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Introduction

The field of evolutionary psychology (EP hereafter) was formed in the 1990s by Tooby, Cosmides, and Barkow, which was a kind of cousin to E. O. Wilson’s Sociobioligy. They surmised that “[t]he human brain is a set of computational machines, each of which was designed by natural selection to solve adaptive problems faced by our hunter-gatherer ancestors” (Duchaine, Cosmides, and Tooby, 2001). EP has been used to explain the psychological differences between rightists and leftists (Ryan, 2020), rape (Thornhill and Palmer 1990; Thornhill and Palmer, 2001, 2004; Ward and Sigert, 2002; Mckibbin et al, 2008; Kong, 2021) and the modular mind. It attempts to explain the proliferation of traits throughout the ages by appeal to natural selection of psychological traits and mental abilities.

Many critiques of the scientific status EP have been raised (see Rose and Rose, 2001), including the fact that it relies on speculative narratives and the lack of testable predictions of previously unknown facts. The scientific method forms the cornerstone of scientific inquiry and using it, we can formulate hypotheses that can be tested and falsified through empirical research. But one critical aspect of scientific inquiry poses an issue for EP—mainly the lack of testable predictions of previously unknown facts. EP weaves admittedly nice-sounding stories about the evolution of traits after the fact, constructing stories to explain observed behaviors in humans and other animals. This of course then raises a serious question: How can EP produce hypotheses that can be tested and validated?

The lack of novel predictions for EP hypotheses then hampers its scientific status. Novel predictions—by their very nature—offer opportunities for discovery and furthering our understanding of the world. Further, a hypothesis doesn’t need only to be novel (in that it predicts a previously unknown fact which wasn’t used in the construction of the hypothesis), but it also needs to be risky—where “risky” means that it could confirm or disconfirm the hypothesis in question. But EP, with its ad/post hoc retrospective storytelling could be accused of falling into the “just-so stories” trap, meaning that any observation can be made to cohere to any given set of observations.

Critics have argued for years that the lack of testable predictions and reliance on post hoc explanations harm the scientific rigor of EP. The scientific method demands empirical testing to confirm or refute hypotheses which then enables researchers to refine their theories and advance our knowledge of the world. So without a solid foundation of testable predictions, EP is no more than narrative construction, which lacks the empirical rigor and objectivity expected of a scientific enterprise.

So it becomes essential to critically examine the scientific status of EP, and by assessing it’s ability to generate testable novel predictions and it’s adherence to the scientific method, we can then evaluate whether or not EP can truly be considered a scientific field. This article will delve into the intracacies of the debate at hand, while exploring the lack of testable predictions and thusly EP’s scientific status. I will then of course argue negatively—EP can’t be a science since it doesn’t make any risky, novel predictions of previously unknown facts.

On risky, novel predictions

A risky, novel prediction refers to a prediction made by a scientific theory or hypothesis that goes beyond what is expected or already known within an existing framework (novelness). It involves making a specific claim about a future observation or empirical result that, if confirmed, would provide considerable evidence in support of the scientific theory or hypothesis.

They are characterized by their level of specificity along with the potential of being falsified. They assert that a particular outcome would be observed under particular conditions, which should not align with current knowledge or contemporary theories. They are considered “risky”, in that they carry the possibility of being proven wrong which therefore would be a significant strike against the validity of the proposed hypothesis or theory.

So what distinguishes a risky, novel prediction from one that isn’t is its departure into the unknown. So by venturing into the unknown, we can then test the limits of our scientific knowledge and expand the frontiers of our scientific understanding. So what is the distinction between a risky, novel prediction and one that isn’t?

A risky, novel prediction is more specific or precise than one that isn’t risky or novel. It provides explicity detail on what we should expect should the hypothesis hold. On the other hand, a prediction that isn’t risky or novel could be more general or vague, and so it would lack the specifity to evaluate it’s validity. A further issue which pertains to the vagueness of a prediction that isn’t risky or novel is that fact that, since it is general and vague, one could attempt to save the hypothesis from falsification by forming an ad hoc hypothesis to save it.

A risky, novel prediction carries a higher risk of being proven wrong or falsified. Since it is so specific, it then asserts that a particular outcome should hold under certain conditions, and if it doesn’t hold then it provides evidence against the theory or hypothesis. But a prediction that isn’t risky or novel—one that is general or vague—could easily be retrofitted to align with existing knowledge or easily be accommodated with existing theories, making falsification less likely. I have previously argued about the importance between the distinction between accommodation and prediction and how it means trouble for EP.

A risky, novel prediction goes beyond our current knowledge of the world; it ventures into unexplored territory or addresses phenomena which haven’t been extensively studied. By contrast, a prediction that isn’t risky or novel could cohere with existing theories, prior observations, or established patterns of understanding. Moreover, a risky, novel prediction has the capacity to push the boundaries of scientific knowledge and expand our understanding by challenging older hypotheses or theories. While a prediction that isn’t risky or novel may contribute incrementally to existing knowledge or theories.

Now that I have laid out the distinction between risky, novel predictions and those that aren’t, here’s the argument.

P1: Scientific theories that make risky, novel predictions are considered more scientifically valuable.
P2: Theory X makes a risky, novel prediction.
P3: If theory X makes a risky, novel prediction, then it exhibits the characteristics of scientific inquiry.
P4: Theory Y does not make any risky, novel predictions.
P5: If a theory does not make any risky, novel predictions, then it lacks the hallmark of scientific inquiry.
C1: Theory Y lacks a hallmark of scientific inquiry.
(MT, P1, P5)
C2: Theory X exhibits the characteristics of scientific inquiry. (MP, P2, P3)
C3: Theory Y does not exhibit the characteristics of scientific inquiry. (MT, C1, P4)
C4: Thus, there is a distinction between theories that make risky, novel predictions and theories that do not. (MP, C2, C3)

This discussion shows the utility of risky, novel predictions and the argument provided shows the distinction between theories or hypotheses that make novel predictions and those that do not. EP is an enterprise that makes no novel, risky predictions of previously unknown facts, therefore it is not scientific.

Why EP hypotheses aren’t scientific

Now that I have distinguished between hypotheses that predict novel facts of the matter and those that don’t, the argument that EP isn’t a scientific enterprise will now be presented.

EP relies almost exclusively on the analysis of existing data and observations. Due to the retrospective and reverse engineering (working backwards) of EP hypotheses, it is tough—and I claim it is impossible—to generate entirely new predictions that have not been previously considered or studied. This therefore is a methodological constraint.

EP aims at providing historical explanations to explain the origin and development of human behavior and psychology. It focuses on making retrospective explanations for existing phenomena rather than making specific predictions of future or unknown events. It tries to use evolutionary principles in order to explain the evolutionary forces that shaped the human mind. One way is by the assumption that the human mind is modular—this is called the massive modularity hypothesis (MMH). This hypothesis proposes that modules for mental processing evolved due to evolutionary natural selective pressures. This then prompted Tooby and Cosmides to claim that “our skulls house stone age minds.” But unfortunately for evolutionary psychologists, “the endorsement of the Massive Modularity Hypothesis by evolutionary psychologists is both unwarranted and unmotivated” (Samuels, 1998).

Further, EP’s reliance on “natural selection” is yet another strike against it’s scientific validity. This is because “natural selection” isn’t a mechanism. Thus, any claims that natural selection explains why we have certain psychological traits fails. It also fails because the mental is irreducible and so it can’t be selected like physical traits can.

Another hurdle to the scientific status of EP is its lack of independent verification. A hypothesis is independently verifiable if and only if it is verified independently of the data it purports to explain. So if there is no independent verification, then the hypothesis is ad hoc. If the hypothesis is ad hoc, then it is therefore a just-so story. So the question to ask an EP proponent is this: What is the independent verification for the hypothesis in question?

Here’s the argument:

P1: If a field is scientific, then it’s hypotheses make testable predictions of previously unknown facts.
P2: No EP hypothesis makes testable predictions of previously unknown facts.
P3: If EP hypothesis makes testable predictions of previously unknown facts, then EP isn’t a science.
C: Thus, EP is not a science.

Or we can put it like this:

P1: If a field is scientific, then its hypotheses should be based on empirical evidence and make testable predictions of previously unknown facts.
P2: No EP hypothesis makes is based on empirical evidence and makes testable predictions of previously unknown facts.
P3: If EP hypothesee are not based on empirical evidence and do not make testable predictions of previously unknown facts, then EP is not a science.
C: Therefore, EP is not a science.

This hurdle is one that, in my opinion, is insurmountable. The only way for us to verify EP hypotheses would be if we had time machines so we could go back in time and see how and why traits evolved the way they did. But we don’t have time machines. So we can’t verify EP hypotheses.

Conclusion

The field of EP has been subject to intense scrutiny ever since it’s inception. This began back in the 1970s with E. O. Wilson’s Sociobioligy, which Gould and Lewontin published their Spandrels paper in response to unverifiable stories using natural selection (Gould and Lewontin, 1977). I examined EP’s ability to provide risky, novel predictions of previously unknown facts and it’s reliance on retrospective explanations and storytelling along wkth reverse engineering. Thus, this discussion has shown that EP isn’t—and can never be—a scientific discipline since it lacks the hallmarks of scientific inquiry.

Thus EP hypotheses resemble just-so stories, which are narratives constructed after the fact to explain the proliferation of observed traits in the present day. The fact of the matter is, one can think up any kind of story to explain how and why a trait persists in the current day. Though the problem for EP is this: There is no way for any hypothesis to adjudicate between competing hypotheses. Multiple possibilities could explain the observations, but we have no way to know which could possibly be true due to the lack of independent verification and evidence.

EP hypotheses are always consistent with observations since they are selected to be consistent (Smith, 2016: 279). So of course these hypotheses provide coherent, plausible explanations for existing phenomena, because there is no other way for it to be.

In my previous article on this issue, I concluded:

To be justified in believing hypothesis H in explaining how trait T became fixated in a population there must be independent evidence for this belief. The hypothesis must generate a novel fact which was previously unknown before the hypothesis was constructed. If the hypothesis cannot generate any predictions, or the predictions it makes are continuously falsified, then the hypothesis is to be rejected. No EP hypothesis can generate successful predictions of novel facts and so, the whole EP enterprise is a degenerative research program. The EP paradigm explains and accommodates, but no EP hypothesis generates independently confirmable evidence for any of its hypotheses. Therefore EP is not a scientific program and just-so stories are not scientific.

The reliance on natural selection to retrospectively verify it’s hypotheses has also been an issue. This of course raises concerns about circular reasoning, since natural selection is used to support explanations of the hypothesis, rather than the hypotheses being generated from independent empirical evidence—this is because there can be no empirical evidence for any EP hypothesis.

Lastly, the absence of testable predictions of previously unknown facts is a significant limitation of EP, which then justifies the just-so story argument. This is because a hallmark of science is to generate hypotheses which can be empirically tested and potentially falsified. Though all EP hypotheses lack the specifity and novelty expected of actual scientific hypotheses which are required for meaningful empirical testing. The significant issues with EP are devestating to it’s proponents claims of being a science. The further fact that mental abilities/psychological traits can’t be selected since they aren’t physical is another insurmountable hurdle; psychological traits lack a specified measured object, object of measurement and measurement unit, so they aren’t physical therefore they can’t be selected.

So the conclusion I have argued for here the follows from the premises I’ve provided—EP isn’t a science since it relies on natural selection, retrospective explanations, and doesn’t generate any risky, novel facts of the matter, nor does it generate any novel predictions. It is for these reasons that EP isn’t and can never be a science.