It is common to think – especially among evolutionists who do not have a background in psychology – that there is nothing wrong with going directly from the principles of natural selection to predictions about behavior, skipping the psychological or information-processing level of analysis. But skipping the level of psychological adaptations – the information-processing machinery built by natural selection – can lead one astray (Cosmides and Tooby 1987).

Consider incest aversion. Studies suggest that the mind uses a few key cues during childhood to tag individuals as siblings, marking them as unsuitable sexual partners. Chief among these are childhood co-residence (years spent growing up with the other child in the same house) and maternal perinatal association (if you are the older sibling, observing your mother breastfeeding the other child). The human mind uses these two key informational inputs to tag someone as a sibling and consequently produces incest aversion at the thought of having sex with them. Normally, siblings encounter these cues during childhood and nonsiblings do not. But sometimes there is a mismatch – and these mismatches are revealing. For instance, in the phenomenon of Taiwanese minor marriages, a young female child is betrothed to a young male child, and they are both raised by the boy’s parents in the boy’s parents’ house. Because they grow up together in the same household (childhood co-residence), their brains mistakenly tag each other as siblings, producing incest aversion. As a consequence, the individuals involved in Taiwanese minor marriages report less sexual interest in one another, lower fertility rates, lower relationship satisfaction, and higher divorce rates (Lieberman et al. 2007; Lieberman and Symons 1998). In essence, the mind mistakenly coded a nonrelative as a sibling because it received the key informational input of childhood co-residence (Lieberman et al. 2003, 2007).

This process can fail in the opposite way, too: genetic siblings who do not receive the key informational inputs of childhood co-residence and maternal perinatal association may fail to psychologically tag each other as siblings, leaving open the possibility of being sexually attracted to each other later in life. This is exactly what happened to some siblings who were separated at birth, grew up apart, and later in life found each other and fell in love (Childs 1998). This outcome makes no sense unless you take into account the information-processing level of analysis. If you attempt to go directly from the principles of natural selection to behavior, the phenomenon appears incomprehensible – they are genetic siblings, so why are they sexually attracted to each other? By contrast, if you do not skip the information-processing level of analysis, the difficulty immediately disappears: these siblings were reared apart, so their minds did not receive the key informational inputs needed to produce incest aversion. That is why they are capable of being sexually attracted to one another.

In short, if you leapfrog the psychological level of analysis and attempt to go directly from the principles of natural selection to statements about behavior, you will make mistakes in both prediction and explanation (Cosmides and Tooby 1987). This brings to mind two quotes from foundational evolutionary thinkers, one by Donald Symons and the other by John Tooby and Leda Cosmides. To paraphrase Don Symons, the evolutionist should focus on psychology and information processing. When he ignores these in favor of observable behavior, he is like the drunk looking for his key under the lamppost: he knows he dropped it in the dark, but under the lamppost the light is better (Symons 1979).

And as Tooby and Cosmides wrote so eloquently, “The fact that the brain processes information is not an accidental side effect of some metabolic process. The brain was designed by natural selection to be a computer. Therefore, if you want to describe its operation in a way that captures its evolved function, you need to think of it as composed of programs that process information” (Tooby and Cosmides 2005, pp. 16–17). In short, if you want to maximize the accuracy of your evolution-based predictions and explanations, you would do well not to skip the information-processing level of analysis.