The Fundamental Computational Bias and the Ecology of the Modern World

THE FUNDAMENTAL COMPUTATIONAL BIAS AND THE ECOLOGY OF THE MODERN WORLD

The fundamental computational bias, that “specific features of problem content, and their semantic associations, constitute the dominant influence on thought” (Evans et al., 1983, p. 295; Stanovich, 1999), is no doubt rational in the evolutionary sense. Selection pressure was probably in the direction of radical contextualization. An organism that could bring more relevant information to bear (not forgetting the frame problem) on the puzzles of life probably dealt with the world better than competitors and thus reproduced with greater frequency and contributed more of its genes to future generations.

Evans and Over (1996) argue that an overemphasis on normative rationality has led us to overlook the adaptiveness of contextualization and the nonoptimality of always decoupling prior beliefs from problem situations. They note the mundane but telling fact that when scanning a room for a particular shape, our visual systems register color as well. They argue that we do not impute irrationality to our visual systems because they fail to screen out the information that is not focal. Our systems of recruiting prior knowledge and contextual information to solve problems with formal solutions are probably likewise adaptive in the evolutionary sense. However, Evans and Over (1996) note, there is an important disanalogy here as well, because studies of belief bias in syllogistic reasoning have shown that “subjects can to some extent ignore belief and reason from a limited number of assumptions when instructed to do so” (p. 117). That is, in the case of reasoning – as opposed to the visual domain – some people do have the cognitive flexibility to decouple unneeded systems of knowledge and some do not. The studies reviewed here indicate that those who do have the requisite flexibility are somewhat higher in cognitive ability and in actively open-minded thinking (see Stanovich & West, 1997).

A conflict between the decontextualizing requirements of normative rationality and the fundamental computational bias may perhaps be one of the main reasons that normative and evolutionary rationality dissociate. The fundamental computational bias is meant to be a global term that captures the pervasive bias toward the contextualization of all informational encounters. It conjoins the following processing tendencies: (a) the tendency to adhere to Gricean conversational principles even in situations that lack many conversational features (Adler, 1984; Hilton, 1995); (b) the tendency to contextualize a problem with as much prior knowledge as is easily accessible, even when the problem is formal and the only solution is a content-free rule (Evans, 1982, 1989; Evans, Barston, & Pollard, 1983); (c) the tendency to see design and pattern in situations that are either undesigned, unpatterned, or random (Levinson, 1995); (d) the tendency to reason enthymematically – to make assumptions not stated in a problem and then reason from those assumptions (Henle, 1962; Rescher, 1988); (e) the tendency toward a narrative mode of thought (Bruner, 1986, 1990). All of these properties conjoined together represent a cognitive tendency toward radical contextualization. The bias is termed fundamental because it is thought to stem largely from System 1 and that system is assumed to be primary in that it permeates virtually all of our thinking (e.g., Evans & Over, 1996). If the properties of this system are not to be the dominant factors in our thinking, then they must be overridden by System 2 processes so that the particulars of a given problem are abstracted into canonical representations that are stripped of context.

In short, one of the functions of System 2 is to override some of the automatic contextualization provided by System 1. This override function might only be needed in a tiny minority of information processing situations (in most cases, the two systems interact in concert), but they may be unusually important ones. For example, numerous theorists have warned about a possible mismatch between the fundamental computational bias and the processing requirements of many tasks in a technological society containing many symbolic artifacts and often requiring skills of abstraction (Adler, 1984, 1991; Donaldson, 1978, 1993; Hilton, 1995).

Einhorn and Hogarth (1981) highlighted the importance of decontextualized environments in their discussion of the optimistic (Panglossian/Apologist) and pessimistic (Meliorist) views of the cognitive biases revealed in laboratory experimentation. They noted that “the most optimistic asserts that biases are limited to laboratory situations which are unrepresentative of the natural ecology” (p. 82), but go on to caution that “in a rapidly changing world it is unclear what the relevant natural ecology will be. Thus, although the laboratory may be an unfamiliar environment, lack of ability to perform well in unfamiliar situations takes on added importance” (p. 82). There is a caution in this comment for critics of the abstract content of most laboratory tasks and standardized tests. The argument that the laboratory tasks and tests are not like “real life” is becoming less and less true. “Life,” in fact, is becoming more like the tests!

Evolutionary psychologists in the Apologist camp have concentrated on shaping the environment (changing the stimuli presented to subjects) so that the same evolutionarily adapted mechanisms that fail the standard of normative rationality under one framing of the problem give the normative response under an alternative (e.g., frequentistic) version. Their emphasis on environmental alteration provides a much-needed counterpoint to the Meliorist emphasis on cognitive change. The latter, with their emphasis on reforming human thinking, no doubt miss opportunities to shape the environment so that it fits the representations that our brains are best evolved to deal with. Investigators framing cognition within a Meliorist perspective are often blind to the fact that there may be remarkably efficient mechanisms available in the brain – if only it was provided with the right type of representation. However, it is not always the case that the world will let us deal with representations that are optimally suited to our evolutionarily designed cognitive mechanisms.