What logical term or concept ought to be more widely known?

Various What scientific term or concept ought to be more widely known? Edge, 2017.

INTRODUCTION: SCIENTIA

Science—that is, reliable methods for obtaining knowledge—is an essential part of psychology and the social sciences, especially economics, geography, history, and political science. …

Science is nothing more nor less than the most reliable way of gaining knowledge about anything, whether it be the human spirit, the role of great figures in history, or the structure of DNA.

Contributions

As against others on:

(This is as far as I’ve got.)

Comment

I’ve grouped the contributions according to whether or not I think they give due weight to the notion of uncertainty as expressed in my blog. Interestingly Steven Pinker seems not to give due weight in his article, whereas he is credited by Nicholas G. Carr with some profound insights (in the first of the second batch). So maybe I am not reading them right.

My own suggestion would be Turing’s theory of ‘Morphogenesis’. The particular predictions seem to have been confirmed ‘scientifically’, but it is essentially a logical / mathematical theory. If, as the introduction suggests, science is “reliable methods for obtaining knowledge” then it seems to me that logic and mathematics are more reliable than empirical methods, and deserve some special recognition. Although, I must concede that it may be hard to tell logic from pseudo-logic, and that unless you can do so my distinction is potentially dangerous.

Morphogenesis

The second law of thermodynamics, and much common sense rationality,  assumes a situation in which the law of large numbers applies. But Turing adds to the second law’s notion of random dissipation a notion of relative structuring (as in gravity) to show that ‘critical instabilities’ are inevitable. These are inconsistent with the law of large numbers, so the assumptions of the second law of thermodynamics (and much else) cannot be true. The universe cannot be ‘closed’ in its sense.

Implications

If the assumptions of the second law seem to leave no room for free will and hence no reason to believe in our agency and hence no point in any of the contributions to Edge: they are what they are and we do what we do. But Pinker does not go so far: he simply notes that if things inevitably degrade we do not need to beat ourselves up, or look for scape-goats when things go wrong. But this can be true even if the second law does not apply. If we take Turing seriously then a seeming permanent status quo can contain the reasons for its own destruction, so that turning a blind eye and doing nothing can mean sleep-walking to disaster. Where Pinker concludes:

[An] underappreciation of the Second Law lures people into seeing every unsolved social problem as a sign that their country is being driven off a cliff. It’s in the very nature of the universe that life has problems. But it’s better to figure out how to solve them—to apply information and energy to expand our refuge of beneficial order—than to start a conflagration and hope for the best.

This would seem to follow more clearly from the theory of morphogenesis than the second law. Turing’s theory also goes some way to suggesting or even explaining the items in the second batch. So, I commend it.

Dave Marsay

 

 

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Who thinks probability is just a number? A plea.

Many people think – perhaps they were taught it – that it is meaningful to talk about the unconditional probability of ‘Heads’ (I.e. P(Heads)) for a real coin, and even that there are logical or mathematical arguments to this effect. I have been collecting and commenting on works which have been – too widely – interpreted in this way, and quoting their authors in contradiction. De Finetti seemed to be the only example of a respected person who seemed to think that he had provided such an argument. But a friendly economist has just forwarded a link to a recent work that debunks this notion, based on wider  reading of his work.

So, am I done? Does anyone have any seeming mathematical sources for the view that ‘probability is just a number’ for me to consider?

I have already covered:

There are some more modern authors who make strong claims about probability, but – unless you know different – they rely on the above, and hence do not need to be addressed separately. I do also opine on a few less well known sources: you can search my blog to check.

Dave Marsay

Assessing and Communicating Risks and Uncertainty

David Spielgelhalter Assessing and Communicating Risks and Uncertainty Science in Parliament vol 69, no. 2, pp. 21-26. This is part of the IMA’s Mathematics Matters: A Crucial Contribution to the Country’s Economy.

This starts with a Harvard study showing that “a daily portion of red meat was associated with an increase in the annual risk of death by 13% over the period of the study”. Does this mean, as the Daily Express claimed, that “10% of all deaths could be avoided”?

David S uses ‘survival analysis’ to show that “a 40 year-old  man who eats a quarter-pound burger for his working lunch each day can expect, on average, to live to 79, while his mate who avoids the burger can expect to live to 80.” He goes on: “over a lifetime habit, each daily portion of red meat is associated with about 30 minutes off your life expectancy .. ” (my emphasis.)

As a mathematician advising politicians and other decision-makers, I would not be comfortable that policy-makers understood this, and would act appropriately. They might, for example, assume that we should all be discouraged from eating too much red meat.

Even some numerate colleagues with some exposure to statistics might, I think, suppose that their life expectancy was being reduced by eating red meat. But all that is being said is that if a random person were selected from the population as a whole then – knowing nothing about them – a statistician would ‘expect’ them to have a shorter life if they eat red meat. But every actual individual ‘you’ has a family history and many by 40 will have had cholesterol tests. It is not clear what the relevance to them is of the statistician’s ‘averaged’ figures.

Generally speaking, statistics gathered for one set of factors cannot be used to draw precise conclusions about  other sets of factors, much less about individuals. David S’s previous advice at Don’t Know, Can’t Know applies. In my experience, it is not safe to assume that the audience will appreciate these finer points. All that I would take from the Harvard study is that if you eat red meat most days it might be a good idea to consult your doctor. I would also hope that there was research going on into the factors in the apparent dangers.

See Also

I would appreciate a link to the original study.

Dave Marsay

Football – substitution

A spanish banker has made some interesting observations about a football coach’s substitution choice.

The coach can make a last substitution. He can substitute an attacker for a defender or vice-versa. With more attackers the team  more likely to score but also more likely to be scored against. Substituting a defender makes the final score less uncertain. Hence there is some link with Ellsberg’s paradox. What should the coach do? How should he decide?

 

 

A classic solution would be to estimate the probability of getting through the round, depending on the choice made. But is this right?

 

Pause for thought …

 

As the above banker observes, a ‘dilemma’ arises in something like the 2012’s last round of group C matches where the probabilities depend, reflexively, on the decisions of each other. He gives the details in terms of game theory. But what is the general approach?

 

 

The  classic approach is to set up a game between the coaches. One gets a payoff matrix from which the ‘maximin’ strategy can be determined? Is this the best approach?

 

 

If you are in doubt, then that is ‘radical uncertainty’. If not, then consider the alternative in the article: perhaps you should have been in doubt. The implications, as described in the article, have a wider importance, and not just for Spanish bankers.

See Also

Other Puzzles, and my notes on uncertainty.

Dave Marsay 

What is the Public Understanding of Risk?

What is the Public Understanding of Risk?
Risky Business: Risk and Reward Assessment in Business Decision Making
D. Simmons FIMA , MD Analytics, Willes RE

Science in Parliament, Spring 2012, Reprinted in the IMA’s Mathematics Today, Vol. 48 No. 3 June 2012

This says very little about the public understanding of risk, and is more about the understanding within insurance and reinsurance companies. It discusses the potential use of probability in legal cases, and says:

There is no reason why such [probabilistic / statistical ] tools should not be used in government.

This contrasts oddly with an article in the previous issue:

T. Johnson, Heralding a New Era in Financial Mathematics, April 2012 

This starts by referring to Keynes and goes on:

The Bank of England believes that recent developments in financial mathematics have focused on microeconomic issues, such as pricing derivatives. Their concern is whether there is the mathematics to support macroeconomic risk analysis; how the whole system works. While probability theory has an important role to play in addressing these questions, other mathematical disciplines, not usually associated with finance, could prove useful. For example, the Bank’s interest in complexity in networks and dynamical systems has been well documented.

… As well as the Bank of England’s interest in models of market failure and systemic risk, more esoteric topics such as non-ergodic dynamical systems and models of learning in markets would be interesting. Topics associated with mainstream financial mathematics could include control in the presence of liquidity constraints, Knightian uncertainty and behavioural issues and credit modelling.

Thus, there seems to be at least one area where Keynes’ notion that uncertainty cannot always be represented by a single number, probability, is still relevant. Simmons’ contention inevitably lies outside the proper scope of mathematics, and is contentious.

Simmons does say:

All assumptions behind a decision can be seen, discussed, challenged and stressed.

This is a common claim of Bayesians and other probabilists, and has great merit, particularly if one is comparing it with a status quo of relying on gut-feel. But the decision to use a probabilistic approach is not unimportant and we should consider, as Keynes does, the implicit assumptions behind it.

There are actually many different axiomatizations of probability. They all assume that the system under consideration is in some sense regular, and that one is concerned with averages. These conditions seem to apply to insurance and re-insurance, but not always to legal matters or government policy.

My own involvement in reinsurance was in the government’s covering of the market’s failure to cope with the non-stochastic risk presented by terrorism. If it were true that government could address risk in the same way as the reinsurers, what would the point of government cover be? Similarly, in finance, what is the regulatory role of governmental institutions if the probabilistic view of risk is correct? My career has largely been spent in explaining to decision-makers why the people who ultimately carry the risk have to take a different approach to limited liability companies, who can treat risk as if it were a gamble. (I tend to find the tools of Keynes, Turing and Good appropriate to ‘wider risk’.)

Hopefully the IMA president’s up-coming address will enlighten us all.

See also

Other debates, my blog, bibliography.

 

Dave Marsay 

The origins of Bayes’ insights: a puzzle

In English speaking countries the Rev. Thomas Bayes is credited with the notion that all kinds of uncertainty can be represented by numbers, such as P(X) and P(X|Y), that can be combined just as one can combine probabilities for gambling (e.g. Bayes’ rule).

You are told that one of these is true:

  1. Bayes was in the  habit of attending the local Magistrates Court and making an assessment of the defendant’s guilt based on his appearance, and then comparing it with the verdict.
  2. Bayes performed an experiment in which he blindly tossed balls on to a table while an assistant told him whether the ball was to the right or left of the original.

Assign probabilities to these statements. (As usual, I’d be interested in your assumptions, theories etc. If you don’t have any, try here.) 

More similar puzzles here.

Dave Marsay

Avoiding ‘Black Swans’

A UK Blackett Review has reviewed some approaches to uncertainty relevent to the question “How can we ensure that we minimise strategic surprises from high impact low probability risks”. I have already reviewed the report in its own terms.  Here I consider the question.

  • One person’s surprise may be as a result of another person’s innovation, so we need to consider the up-sides and down-sides together.
  • In this context ‘low probability’ is subjective. Things are not surprising unless we didn’t expect them, so the reference to low probability is superfluous.
  • Similarly, strategic surprise necessarily relates to things that – if only in anticipation – have high impact.
  • Given that we are concerned with areas of innovation and high uncertainty, the term ‘minimise’ is overly ambitious. Reducing would be good. Thinking that we have minimized would be bad.

The question might be simplified to two parts:

  1. “How can we ensure that we strategize?
  2. “How can we strategize?”

These questions clearly have very important relative considerations, such as:

  • What in our culture inhibits strategizing?
  • Who can we look to for exemplars?
  • How can we convince stakeholders of the implications of not strategizing?
  • What else will we need to do?
  • Who might we co-opt or collaborate with?

But here I focus on the more widely-applicable aspects. On the first question the key point seems to be that, where the Blackett review points out the limitations of a simplistic view of probability, there are many related misconceptions and misguided ways that blind us to the possibility of or benefits of strategizing. In effect, as in economics, we have got ourselves locked into ‘no-strategy strategies’, where we believe that a short-term adaptive approach, with no broader or long-term view, is the best, and that more strategic approaches are a snare and a delusion. Thus the default answer to the original question seems to be ‘you don’t  – you just live with the consequences’. In some cases this might be right, but I do not think that we should take it for granted. This leads on to the second part.

We at least need ‘eyes open minds open’, to be considering potential surprises, and keeping score. If (for example, as in International Relations) it seems that none of our friends do better than chance, we should consider cultivating some more. But the scoring and rewarding is an important issue. We need to be sure that our mechanisms aren’t recognizing short-term performance at the expense of long-run sustainability. We need informed views about what ‘doing well’ would look like and what are the most challenging issues, and to seek to learn and engage with those who are doing well. We then need to engage in challenging issues ourselves, if only to develop and then maintain our understanding and capability.

If we take the financial sector as an example, there used to be a view that regulation was not needed. There are two more moderate views:

  1. That the introduction of rules would distort and destabilise the system.
  2. That although the system is not inherently stable, the government is not competent to regulate, and no regulation is better than bad regulation.

 My view is that what is commonly meant by ‘regulation’ is very tactical, whereas the problems are strategic. We do not need a ‘strategy for regulation’: we need strategic regulation. One of the dogmas of capitalism is that it involves ‘free markets’ in which information plays a key role. But in the noughties the markets were clearly not free in this sense. A potential role for a regulator, therefore, would be to perform appropriate ‘horizon scanning’ and to inject appropriate information to ‘nudge’ the system back into sustainability. Some voters would be suspicious of a government that attempts to strategize, but perhaps this form of regulation could be seen as simply better-informed muddling, particularly if there were strong disincentives to take unduly bold action.

But finance does not exist separate from other issues. A UK ‘regulator’ would need to be a virtual beast spanning  the departments, working within the confines of regular general elections, and being careful not to awaken memories of Cromwell.

This may seem terribly ambitious, but maybe we could start with reformed concepts of probability, performance, etc. 

Comments?

See also

JS Mill’s views

Other debates, my bibliography.  

Dave Marsay