Wednesday, December 15, 2010

Predicting History is Easy: Model Politics as a Game

Prof. Bruce Bueno de Mesquita wants that the world knows he can do the unthinkable. With >90% accuracy he can predict the future. This is what his recent popular science book "The Predictioneers Game" claims. Others strongly contradict his claim.
Because his model is not shown in the popular book, I asked him to point me out the right sources. He kindly answered: 
The ISA paper is scheduled for publication in the journal Conflict Management and Peace Science (CMPS). [...] you might want to read European Community Decision Making, edited by Frans Stokman and me and published by Yale University Press or my short boo[k], Predicting Politics (Ohio State University Press) but these are on the old model. The math and structure of the new model is set out in the CMPS paper that is due out within the next few months.
Let me play a game:
What would it mean if his astonishing predictive power turns out to be true? would it mean we know the state of the world in 20 years? would it mean that your fate is given? would it mean that we will all use his method in business and private life in the future? 
what would it mean if his claim is wrong. he wants to put his academic renown at stake to be invited to talkshows? he don't know he is wrong and will be derided and forgotten? Or is he playing an aggressive game to promote his...
[...] company, Mesquita & Roundell,[1] that specializes in making political and foreign-policy forecasts using an unpublished and proprietary computer model based on game theory and rational choice theory.
The future will tell, because I will read his paper when its published.

Monday, December 6, 2010

Less is more: Braess' Paradox

Like many counterintuitive anomalies, it needs the right combination of conditions to actually pop up in real life; but it has been observed empirically in real transportation networks — including in Seoul, Korea, where the destruction of a six-lane highway to build a public park actually improved travel time into and out of the city (even though traffic volume stayed roughly the same before and after the change)
http://www.cs.cornell.edu/home/kleinber/networks-book/networks-book-ch08.pdf

Dissimnation of a great Technology now easier

The Brunswick Society Newsletter is now online even for nonsubscribers. Sensible decision Brunswickians!
http://www.brunswik.org/newsletters/2010news.pdf

Monday, November 22, 2010

They laught when I said "Influence Diagrams" but when I made better decisions...

I almost forgot them! Influence Diagrams! We have a decision shaping tool at hand. We can do what Paul Meels envisioned. Shaping the qualities of our decision. Let the computer do the number crunch. I will show you my experience with this, have to reiterate over the great book Bayesian Networks and Influence Diagrams, then they will stop laughing.

Friday, October 15, 2010

Clinical vs Statistical Prediction

Got a very old copy of Meehl's "Clinical vs Statistical Prediction" sent over from the US yesterday. The text is as  promising as I expected. There is no real argument for intuition, but speed in decision when you don't have a model at hand.

Tuesday, September 21, 2010

A remarkable point of view: Egon Brunswick's Lens Model

Vienna during the dawn of the 20th century was a remarkable place.
The list of residents - and their ideas - shaping the century is exhaustive.
The most knows: Freud and Hitler.
The known to the many: Edward Bernays, Peter Drucker, Joseph Schumpeter, Karl Popper, Friedrich Hayek, Ludwig Wittgenstein, Kurt Goedel, Artur Schnitzler, Robert Musil,... to mention a few important to me.

The Psychologist Egon Brunswick is a true maverik. Although only a small inner circle is aware of his work, he did some remarkable thinking.
Representative Design
Is a true theory how to to capture reality into your experimental setting
Ecological Validity is a theory how a subject's intepretation relates to real world
Vicarious Function is a true idea how this interpretation goes.
Probabilistic Functionalism is a scientific revolution, that could relieve us from the analytic trap: get rid of simplistic models.
Brunswick Lens Model has shown to predict better than experts the lens model was trained on. Thats a fascinating way: augmented intellect.


I will deepen my Brunswickan knowledge and share it on this blog
Read about current Brunswickian Research on http://www.albany.edu/cpr/brunswik/newsletters/2009news.pdf

Saturday, September 11, 2010

How to search for a lost object

The joke goes, that a drunk searches for lost keys right under the street lightning, because there its easier. But how would a mathematican do it?


John Pina Craven found a lost nuclear bomb  in deep sea.
The method he applied was Bayesian search theory.
In 1866 a US B52 bomber exploded over Spain:
The aircraft and hydrogen bombs fell to earth near the fishing village of Palomares. [...] Three of the weapons were located on land within 24 hours of the accident—two had exploded on impact, spreading contaminated material while a third was found relatively intact in a riverbed. The fourth weapon could not be found despite an intensive search of the area—the only part that was recovered was the parachute tail plate, leading searchers to postulate that the weapon's parachute had deployed, and that the wind had carried it out to sea.

The search for the fourth bomb was carried out by means of a novel mathematical method, Bayesian search theory, led by Dr. John Craven. This method assigns probabilities to individual map grid squares, then updates these as the search progresses. Initial probability input is required for the grid squares, and these probabilities made use of the fact that a local fisherman, Francisco Simó Orts, popularly known since then as "Paco el de la bomba" ("Bomb Frankie"), witnessed the bomb entering the water at a certain location. Orts was contacted by the U.S. Air Force to assist in the search operation.
The method applied in one of the four areas identified as probable target [i]

Sunday, September 5, 2010

Scoring, you doing it wrong



Business Schools all over the world seem to teach scoring methodologies.[i] Douglas W. Hubbard[ii] and L. Anthony Cox[iii] have shown that there are fundamental flaws in their application, thus they are valued by the authors as counterproductive. “All of them, without exception, are borderline or worthless. In practices, they may make many decisions far worse than they would have been using merely unaided judgments.[iv] First I will present the case study of a seminar I attended where their arguments are applied and proven right, second (in a later article) I will present the case of a consumer test, where I propose that the design of scoring led not to “borderline or worthless” results.


[i] This is anecdotal evidence: I encountered the practice frequently when attending seminars, trainings and workshops in the field








Sunday, August 1, 2010

Hair Salon Simulation now under creative commons

So, as told in my last post I tried hard to argue that immeasurables exist,... and failed miserably. Thats a good reason to start a AIE Group at TIS.

I declare my first Excel Model, the Vienna Hair Salon Simulation as licensed under a Creative Commons Attribution 3.0 Unported License.
Creative Commons License
Here the Problem and its Solution rawly traduced via Google Translate:
How many salons there are in Vienna?
I put the following considerations:
  1. There are approximately 1.8 million "Wiener"
  2. Almost all have hair and almost all cut not privately
  3. Viennese cut them every one to two months
  4. The hairdressers work about 220 days a year, but some part-time
  5. Pro Salon work 1-4 Hairdressers
  6. A hairdresser needs 20min to 1h for a haircut
From this I calculate the number of salons. Because the calculation is not just simple add up, I make a Monte Carlo simulation.
The result is that the most likely number of hair saloon is between 0 and 2000.

histogram of the simulation
The dirty truth is that the model tends to favor slightly the 0-200 salons bin. Of course the Garbage-In/ Grabage-Out Principle says you can't look at the details if your model is that rough. So the result is fairly good.

Sunday, July 25, 2010

A Measurement Challenge

Today I postet the following comment to Douglas Hubbards forum:

Mr. Hubbard,

I’ m a Software Developer from Italy with a passion for the ‘uncertainty sciences’ last century gave us so plentiful. I’ve read both your books and I am about to order the second edition of HTMA. In fact I am so intrigued by AIE methodology that I convinced some quantitatively skilled colleagues to set up a workgroup to apply AIE on some relevant problems to us.

I want to say it’s an honor to confront you with a measurement challenge. Let’s start:

The Swiss bank UBS published an article in its ‘UBS investor’s guide’, special edition April 2010, predicting the outcome of the FIFA 2010 Soccer World Cup. http://www.ubs.com/1/e/bank_for_banks/news/topical_stories/edition_10.html

You will agree this is a relevant problem, as the 'uncertainty reduction' on the game’s outcome will give an advantage in sports-betting.

With hindsight, they failed the prediction miserably, claiming:

(1) Brazil is most probable winner – didn’t reach the semis

(2) Germany and Italy likely to go far – true for Germany (3th in Rank) but Italy didn’t survive the first round.

(3) “Spain – favored by many – will likely not do well, and could exit before the semi-final stage” – Spain won the World Cup.

UBS has now an inglorious record of 1 success in 3 attempts - Wordcup 2006 went good, but European Championship 2008 and Wordcup 2010 failed.

I am inclined to argue that you can’t predict the outcome of the game a priori.

1. UBS likely has built a state of the art econometric model but the conclusive verdict about the rightness of the model can only be “it works”. This show: you certainly can make a sound argument about how you measure it, but still failing miserably.

2. But you cannot know if your model is right or you had luck. This is so because the experiment is not repeatable well. The basic dilemma of social sciences: social systems are complex and adaptive. Using a model: the stochastic process is itself complex, if not random. When we cope with induction we can only believe in the stable nature of the stochastic generator. What UBS’ case tells me: there is anecdotal evidence that the underlying principles of “who wins” are not stable. You cannot say if it will work for the next FIFA world championship or not, making it useless.

3. But probably even if you would know the exogenous factors that influence the game, I suspect the endogenous factors in the system are much more important. Making any reasonable forecast before the games started futile.

Mr. Hubbard: can you measure it?

Sincere Regards,

Roland Kofler

Sunday, July 18, 2010

Don't have an opinion, build a model

In medicine as in life we have to distinguish emotions and ratio. This is the hardest task ever. Metaphysics succeeds because it simply discounts the problem. So does post-modernism.
But Paul Meehls does not look away.

The machine decides same or better than the intuition. A well ignored secret since 50 years.
http://www.tc.umn.edu/~pemeehl/167GroveMeehlClinstix.pdf

Sunday, May 9, 2010

Wieviele Friseursalons gibt es in Wien?

Der berühmte Physiker Enrico Fermi war dafür bekannt, dass er aus einfachen Beobachtungen präzise Abschätzungen (nicht nur) physikalischer Phänomene herleiten konnte. So soll er durch wehende Papierschnipsel die Detonationsenergie des ersten Atomversuchs abgeleitet haben. Seine Studenten mussten knifflige Schätzprobleme lösen, wie durch Gedankenexperiment die Anzahl der Klavierstimmer in Chicago ermitteln.
Fasziniert von der Methodik habe ich mich darangemacht mein eigenes "Fermi Problem" zu stellen und zu lösen:
Wieviele Friseursalons gibt es in Wien?
Ich stellte folgende Überlegung an:
  1. Es gibt ca. 1,8 mio Wiener
  2. Fast alle haben genügend Haare und fast alle schneiden sie nicht privat
  3. Sie schneiden sie alle ein bis zwei Monate
  4. Die Friseure arbeiten ca. 220 Tage im Jahr, aber einige Teilzeit
  5. Pro Salon arbeiten 1 bis 4 Friseure
  6. Ein Friseur braucht 20min bis 1h für eine Frisur
Daraus errechne ich mir nicht die minimale mögliche und maximale Anzahl der Salons, denn die Rechnung besteht nicht nur aus simplen aufaddieren, sondern aus mehreren sich beeinflussenden Variablen. Ich mache eine Monte Carlo Simulation.
Der wahrscheinlichste Anzahl der Friseure liegt immer zwischen 1000 und 2000.
Ich schlage im Herold nach und es gibt 1136 eingetragene Friseursalons in Wien.

Zum nachvollziehen habe ich die ganze Simulation auf Google Docs hochgeladen.
Würde mich freuen wenn jemand Fehler findet.


Tuesday, February 9, 2010

Unterdurchschnittliche F&E Ausgaben in Suedtirol

Prozentueller Abstand wie folgeneder:

Oesterreich 2x soviel wie Italien, 2x soviel wie Trentino, 2x soviel wie Suedtirol

Aber die Suedtiroler Unternehmen realisieren anteilmaessig das Beduerfniss nach Forschung ueberdurchschnittlich

Bericht Astat

Tuesday, January 12, 2010

Technologies as a infinite combination of themself

If new technologies were constructed from existing ones, then considered collectively, technology created ifself.
I also began to see that the economy was not so much a container for its technologies, as I had been implicitly taught. The economy arose from its technologies. It arose from its productive methods and legal and organizational arrangements that we use to satisfy our needs.

W. Brian Arthur - The Nature of Technology

Sunday, January 10, 2010

Privacy under Pressure

Friday night I had an interesting discussion regarding the future of privacy. My feeling was that peoples privacy in the web came under strong pressure the last five years, certainly due the success of social networks. Two days later I read a ReadWriteWeb article where Facebook’s Mark Zuckerberg sees a shift in social norms that deprecates personal privacy in the web. This article will try an inquiry about how privacy came under pressure. First word to Mr. Zuckerberg:
People have really gotten comfortable not only sharing more information and different kinds, but more openly and with more people. That social norm is just something that has evolved over time […]

We view it as our role in the system to constantly be innovating and be updating what our system is to reflect what the current social norms are.

Doing a privacy change for 350 million users is not the kind of thing that a lot of companies would do. But […] what would we do if we were starting the company now and we decided that these would be the social norms now and we just went for it”
Zuckerberg talks about the perceived shift of social norms as an opportunity to innovate. Indeed Management Thinker Peter Drucker named Changes in public perception as one of seven sources of innovation.
Assuming Zuckerberg is right, how comes that we experience a shift in culture where privacy is valued less? If the social network is the reason we have to take a look at the actors involved in their social affair. I identify four roles in there:
  1. The consuming viewer, who in his pure role only consumes the information created by self publishers. In reality processes the information and interchanges it with the publisher. He has no interest in privacy, as he wants to perceive as much as possible from the publishers output

  2. The network owner, who provides the tools for interchange. She has a genuine interest in maximizing the networks value. Privacy is working against her value maximization endeavor.

  3. Third party businesses. They want as much as information as they can get and are against privacy.

  4. The self publishing person that creates information about herself. She gains value in feedback from peers. She can increase potential value by becoming a public persona. But has an interest in controlling who knows what about herself.
We have obviously a single role with interest in privacy and this role is not so sure about it anymore, maybe because:
  1. Strong communicators showed how their value increases with giving away their data. More cautious People follow as they experience nothing awful happens.

  2. People are more comfortable with internet in general. Old fears and power abuse fantasies are gone.

  3. Privacy concerns exist, but many see the control in how you present yourself - not in whom you allow to view your profile
We have seen that social network privacy encounters strong interests against from all the network actors and since it decreases the benefit of everyone involved, its crisis is reasonable. Only to become again vital if a major abuse occurs.

Friday, January 8, 2010

What the heck is a tool?

A broad definition of a tool is an entity used to interface between two or more domains that facilitates more effective action of one domain upon the other. The most basic tools are simple machines. For example, a crowbar simply functions as a lever. The further out from the pivot point, the more force is transmitted along the lever. A hammer typically interfaces between the operator's hand and the nail the operator wishes to strike.

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