by From Lars Syll Why, it might be objected, should the goal of social science be mere causal explanations of particular events? Isn’t such an attitude more the province of the historian? Social science should instead be concentrating on systematic knowledge. The Prisoner’s Dilemma, this objection concludes, is a laudable example of exactly that – a piece of theory that sheds light over many different cases. In reply, we certainly agree that regularities or models that explain or that give heuristic value over many different cases are highly desirable. But ones that do neither are not – especially if they use up huge resources along the way. When looking at the details, the Prisoner’s Dilemma’s explanatory record so far is poor and its heuristic record mixed at best. The only way to
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from Lars Syll
Why, it might be objected, should the goal of social science be mere causal explanations of particular events? Isn’t such an attitude more the province of the historian? Social science should instead be concentrating on systematic knowledge. The Prisoner’s Dilemma, this objection concludes, is a laudable example of exactly that – a piece of theory that sheds light over many different cases.
In reply, we certainly agree that regularities or models that explain or that give heuristic value over many different cases are highly desirable. But ones that do neither are not – especially if they use up huge resources along the way. When looking at the details, the Prisoner’s Dilemma’s explanatory record so far is poor and its heuristic record mixed at best. The only way to get a reliable sense of what theoretical input would actually be useful is via detailed empirical investigations. What useful contribution – whether explanatory, heuristic or none at all – the Prisoner’s Dilemma makes to such investigations cannot be known until they are tried. Therefore resources would be better directed towards that rather than towards yet more theoretical development or laboratory experiments.
Game theory is, like mainstream economics in general, model-oriented. There are many reasons for this – the history of the discipline, having ideals coming from the natural sciences (especially physics), the search for universality (explaining as much as possible with as little as possible), rigour, precision, etc. Most mainstream economists and game theorists want to explain social phenomena, structures and patterns, based on the assumption that the agents are acting in an optimizing (rational) way to satisfy given, stable and well-defined goals.
Building their economic models, modern mainstream economists ground their models on a set of core assumptions describing the agents as ‘rational’ actors and a set of auxiliary assumptions. Based on these two sets of assumptions, they try to explain and predict both individual and social phenomena.
The model used is typically seen as a kind of thought experimental ‘as if’ benchmark device for enabling a rigorous mathematically tractable illustration of social interaction in an ideal-type model world, and to be able to compare that ‘ideal’ with reality. The ‘interpreted’ model is supposed to supply analytical and explanatory power, enabling us to detect and
understand mechanisms and tendencies in what happens around us in real economies.
But if the models are to be relevant, we also have to argue that their precision and rigour still holds when they are applied to real-world situations. They often do not. When addressing real economies, the idealizations and abstractions necessary for the deductivist machinery to work simply do not hold. If the real world is fuzzy, vague and indeterminate, then why should our models build upon a desire to describe it as precise and predictable? Being told that the model is rigorous and amenable to ‘successive approximations’ to reality is of little avail, especially when the law-like (nomological) core assumptions are highly
questionable and extremely difficult to test.
Many mainstream economists – still – think that game theory is useful and can be applied to real-life and give important and interesting results. That, however, is a rather unsubstantiated view. What game theory does is, strictly seen, nothing more than investigating the logic of behaviour among non-existant robot-imitations of humans. Knowing how those ‘rational fools’ play games do not help us to decide and act when interacting with
real people. Knowing some game theory may actually make us behave in a way that hurts both ourselves and others. Decision-making and social interaction are always embedded in socio-cultural contexts. Not taking account of that, game theory will remain an analytical cul-de-sac that never will be able to come up with useful and relevant explanations.
Over-emphasizing the reach of instrumental rationality and abstracting away from the influence of many known to be important factors, reduces the analysis to a pure thought experiment without any substantial connection to reality. Limiting theoretical economic analysis in this way – not incorporating both motivational and institutional factors when trying to explain human behaviour – makes economics insensitive to social facts.
Game theorists extensively exploit ‘rational choice’ assumptions in their explanations. That is probably also the reason why game theory has not been able to accommodate well-known anomalies in its theoretical framework. That should hardly come as a surprise to anyone. Game theory with its axiomatic view on individuals’ tastes, beliefs, and preferences, cannot accommodate very much of real-life behaviour. It is hard to find really compelling arguments in favour of us continuing down its barren paths since individuals obviously do not comply with, or are guided by, game theory.
Apart from a few notable exceptions it is difficult to find really successful applications of game theory. Why? To a large extent simply because the boundary conditions of game theoretical models are false and baseless from a real-world perspective. And, perhaps even more importantly, since they are not even close to being good approximations of real-life, game theory is lacking predictive power. This should come as no surprise. As long
as game theory sticks to its ‘rational choice’ foundations, there is not much to be hoped for.
Game theorists can, of course, marginally modify their tool-box and fiddle with the auxiliary assumptions to get whatever outcome they want. But as long as the ‘rational choice’ core assumptions are left intact, it seems a pointless effort of hampering with an already excessive deductive-axiomatic formalism. If you do believe in a real-world relevance of game theoretical ‘science fiction’ assumptions such as expected utility, ‘common knowledge,’ ‘backward induction,’ correct and consistent beliefs etc., etc., then adding things like ‘framing,’ ‘cognitive bias,’ and different kinds of heuristics, do not ‘solve’ any problem. If we want to construct a theory that can provide us with explanations of individual cognition, decisions, and social interaction, we have to look for something else.
As noted by Northcott and Alexandrova, applications of game theory have on the whole resulted in massive predictive failures. People simply do not act according to the theory. They do not know or possess the assumed probabilities, utilities, beliefs or information to calculate the different (‘subgame,’ ‘tremblinghand perfect’) Nash equilibria. They may be reasonable and make use of their given cognitive faculties as well as they can, but they are obviously not those perfect and costless hyper-rational expected utility maximizing calculators game theory posits. And fortunately so. Being ‘reasonable’ make them avoid all those made-up ‘rationality’ traps that game theory would have put them in if they had tried to act as consistent players in a game theoretical sense.