In my previous post I set up the problem of how to interpret the uses of psychological predicates in many unexpected domains throughout biology. In this one I will describe in general the evidence on which the extensions are based. I divide this evidence into two types: qualitative analogy and quantitative analogy. (Any case of extension can include both.) Qualitative analogy is familiar from the history of science – e.g., the mini-solar-system model of the atom – and, in biology, evolutionary lineages that yield homologies (or homoplasies, if the same functions develop in distinct lineages). Much of the evidence for the new extensions so far is of this sort.
The more interesting type is quantitative analogy, or extension based on mathematical modeling. A non-psychological example of a mathematical model is the Lotka-Volterra model, which captures the fluctuations in relative size between predator and prey populations. Following Weisberg, a model consists of a structure (in this case, described by two linked equations) and an interpretation or construal, which specifies what the modeler intends the symbols in the equation to stand for (in this case, real-world populations of sharks and cod (or other prey fish) in the Adriatic). The crucial fact about models in this context is that scientists try to extend them to new domains all the time, and it is not up to them whether the data gathered in the new domain will fit the model or not, setting aside questionable data-massaging. For example, the Lotka-Volterra model has been extended to the relations between foxes and rabbits, wages and jobs, and capillary tips and chemoattractant, inter alia. This is important because scientists are using mathematical models of cognitive capacities in new domains and extending the concepts used in the construals to the new domains. It is not up to us whether a model fits in the new domain. But if it does, that provides strong, if prima facie, evidence that the entities in the new domain possess the capacity being modeled. Moreover, that evidence is objective in the sense that it is independent of ordinary observation-based judgments of the entities’ similarity to us. A model provides at least structural similarity between distinct domains and motivates inquiry into the nature and depth of the similarity.
An example is Roger Ratcliff’s Drift-Diffusion Model (DDM) of two-choice decision-making, which was initially developed from data gathered from people (e.g., college undergraduates). These are simple choices, such as deciding whether a given stimulus is the same or different from a sample, and then pressing a computer key “yes” or “no”. (In real life: (e.g.) should I go to the left or the right around this obstacle?) The model divides the time from the presentation of the stimulus to the subject’s response into a non-decision time (encoding the stimulus, preparing to press the key) and the decision time, which includes the cognitive processes of accumulating and assessing evidence until a decision threshold is reached, and then making the decision. The model captures the speed-accuracy tradeoff whereby, when presented with noisy stimuli, we make either quick or accurate decisions but not both. It turns out that the model also applies to fruit flies (inter alia). In fact, differences in the speed and accuracy of fruit fly decision-making have been linked to mutations in the FOX-P genetic family, which is linked to cognitive deficits in humans.
To make the problem vivid in non-technical form, I’ll modify a popular version of the Argument for Other Minds:
- My behavior is caused by my mental states.
- I observe that others behave similarly to me.
- Either they have mental states that cause their behavior, or I am unique and something else causes their behavior.
- The first hypothesis is best because it explains both cases.
- So it is probable (or rational to conclude) that they also have mental states.
- My choosing behavior is caused by my decision-making processes.
- Scientists have developed a quantitative model of decision-making of my and others’ choosing behavior.
- Either the models’ construals are the same for others or I am unique and we must interpret the construals differently for the others.
- The first hypothesis is best because it explains both (or all) cases.
- So it is probable (or rational to conclude) that they also have decision-making processes.
Anyone who accepts the original argument should find the modified version cogent as well. It just so happens that the “others” includes fruit flies, inter who knows how many alia. (Volterra started with fish, after all.) Nothing has changed except for the entity to which the capacity is ascribed. To point out that the new entities are non-human merely raises the question: What determines whether the capacities ascribed to the entities are real or full-blooded?