La grande erreur de l’économie.

English: Graph illustrating the Brander Spence...
English: Graph illustrating the Brander Spencer model (Photo credit: Wikipedia)

Avant que j’écrive cet article, il faut que j’excuse mon français. J’ai voulu pratiquer mon français en écrivant dans mon blogue pendant de nombreuses années, mais je n’ai pas eu la confiance d’écrire sur les sujets que j’aime en français. Ceci est mon premier essai. Cela dit, on y va.

Présentement, je lis un livre de Robert Ulanowicz, «The Third Window». Cette un livre sur les problèmes de science  écologique. Spécifiquement les nombreuses tentatives d’appliquer le réductionnisme de physiques sur le terrain. L’hypothèse de Ulanowicz’s est que la complexité inhérente dans le terrain rend ce programme impossible parce qu’une seule action peut changer tout le mécanisme dans l’objet d’étude. Une autre structure pour l’étude est requise, ou au moins c’est impératif à reconnaître les limitations extrêmes des modèles.

Je pense que c’est la même chose en économie, mais je pense aussi que beaucoup, si pas toutes, les personnes dans ce terrain ne considèrent pas ce problème. Ils sont trop obsédés par l’aide d’un programme de recherche comme celui des physiques – un programme basé sur le réductionnisme.

Ce programme est condamné à l’échec.

En finance, Nassim Taleb discute l’ idée du «Black Swan». Bien qu’il soit possible de définir une modèle où un grand nombre de traits observés existent, un seul incident peut changer l’ensemble du mécanisme. Alors, le modèle est complètement faux. C’est parce que le modèles comme ceux des physiques exigent que le système ait une distribution de probabilité simple – par exemple, une distribution de courbe en cloche.

C’est un château de cartes. Ce sera toujours un château de cartes.

Par exemple, si ce problème arrive en physique. Ce serait comme s’il y avait toujours une particule qui dévaste tout, et les particules arrive tout le temps. L’intégralité de l’étude de la physique devrait être réécrite toutes le quelques semaines. Ce serait inutile. Personne ne perdrait son temps à l’utiliser.

Mais, en économie, les décisions majeurs sont prises régulièrement avec ces modèles. Des décisions qui affectent des millions au quotidien. La science n’est pas une science. C’est une idéologie avec une mythologie construite à partir de fausses prémisses.

Je pense qui c’est le temps que ces décisions soient effectuées sans cette fausse science mais avec la reconnaissance que les décisions soient idéologiques. Les décisions le sont parce que les politiciens croient c’est la meilleure chose à faire. Cessons d’essayer de prétendre qu’il n y a aucune science derrière les décisions. Les décisions sont toutes idéologiques.

C’est le mensonge qui anime nos mauvaises décisions politiques.

C’est pourquoi une grande partie du monde doit avoir de nombreux problèmes.

Ou alors, il faut construire une nouvelle science de l’économie. Qu’on ne la fonde pas sur le culte de cargo du réductionnisme, mais sur la réalité que nous ne pourrons jamais comprendre comment fonctionne l’économie, sauf dans de rare circonstances simples.

Lorsqu’on n’a pas besoin d’un modèle de l’économie.

Some translation needed (applications of immix)

Symbol of Confusion
Symbol of Confusion (Photo credit: Wikipedia)

A big problem I’ve encountered in business is the widening chasm between sales, marketing and IBM-style management folks and the new group of technical experts coming up. I’ve been in rooms where the marketing people have great ideas about a product and the technical people simply cannot understand or comprehend what they are saying or, worse, why it is a good methodology to sell a product. To them, it’s the technical structure of the product, the spreadsheets and data, not the human or “mushy” interaction with the wetware on the other side.

There are times I wonder if part of the reason techies spend so much time on futurism is the hope that by removing the wetware entirely, the system becomes much simpler.

However, it goes the other way around. Techies will describe what they are doing in terms that to them are simple, but to the sales and marketing guys are essentially another language. Many smart sales and management folks will usually retort with “ok, let’s pretend I’m an idiot, please explain this to me in language I understand.” I surprisingly polite, if somewhat demeaning way to ask for clarification. The issue though is when the techie “dumbs it down,” they resort to either simpler technological terminology, defeating the whole point of why the prototype they built is cool, or they change the terminology to a different field that they have less respect for (This is more common than you’d think.)

I confess, I’ve done both of the above. I’ve put on my sales, marketing and management cap and found it excruciatingly difficult to explain to a techie why the direction they are going won’t work. Why to sell the produce we need to do something more palatable, more refined. Why, at the end of the day, we need to have a product that actually works rather than the potential for an awesome product eventually. This is something I want to fix eventually, since if I put on my techie hat, I fall into the same holes as them. (Whoo, that’s cool, do that, don’t worry if it doesn’t work…)

I’ve put on my techie hat, went into a sales meeting and found myself discussing the more complex points of software engineering on a clustered system to an individual who only wanted to know why the algorithms on mutual funds were taking longer to calculate than he wanted.

Yet, ironically I’ve found when I’m not the one communicating, it has put me into an interesting situation. I can read over a paper on advanced clustering algorithms and explain to a manager of a small company why this is useful for their primary software product. I’ve also found myself in a technical development meeting explaining to techies that the sales manager is not demanding an entire rewrite, but simply a new field on a single screen.

So, while this is important and I enjoy playing this role. I realized that this is ironically what immix has become. The internet is full of 100s of APIs and organizations have likely thousands if not millions of different systems that have their own DBs, no APIs, no clean way to link to the old database and combine it with new systems in a clean fashion.

While more standardization of APIs is useful, that doesn’t give many businesses any ROI since they don’t want to throw out all of their existing work.

immix has become for many organizations an interesting middle man. It allows the various systems to communicate to it in their own way, and then through module building communicates what is necessary to other systems (including the nefarious wetware I mentioned above.)

It makes the software and hardware talk together. It creates a social network for humans, hardware and software.

Carrier to Noise Ratio of a QPSK Signal
Carrier to Noise Ratio of a QPSK Signal (Photo credit: Wikipedia)

The realization I had is that over the last 5 years we’ve encapsulated in software what I’ve been doing in business for a long time. we’ve built a technical translation system that allows normally incompatible systems to understand what they are doing and make more intelligent solutions, and this is important. The internet is overwhelmed with people talking to the wind, and many of the time with good ideas when you can understand the underlying logic. Adding things to the mix will just make it even more confusing, adding noise and not signal. Not because there isn’t signal, but because the things are all communicating slightly differently.

However, by having a centralizing IoT framework that repolarizes those signals all into the same frame, you can actually start to make sense of it all.

I’ve always felt like a jack of all trades because of my varied knowledge and personally worried that it put me at a disadvantage as I needed to read so much more to get the depth I wanted in all of the fields.

However, now it gives me an advantage because I can talk the various languages needed to build good businesses, and I can see how to build a framework that does the same thing electronically.

Maybe I finally found my niche.

Some translation needed.


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Texas Sharpshooter fallacy made large

Academia has a fascinating issue I’ve been pondering about recently. In essence, the fact that almost all journals have a clear and obvious bias towards positive results, there is almost a guaranteed texas sharpshooter fallacy that will occur over time when many many papers are written.

From wikipedia:

The Texas sharpshooter fallacy often arises when a person has a large amount of data at their disposal, but only focuses on a small subset of that data. Random chance may give all the elements in that subset some kind of common property (or pair of common properties, when arguing for correlation). If the person fails to account for the likelihood of finding some subset in the large data with some common property strictly by chance alone, that person is likely committing a Texas Sharpshooter fallacy.

Now, I’m not entirely sure if this is the best fallacy to use, but basically it’s based around the idea that given a million monkeys and an infinite amount of time, someone will eventually write Shakespeare. Now, if we ignore all of the negative results, and all of the gibberish and only publish once someone writes Shakespeare, it would seem, at times, as if a monkey left to a certain type of typewriter is more inclined to write Shakespeare.

Don’t get me wrong though, science is explicitly built around the idea that these points would be made public and then eventually proven false by repeated experiments by other individuals. However, with the modern media hyping everything the moment it is published and an overconfidence on anything that is “science” or “published” we have a big problem on our hands.

Yes, evolution is a fact, that’s been around long enough and there is no credible theory that challenges it that I’m willing to say that. In the same sense that I am wiling to say that Maxwell’s Laws are facts and the like.

However, 90% of the new science you keep hearing about… Is probably wrong. Especially psychology and medical science has this flaw (with the sheer number of papers and the need to publish or perish, how could it not.) Yet, we keep going back to that trough. It was published in a peer-reviewed journal, so it must be true, right? The media hypes that red wine is good for you, bad for you, indifferent…

Here’s my theory on this whole matter, not peer-reviewed or published, but at least a functional heuristic. Give it 20 years, or 40 years. Let people challenge the results and see if they actually apply. I wish we could teach people how science (and to be honest any knowledge development) really works. You have an idea, it seems to work for you. You try to figure out why and reproduce it so you can continue to enjoy the benefits. You develop something that seems to work and is reproducable, then you tell people and they try it out.

And 9 times out of 10 they discover that you weren’t quite right.

However, if the idea continues to generate positive results for you, you ignore them and keep using it. If they are right and it starts to fail, you go back and you try again.

To believe that new science is right simply because it’s published is to be as dogmatic as to believe the a religious book is correct simply because someone told you so. Journals (even good journals) are not always right.

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Unsolved (math) problems…

Man, I love unsolved problems in any field of science or philosophy. This does not mean I don’t enjoy reading the elegant solutions or re-derivations of solutions to problems solved long ago (I’m looking at my grad studies Galois Theory prof and his re-derivation of everything in that subject using category theory.) However, there’s something energizing to seeing that not every problem has been solved and that science isn’t perfected.

In fact, nothing sends a chill up my spine more than when an experiment in Physics could potentially disprove a well accepted theory. Every time that has happened historically, the world changed (and usually for the better.)

But, I’m not a physicist and while I enjoy playing with the mathematics of quantum computation, I am a math major historically, and a mathematics buff through and through. Thus, I’m putting out this request to anyone who sees it. I want to know any unsolved problems you know of (beyond the obvious clay mathematics prizes) that you are aware are unsolved. Whether they are simple conjectures from combinatorics, to open questions from long long ago. If you have them, I want to hear them. If only so I have more fun things to play with whenever I get time.

Plus, it’d be pretty spiff to have one page (this blog entry) on the web as a central resource for mathies who are interested in these problems.


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Chaos and Order

In the last 10 years I’ve really come to terms with the discordian idea of creation v. destruction rather than the political reality of chaos v. order. At the end of the day, my concern lies with the idea of creation to help society (and self) rather than destruction. Yet, still it seems everything is frames in the dichotomy of chaos and order.

Chaos and order is necessary for motion or advancement. Without some chaos or movement there would no energy in a system to move it forward. For example, the most perfectly ordered system (mechanically) I can think of is a hunk of metal. It sits there, and until something applies a force to it, it doesn’t move at all. Similarly the most energetic chaotic system I can think of would be something like a bomb, it explodes, there is no predicting what will happen to the individual fragments and the energy is quickly dissipates and becomes useless.

Yet, a car engine is almost exactly those two elements brought into harmony. The hunk of metal (the piston) acts as an enabling constraint for the explosion of the gasoline. This allows work to be drawn from the system. From an ordered constraint, and a chaotic energy source, we get work.

After some thought, it’s easy to arrive at the heuristic that for an independent system that is self-emergent to organize in a “useful” fashion to produce work, it requires chaos in the form of some energy being released, or some normally uncontrollable flow, and it requires order in the form of an enabling constraint to allow for “work” to be drawn from the chaos. In a non-humanistic sense, work commonly just means reproduction of the existing codes/idea in order to produce more of those objects in an effective manner. In an economic sense, it means the production of better and more efficient systems for producing value and wealth.

In a human sense, it means progress.

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