice if the key issue in politics were associated with fixing our society-wide incompetence. We need competence and effective governance from both private and public entities. I would argue that the problem is an unhealthy focus on the individual rather than the overall society. The narrow definition of success associated with the combination of short-term gains and organizational locality are making every decision tactical. This tactical decision-making benefits very few and leads to outcomes that hurt society at the large scale.

In business this produces choices that give shareholders the option of cashing out while destroying jobs, and the future of companies. In government this looks like buck passing and the CYA culture. Together they equal the web of mistakes that made the Dallas Ebola case so much worse. Make no mistake this case is the combination of profit focused medicine coupled with a lack of proper government execution. For example the profit motive is one of the main reasons we don’t have more effective medicines for treating diseases like Ebola. There is little or no profit to made there despite its potential importance to society or its destructive potential.  The core problem is a lack of outrage about the overall lack of competence in governance. This is the thing we should be fixing and it is a completely bipartisan problem.

We should be demand competent thoughtful governance from both the private and public sectors. The outcomes need to balance the good of the individual and society as a whole. We need to explicitly reject the governance that only benefits a precious few. In the long run a more balanced approach will lead to a far better future for everyone including those few who take nearly all the benefits today.

Selfishness and greed, individual or national, cause most of our troubles.

― Harry S. Truman

 Simplicity is the ultimate sophistication.

― Leonardo da Vinci

Life is really simple, but we insist on making it complicated.

― Confucius

V&V and UQ are often described by detractors as being too complex. It certainly can be, but it doesn’t have to be. In keeping with all the brilliant advise quoted here, I’m going to offer simple definitions for the main components of the practice. Each can be posed as a question we seek to answer.

• Verification: (1) Do more computing resources yield better answers? (2) Is my model implemented correctly?
• Validation: Does my model represent reality?
• Uncertainty Quantification: How much different could my answers reasonably be?
• Sensitivity Analysis: What variables do my answers most depend upon?

The downside is the failure to address a host of important technical details, but the simple definitions provide the core of this important topic.  What do you thinK?

Our life is frittered away by detail. Simplify, simplify.

― Henry David Thoreau

Any darn fool can make something complex; it takes a genius to make something simple.

― Pete Seeger

I read a lot. Technical papers. Blogs. You name it. The other day I came across an article that didn’t grab me immediately, but I soldiered on, and deep into the article (http://pchiusano.github.io/2014-10-13/worseisworse.html, I mentioned it yesterday where it describes the issues with applied mathematics) a thought arose in me, “this is some good shit!” The concepts applied so much more broadly than the original and primary focus on software, but to broad swaths of science, technology, business and the human existence in general.

The recent blog post rightly focused on the problems with culture and a bit more commentary might be useful. The core of the problem is one of local optimization. One can choose a solution that is optimal for one’s self or a small group that has awful consequences more broadly. If the implicit or explicit reward system isn’t carefully constructed and the consideration of the global consequences are ignored, something comfortable, but ultimately awful will be allowed to persist as a solution. For software this is common because of its niche status even today. For most organizations a legacy system provides value today and they aren’t willing to pay or wait for a better solution. This is part of essence of “worse is better”. It is part of the reason that the status quo always has a “home field advantage”.

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

George Bernard Shaw

At a deeper level the issue is associated with the notion of winner and losers in any resource battle. While the current economy is demonstrably worse for a vast majority of Americans (or Westerners), it is much better for a select cadre of the wealthiest. These wealthy are powerful and work to influence the gears of politics and power to maintain this status quo. It is difficult to move toward a different system when those with true power oppose it. This is in spite of a general conclusion that a more equitable system that favored a much larger segment of the population would actually result in more for most of the wealthy too. Decisions favor the incumbent. It is always more clear to defend what you already have rather than what you might have.

There are three classes of men; the retrograde, the stationary and the progressive.

― Johann Kaspar Lavater

These forces are always working against progress. Usually the thing that represents progress (a new language, new code, new theory…) is actually lower in performance than the incumbent, which has been optimized (or calibrated). Those who are not invested in the progress will usually choose the status quo for completely rational reasons including its performance, and the relative comfort of the known product. Thus for many, if not most, worse is really better (or easier). If the system is not carefully designed to blunt this outcome, progress will be especially painful. When the system is designed to stop progress, progress is almost impossible.

Better never means better for everyone… It always means worse, for some.

― Margaret Atwood

 There can be no progress without head-on confrontation.

― Christopher Hitchens

For reference there is a Wikipedia entry, and some reflections on Gabriel’s original essay:

http://en.wikipedia.org/wiki/Worse_is_better

http://dreamsongs.com/WorseIsBetter.html

I work with a lot of mathematicians, applied mathematicians to be precise. A lot of the time I ponder the point of their work. Is the importance of the work the beauty and knowledge of math itself, or the utility of the work for practical purposes? My sense is that the “applied” in applied math pushes the balance toward utility. Too often the utility in the work being sold as applied math
today is almost impossible to divine. This is the rub. It ends up being the same dynamic as pure versus applied research. How applied, does applied math need to be to be applied math?

 Physicists have come to realize that mathematics, when used with sufficient care, is a proven pathway to truth.

― Brian Greene,

We had a talk at work earlier in the week that brought these issues into focus. A relatively well-known and successful professor came for a visit and gave a research seminar on his work. On the face of it, the talk looked interesting and topical. This rapidly faded when the talk unfolded for a very simple reason. The professor was limiting discussion to where he could prove results. If the flow he was studying became too energetic (too high a Reynolds number, or its equivalent, the proofs couldn’t be constructed). As a result the work had limited applicability to investigations because results can’t be proven for most applied problems. Most applied problems
have too high a Reynolds number to be amenable to the techniques he was applying. Furthermore these higher Reynolds number flows are the challenge applications and computing is most paced by. Despite the importance of the applications, the applied math isn’t being applied. Arrrgggg!

 Mathematics is the art of explanation.

― Paul Lockhart

Is it really applied math, if I can’t apply to the results to things we care about?

My attitude is that I will roll up my sleeves and work to understand the math if the results can be shown to apply to situations I care about. If the math avoids the situations of interest, can’t be demonstrated, or simply doesn’t demonstrate itself, I won’t make the effort because the mathematician hasn’t done their part to meet me half way. What should happen when we have important applied cases where results can’t be proven? Should the effort in math be given to expand the grasp of mathematics to handle these cases? Or should mathematicians work on proving weaker bounds or results?

Deep in the human unconscious is a pervasive need for a logical universe that makes sense. But the real universe is always one step beyond logic.

― Frank Herbert

My opinion is that proving results on simple problems of little relevance is basically useless insofar as applied math is concerned. Nothing is wrong with providing a sliding scale where the strength of the guarantees changes with problem difficulty. The important thing is to provide the proper mathematical grounding for the problems people solve. If the math simply doesn’t exist for important problems, then say so and set about to improve the capacity of math to provide results.

The important problems will continue to be solved. The issue is that applied math won’t be participating. The retreat of applied math from relevance has been palpable for the past two decades. Once upon a time applied math was a key partner in computational, modeling and physics progress. This role has shrunk over time due to an unwillingness to get their hands dirty. There also seems to be a desire to look more like pure math, which leads to a lack of demonstration.

This leaves me with the question: if applied math can’t be applied? Is it really applied math?

I’m an easy sell for the community; I know that applied math can contribute mightily to progress. All that is needed is for the applied mathematicians to make an earnest effort to work on problems that matter. In other words solve the problems that are important, not the ones that are easy to solve. Demonstrate that your results actually mean something on real problems. Deal directly with problems that are “dirty” rather than simplify real problems until they lose connection with reality.

We all die. The goal isn’t to live forever, the goal is to create something that will.

― Chuck Palahniuk

Today applied math is optimized locally, but globally it is in crisis. This is yet another instance of “Worse is Better”: http://pchiusano.github.io/2014-10-13/worseisworse.html . We’ve allowed this to happen. The excuse that people need to publish for professional success is hurting the field, and is largely a self-imposed condition. What is the point of success if the publications mean little to the development of technology?

The question to ask is whether it is “the mathematics of applications” or the “using math on applications”. There is a difference. Today it is largely the later, instead it needs to be doing math that impacts applications.

Since the mathematicians have invaded the theory of relativity I do not understand it myself any more.

― Albert Einstein

Nothing limits you like not knowing your limitations.

― Tom Hayes

  We spend too much time showing how well things work, and not nearly enough time figuring out where they don’t. Progress is there to be made by systematically exploring the limits of applicability for methods rather than show them off on cream-puff problems. Despite this, the reward system is hopelessly tilted toward the demonstration of methods through relatively trivial tests.

I mean that gods do not limit men. Men limit men.

― Tom Robbins

Exposition in science is quite success focused much to the detriment of everyone. Failures are not tolerated much less expressed in many structured ways. Numerical methods are no different. In writing, people show demonstrations of their methods working, but rarely how the methods fail. This is quite unfortunate because it is limiting progress. For a numerical method people will typically simply solve a few standard test problems show results and call it a day. Rarely does anyone discuss how things fall apart or describe what the limitations on a methodology are.

Only those who dare to fail greatly can ever achieve greatly.

― Robert F. Kennedy

I have always found that the best way to make methods better is to continually break them. I will routinely torture methods to the breaking point fully knowing that “breaking” is itself complex. Methods break in many ways starting with a failure to converge to the “right” solution, or converge at the right rate, followed by a failure to converge to a solution, followed by a loss of stability. The improvement comes from understanding the cause of the failure, and changing the method to expand the range where a better outcome can be achieved. The process of failure is often demonstrably Edisonian, and the challenge is to provide the scientific, structural explanation for the failure to blunt the purely empirical edge. This tension is how progress and knowledge grow, and failure is the engine.

I have not failed. I’ve just found 10,000 ways that won’t work.

― Thomas A. Edison

Failures are the engine of success. This is widely known and acknowledged, and despite this failure is not encouraged because of superficial fears regarding perception. As a result we have come to accept mediocrity as success, losing almost any conception of what true success looks like. Our success is almost by fiat rather than achievement. We will ultimately pay the price of this orgy of over-evaluation unless something changes in how we view things.

Not knowing that we learn from our mistakes and failures is perhaps the biggest one of them all.

Have no fear of perfection – you’ll never reach it.

― Salvador Dalí

I wrote this in a notebook a few weeks ago and it would be a good idea to explain myself. The lack of certainty and chaos in the Universe is obvious, yet so much of our modeling is based on deterministic thinking. This legacy of Newton pollutes so much of
our thinking that it is probably one of the greatest impediments to progress today. It is an “unknown known” that I wrote about a couple of days ago. I’m not going to go down the philosophical rabbit hold of “free will” or any of that. My point-of-view that this sort of discussion is fairly pointless, for all practical purposes we can never know our initial or boundary conditions well enough to treat our World as deterministic.

The assumption of an absolute determinism is the essential foundation of every scientific enquiry.

― Max Planck

It is impossible to trap modern physics into predicting anything with perfect determinism because it deals with probabilities from the outset.

― Arthur Stanley Eddington
Newton’s laws were revelation, but also woefully incomplete. They spawned a revolution in science that we benefit from today, but their power was not fully realized until many revisions were made. Nonetheless, many scientists are still enthralled by the beauty and purity of his perfects laws. Examples abound and perhaps most acutely with the Navier-Stokes equations. I regard the Clay prize,

http://www.claymath.org/millenium-problems/navier–stokes-equation ,

associated with the proof of existence for the 3-D Navier-Stokes equations to be outright foolishness. It is the enshrinement of mathematics as divorced from reality. The reason is several fold: the equations as given are patently unphysical, and singularities are a relic of the same Newtonian thinking that defines the Universe as a clock simply moving forward with complete determinism.

This isn’t to say that the Navier-Stokes equations aren’t useful as approximations or for modeling under some circumstances, they demonstrably are. The problem is that they have taken on all too great a meaning, and we are asking questions of them they shouldn’t be answering. The specific unphysical aspect of the equations is the divergence free velocity field, which implies infinite sound speeds and divorces the equations from thermodynamics. This is strike one.

Strike two is the notion of needing a singularity to define its characteristic dissipative nature. This is a bit of a physical Mobius strip where the equations are simply showing their limits of applicability. By removing thermodynamics and sound waves from the system, the natural nonlinear mechanism for singularities goes out too. The observations of flow in nature indicate the presence of dissipation without specific dependence on the value for the physical viscosity, i.e., evidence of a singularity. The result is an enormous waste of time and energy.

… Nature almost surely operates by combining chance with necessity, randomness with determinism…

― Eric Chaisson

This is only one instance where determinism is hurting science. In general the modeling of the World or Universe proceeds along lines that implicitly expect determinism despite all the evidence to the contrary. A lot of the time the variation in behavior of a system is relatively small, or the nature of variability is reliable and can be captured in the constitutive laws. A problem that we are increasingly facing is the solution of systems where length and time scales where the variability exists are coming into the resolution of our codes. Continuing to promote the fallacy that the system is deterministic is simply wrong on the face of it.

In some cases the lack of deterministic evolution is obvious like with weather. There some of the issues are being attacked in a fairly head on manner. In other cases like continuum mechanics, the deterministic mindset is so pervasive that the old ways continue unabated. A bit of multiscale thinking is creeping in, but itself is polluted by determinism. Our models are getting to the point where grain structure and material structure can be directly modeling, yet we persist in using models defined when length and time scales were vastly larger. Our approach needs to change for progress to be made.

The uncertainty principle signaled an end to Laplace’s dream of a theory of science, a model of the universe that would be completely deterministic. We certainly cannot predict future events exactly if we cannot even measure the present state of the universe precisely!

We could still imagine that there is a set of laws that determine events completely for some supernatural being who, unlike us, could observe the present state of the universe without disturbing it. However, such models of the universe are not of much interest to us ordinary mortals. It seems better to employ the principle of economy known as Occam’s razor and cut out all the features of the theory that cannot be observed.

― Stephen Hawking

When we change the way we communicate, we change society

― Clay Shirky

Over the weekend a good friend of my wife (her best friend from childhood) was going through a box of mementos and came across letters my wife wrote her over thirty years ago while they were in college. One of the letters was written shortly after my wife and I started dating. In the letter she expressed herself honestly to her friend, and the results were stunning. My reaction to reading it was the same as my wife, an outpouring of emotion in seeing her feelings about me so earnestly expressed. It was remarkable, and incredibly touching. It was like looking back in time and seeing yourself through today’s eyes.

This morning I began to wonder could this happen to a couple starting out today, thirty years from now. The sort of letter my wife wrote doesn’t get written today. We have Facebook, Twitter, instant messaging and e-mail. We don’t write letters with the expectation that no answer will come for days to weeks. Because communications like these can be so easily and cavalierly forwarded or seen by others, the honesty and emotion is usually lacking. As such, the communications are a bit less intense or memorable. Perhaps we aren’t as honest with others or ourselves about things.

Current communications also don’t have the staying power of the letter. They don’t get saved. I can’t lay my hands on emails much older than six or seven years back, and usually less. I wonder how much of history is getting lost in the ephemeral way we communicate. It is worth considering. Generally, I am unabashed in my enthusiasm about technology, but this episode gave me pause. Maybe we don’t even realize what we’ve lost. We have gained a lot, but we may have lost a bit of our soul.

Reports that say that something hasn’t happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns — the ones we don’t know we don’t know. And if one looks throughout the history of our country and other free countries, it is the latter category that tends to be the difficult ones.

Donald Rumsfeld

http://en.wikipedia.org/wiki/There_are_known_knowns

Donald Rumsfeld made this marvelous quote in a remarkably cynical way, as a way to avoid answering a question. It has been a source of much discussion, a recent documentary

http://en.wikipedia.org/wiki/The_Unknown_Known

and the most obvious cultural touchstone for uncertainty quantification. He also forgot the most important category, the unknown known, and the axiomatic things that we don’t even question or think about. For Rumsfeld it was the unknown knowns that more than anything drove us to war and influenced decisions in ways that we never fully acknowledged. All of us have this sort of blind side, the things that drive our decisions that we don’t even think about.

So what our some of the unknown knowns for that I deal with?

For example at Sandia the Finite Element Method is an unknown known. It is applied without thought or debate, it is just assumed to be the method of choice. There is
no discussion or thought with the choice as it is applied axiomatically. Even when non-finite element methods are used, they are called a finite element discretization as a way to smooth the way to acceptance.

I’ve noticed that our viewpoint on modeling in the continuum hypothesis is similarly axiomatic. In many ways it is remarkable that we continue to solve problems in exactly the same philosophical way that Von Neumann envisioned even though computers have advanced by a factor of more than quadrillion in power. In some cases we don’t include details of physics that now come into view such as grain structure, texture, anisotropic properties, etc. In hydrocodes we simply “paint” materials into regions and apply homogeneous properties even though the materials are definitely heterogeneous at the scale of the mesh. Generally speaking, the changes necessary to model things correctly is barely on the technical agenda. These features are more prevalent in
weather and climate where the differences in the physics are more obvious. We know that the asymptotics differ and the equations need to change. In continuum mechanics this is beginning to dawn on people too.

I suppose it is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail.

― Abraham Maslow

Our society has many of its own axioms, such as “American exceptionalism” which is either axiomatically good or bad depending on who you talk to. The view of socialism, free enterprise, and liberalism all fall prey to the unknown known. It has become the prevalent way of managing complexity and simply assuming the answer is easier than thinking about the inherent complexity of things. This thought process is the heart of racism, sexism, gay bashing and a host of societies greatest ills. By simply assuming certain things to be true without question makes life easy, but it also allows people to do terrible things with complete justification. This brings us back to Rumsfeld.

Your assumptions are your windows on the world. Scrub them off every once in a while, or the light won’t come in.

― Isaac Asimov

There is nothing quite so useless as doing with great efficiency something that should not be done at all.

– Peter Drucker

In today’s America it is axiomatic that the concept that applying corporate principles to organizational governance is good and appropriate. It is applied without question and used to justify all manner of mismanagement. The reality is that corporate governance principles are somewhere between inappropriate to completely incompetent for managing research institutions. I’d argue that they are ruining the economy itself because the current “principles” are oriented toward the benefit of the few people at the top of the food chain.

Doing the right thing is more important than doing the thing right.

– Peter Drucker

The cornerstone of corporate governance is the maximization of shareholder value. Almost every business decision flows from the application of this principle. This principle greatly benefits a select few and often costs other stakeholders greatly. Over time, the shareholder class and the management of businesses have merged into the same thing. Business is now managed to enrich its management. It is basic conflict of interest, and society as a whole is paying the price. The business principles being used are bad for the businesses as they are used as sources of money that is systematically siphoned off to compensate “shareholders”.

All of this is at the cost of the long-term health of the companies, the jobs for the employees and the communities they are in. The shareholders don’t care because they have already had their payday.

 Management is doing things right. Leadership is doing the right things

-Peter Drucker

The consequence is that we are over-managed and under-led. These principles are slowly destroying our National system of research laboratories. Whether it is the department of energy or defense, or NASA or NOAA, we are strangling our research through systematic misapplication of management principles that only benefit a few. Take community service like the United Way as an example. Institutions will manage an employee-giving program and then have the institution take credit for the good.

All the while they systematically suppress the employees wages and increase executive compensation. They benchmark themselves to corporations to justify everything, and no one even blinks.

I worry that this process will continue until we have a crisis. Our destruction of our research capability in the name of applying business principles may finally end with disaster. Our dominance of science and research is ending. Europe and China are overtaking the United States. Our government seems to be in denial of this, but it is more obvious all the time. A large part of the blame can be laid at the feet of the misapplication of corporate governance to research institutions.

It matters not how a man dies, but how he lives.