[This is a continuation of this post.]
Key to Fairweather & Montemayor’s argument for frugal virtues are the claims that “heuristic reasoning implements threshold evaluations for selected criteria that exploit reliable features of task environments” (emphasis theirs) and so can be a source of knowledge “when properly selected in the right environments.” Now that we’ve seen how complex are the relations among criteria, mediators, and recognitional capacities, achieving this goal may not seem so straightforward.
Consider an epistemic agent making an inference. She could consciously select a criterion about which to make a heuristic inference, and certainly sometimes people do so. This would enable her to choose a criterion that is suitably connected via environmental and social mediators to her recognitional capacities. More often than not, though, people don’t engage in conscious selection. Indeed, one of the cornerstones of research on heuristics is that people tend to use them automatically, not consciously. This raises the possibility that heuristics will be used on criteria to which they are not adapted.
Next, our epistemic agent needs to select a heuristic to apply. There are many in the heuristic toolbox. As with the criterion, this selection can be conscious and intentional. Gigerenzer has a lucrative consulting practice through which he designs carefully tested heuristics for decision-makers such as doctors and businesses. By and large, however, this second selection will also be an automatic process. Thus, even if someone selects a suitable criterion, she may end up applying the wrong heuristic to it.
There is also the possibility that some of the feedback loops from recognition (or whatever other psychological capacity is used) to the criterion or the mediators may damage the accuracy or reliability of the heuristic inference. Presumably, this is part of the explanation of the sometimes swift and unexpected changes in fashion. As the band Tower of Power puts it, “What’s hip today, might become passé” – in part because it is hip (and recognized) today.
If these stumbling blocks can be circumnavigated, the frugal virtues approach would be promising. In some instances, I’m sure they can. Hospitals that shell out large sums to have Gigerenzer’s team design a heuristic for them are likely have a well-selected criterion, to use the heuristic they paid for rather than one that they had been using (perhaps unconsciously) before, and to see to it that their use of the heuristic does not ricochet back on the mediators or the criterion. But what about ordinary people making ordinary inferences? Here the news is not so good. In Character as Moral Fiction I described studies by Tversky and Kahneman that attempted to get people to stop using the representativeness heuristic when it was not suited to the inference at hand. Recalcitrance ruled the day. Goldstein & Gigerenzer (2002, p. 81-3) report a pair of experiments in which participants could use the recognition heuristic to make inferences about the size of various German cities. They did so 90% of the time when the heuristic was well-suited to the inference, and 92% of the time when it was ill-suited to the inference. In other words, at least for one criterion, people were completely insensitive to evidence against the trustworthiness of the recognition heuristic.
If this sort of result holds generally – if people tend to use heuristics willy nilly – then, even though heuristics can be a source of knowledge “when properly selected in the right environments,” they are not sources of knowledge for creatures like us. It’s hard to get a read on this. Life is not a controlled experiment. But indications are not heartening. For instance, Borges, Goldstein, Ortmann, & Gigerenzer (1999) famously found that, when the criterion was not a city’s population but the prospects of a publicly-traded company’s stock, a portfolio based on the recognition heuristic performed surprisingly well. Over a six-month period, a portfolio based on the best-recognized stocks outperformed portfolios based on the least-recognized stocks and the market as a whole. But don’t call your broker just yet. Other researchers have attempted in vain to replicate this effect. Andersson & Rakow (2007) ran four studies with seven sets of participants from all around the world, but failed to find any support for the recognition-based portfolio’s success. They conclude that “recognition is, on average, simply a near random method of selecting stocks with respect to their profitability” (p. 36). Likewise, Boyd (2001) attempted to replicate the effect to no avail. This might seem unsurprising. After all, one reason we hear about companies is that they are innovative, powerful, and profitable, but another is that they are the exact opposite. Here’s a graph of newspaper headlines mentioning the ‘AIG’, courtesy of Google Trends:
Figure XXX: Headlines mentioning ‘AIG’ over time
This should drive home the import of the domain-specificity of the recognition heuristic. The domains are very small indeed, but our reasoning is not sensitive to this fact. As Kelman (2011) points out, even on the cities task, the recognition heuristic delivers disappointing results when the participants are Americans and the cities aren’t in North America or Western Europe. As of the writing of this paper, Guangfo is the 12th most populous urban zone in the world, but most Americans have never heard of it. Results like these should make us wary of accepting Fairweather & Montemayor’s (forthcoming) account of frugal virtues.
[This last point is made more forcefully here.]
 Adam Morton (2000) explores the possibility of a meta-heuristic that automatically selects which first-order heuristic to apply.