For decades psychologists have done research to demonstrate that the human animal is not omniscient and makes mistakes -- or, in fancier language, that human beings are subject to "cognitive limitations." This type of research achieved the status of a high art and wide public renown with the publication of Judgment Under Uncertainty: Heuristics and Biases (1982) by Daniel Kahneman, Pail Slovic & Amos Tversky. Research on human cognitive limitations has accelerated since then. Entire fields -- e.g., behavioral economics -- take human cognitive limitations as their central premise and problem. Legal scholars now routinely cite this type of research, which is now beginning to have a significant influence on the law of evidence. (The prime example of such influence on the law of evidence is the legal treatment of eyewitness identification.)
Research on human cognitive limitations is plainly interesting and informative and some of it should influence the law of evidence. But there are several reason why this sort of research needs to be kept in perspective. One reason is that the general thesis that human beings make inferential errors and have limited cognitive capacity is not exactly new; people have recognized this for thousands of years. But modern research has gone beyond this general hypothesis and has explored how (but less often why) human beings make inferential and deliberative mistakes in specific types of situations and such research has perhaps shown that human beings are more error-prone than they think they are. Nonetheless, we should all be cautious about such research and findings. That is because ordinary human beings are endowed with truly remarkable and sophisticated cognitive equipment and inferential ability. This is suggested and, I think, effectively established, ironically enough, by cutting-edge contemporary research in fields such as neuroscience and artificial intelligence on the electro-physio-magneto-neuro-equipment that we commonly call "the brain." Consider, for example, the following snippet from the post Low Power Chips to Model a Billion Neurons (August 8, 2012) on the blog Next Big Future (original source: here):
"The average human brain packs a hundred billion or so neurons—connected by a quadrillion (10^15) constantly changing synapses—into a space the size of a cantaloupe. It consumes a paltry 20 watts, much less than a typical incandescent lightbulb. But simulating this mess of wetware with traditional digital circuits would require a supercomputer that’s a good 1000 times as powerful as the best ones we have available today. And we’d need the output of an entire nuclear power plant to run it."
I submit that we should not begin with the (default) assumption that the human animal is dim-witted. The ordinary person has remarkably extraordinary cognitive equipment. This is true even though the human animal is not infallible.
- A hat tip to Markus Sagebiel for calling our attention to the above blog post.
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