Is rationality a cognitive faculty?

Elias L. Khalil

doi:10.12688/f1000research.129786.1

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Opinion Article

Is rationality a cognitive faculty?

[version 1; peer review: 1 approved with reservations, 1 not approved]

Elias L. Khalil

PUBLISHED 23 Jan 2023

Author details Author details

School of Economics, Administration and Public Policy, Doha Institute for Graduate Studies, Doha, 70, Qatar

Elias L. Khalil
Roles: Conceptualization, Formal Analysis, Writing – Original Draft Preparation, Writing – Review & Editing

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Abstract

Rationality cannot be a form of intelligence or any other cognitive faculty such as memory, language faculty, mathematical skill, and so on. To establish this thesis, this paper uses a distinction from set theory, namely, the distinction between “binary relators” and “binary operators”. Rationality acts as a binary relator in the sense that it is an optimization method, while cognitive ability acts as a binary operator in the sense that it is a transformational function. Rationality as an optimization method (binary relator) does not differ from the neo-Darwinian notion of natural selection: either method seeks to find the best choice or fit trait given the constraints. A cognitive faculty as a transformational function (binary operator) simply translates inputs into outputs. The distinction between rationality and cognitive functions has wide-ranging implications regarding the theory of evolution.

Keywords

Set Theory; Binary Relator; Binary Operator; Optimization Method; Natural Selection; Intelligence; Memory; Technology

Corresponding author: Elias L. Khalil

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2023 Khalil EL. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Khalil EL. Is rationality a cognitive faculty? [version 1; peer review: 1 approved with reservations, 1 not approved]. F1000Research 2023, 12:83 (https://doi.org/10.12688/f1000research.129786.1) First published: 23 Jan 2023, 12:83 (https://doi.org/10.12688/f1000research.129786.1) Latest published: 23 Jan 2023, 12:83 (https://doi.org/10.12688/f1000research.129786.1)

Introduction

The literature in the biological sciences generally shies away from the concept of rational choice. When the literature alludes to rational choice, it considers it as a cognitive faculty similar to memory, intelligence, linguistic ability, mathematical skill, and so on. As such, rationality is the subject of natural selection akin to these cognitive faculties. Even some economists, whose discipline canonizes rationality as the central pillar in explaining choice, concur and treat rationality as a cognitive faculty and, hence, the product of natural selection (e.g., Robson, 2001; Robson & Samuelson, 2010).

This paper questions this literature. Rationality cannot be another cognitive faculty. It is rather, similar to natural selection, an optimization method:

Core Thesis: Rationality radically differs from cognitive abilities such as memory, intelligence, language faculty, mathematical skill, and so on. Rationality is rather an optimization method of determining the best choice or fit trait.

This core thesis stands irrespective of the many detractors and critics of rational choice theory in the social and behavioral sciences.¹

This paper advances its thesis via a distinction borrowed from set theory (Rai et al., 2012). The distinction is between “binary relators” and “binary operators”. Rationality acts as a binary relator, i.e., as an optimization method. In contrast, any cognitive faculty acts as a binary operator, i.e., as a transformational function. Rationality as an optimization method (binary relator) does not differ from the neo-Darwinian notion of natural selection: either method defines the best choice or fit trait given the constraints. A cognitive faculty as a transformational function (binary operator) simply translates inputs into outputs.

The distinction between rationality and cognitive faculties has great ramifications regarding the theory of evolution. Primarily, the distinction entails that rationality cannot be the subject of evolutionary change. It is rather a constant feature of any organism, i.e., simply what makes an entity a living entity. This implication can be called the “Organismus economicus hypothesis”. It is in contradistinction of the view that organisms do not make decisions, but rather behave according to rules selected by natural selection. This view can be called the “Organismus automaton hypothesis”, which is at the core of neo-Darwinism (see Khalil & Marciano, 2010).

This paper commences with a sharp distinction between the two hypotheses via the distinction between the optimization method, which specifies the best outcome, and the transformation function, which translates inputs to outputs. Then it finds that the neo-Darwinian approach, as a result of treating rationality as a trait selected by the optimization method, commits a self-reference paradox, akin to the Russell paradox (Russell, 1956). This finding questions the core of the neo-Darwnian approach a questioning that is usually avoided out of the specter of metaphysics. This paper registers that there is no basis of such specter and, hence, we should welcome the Organismus economicus hypothesis.

Optimization method contra transformation function

The Organismus automaton hypothesis

The Organismus automaton hypothesis entails the treatment of rationality as a trait, specifically as a cognitive faculty. It is based on the fundamental thesis that the organism operates according to rules, where such rules are the products, ultimately, of natural selection. Such rules are the operational function of faculties such as memory, intelligence, and supposedly rationality. In this picture, the organism follows rules in the final analysis as an automaton.

This paper ignores sophisticated versions of the The Organismus automaton hypothesis (e.g., Godfrey-Smith, 1996, 2009). This allows us to focus, see Figure 1, on the basic minimal schemata of the optimization structure of the Organismus automaton:

Figure 1. The structure of the Organismus automaton.

where E = a set of fitness ends such as the flight speed of zebra (too much flight speed weakens other abilities and too little undermines the survival fitness of the organism); x_it_j = the particular trait (t) and the instinctual behavior requiring certain set of goods (x) (different organisms are characterized by different combinations of t and x); TF_k = the transformational function of level or type k that transforms inputs onto outputs; and OM = the optimization method that ensures that the optimum E (E_i^*) is selected or chosen.

It is crucial to distinguish among three entities in the above schemata: i) the trait-as-input that is an element of the input set on the left-hand side; ii) the trait-as-technology that acts as the binary operator of level k (TF_k) between the input set and the output set; iii) the optimization method (OM) that acts as binary relator.

To use a distinction from set theory, OM is the “binary relator” while TF_k is the “binary operator” (see Rai et al., 2012). The binary relator that acts as OM performs two roles. The first role works within each set, as it ranks the different outputs in a consistent fashion, that is, it specifies which output is better than the other while abstracting from the constraints. For example, it can rank different speeds of flight without considering the constraints. The OM also ranks correspondingly the different inputs. However, what is selected as the optimum cannot be determined without specifying the environmental constraints. This highlights the second role, once the constraints are specified, the OM relates the input with the output sets in a certain way that shows what is the appropriate input that produces the optimum output (E_i*).

In contrast, the binary operator (TF_k) transforms inputs into output according to k-level trait-as-technology. As such, TF_k is neither the optimization method (OM) nor the trait-as-input (x_it_j) that make up the left-hand input set. TF_k is merely the technical listing of outcomes that the TF_k can produce from the given set of inputs.

The symmetry of the two hypotheses

The structure of the Organismus automaton hypothesis is almost identical to the structure of Organismus oeconomicus hypothesis. The input in the former is the population of individuals where each individual is characterized by an input set, whereas each gives rise to a different end, called a phenotype. The input in the latter is the bundle of goods, whereas each gives origin to a different end, called utility.

The Organismus oeconomicus hypothesis, based on standard rational choice, also consists of the binary relator assuring us the production of the optimum, i.e., the employment of OM, and the binary operator that expresses the transformational function, say, at k-level, i.e., the employment of TF_k. Again here, the binary relator (OM) has two roles. As for the first role, the theory of rationality assures us the ends, that is, the utility values, are consistent and, correspondingly, that the inputs are consistently ranked. Consistency depends on many axioms, the most important are two: transitivity and completeness (see Gilboa, 2012; Khalil, 2023). As for the second role, once constraints are determined, the binary relator identifies the optimum end, that is, the optimum utility, and its corresponding set of inputs.

As for the binary operator at k-level (TF_k), there is a set of technologies, institutions, and beliefs transforming each set of inputs into output. As in the case of the Organismus automaton hypothesis, the binary operator merely lists the technical aspect of what is the outcome of each set of inputs if the given TF_k is employed in their transformation. It neither assures any internal consistency nor determines the optimum outcome.

When the optimum is disturbed

Once an optimum is selected by nature or by choice, the optimum is stable as long as shocks disturb neither the set of inputs nor the set of environmental constraints. The stable decision equilibrium, not to be confused with market equilibrium, can be upset if at least one of the following two conditions changes: (i) a mutation of traits-as-inputs (t) or goods (x) takes place; or (ii) a change in the set of environmental constraints.

The set of environmental constraints is implicit in the above schemata. Namely, the binary relator can only select the optimum end considering such set. Let us see the consequence of the change of such set of environmental constraints (C) from C_i to C_c. Nature should select or the individual should choose, as Figure 2 shows, a new set of inputs, x_ct_d^*, corresponding to the new optimum end, E^*_c:

Figure 2. The selection of the optimum end.

However, nature as well as the individual may face hurdles, mainly arising from transitional cost (Marciano & Khalil, 2012; Khalil, 2013), as it tries to adjust. Hence, there can be an adjustment period or, worse, a lock-in arrangement where the status quo dominates. Natural selection or rational choice may opt for the status quo—i.e., the old end, E_i. In this case, natural selection or rational choice (OM) would still select the old inputs, x_it_j. If nothing happens, E_i will continue forever as the “second best” actual outcome, where the OM is denoted as second-best (OM^SB). In contrast, E^*_c continues to be the ideal or “first-best”, where the OM is denoted as first-best (OM^FB). However, what matters, the first-best (E*_c) is suboptimal while the second best (E_i) is optimal—given the transitional cost that secures the lock-in arrangement.

This gap between E^*_c (first-best) and E_i (second-best) may shed light on the controversy between the “hard” and “soft” neo-Darwinian approaches. For the “hard” approach (for example, Dawkins, 1989; Dennett, 1984), OM should surely generate the E^*_j. For the “soft” approach (for example, Gould & Lewontin, 1979), the binary relator is rather OM^SB, generating the seemingly suboptimal outcome E_i. However, as Marciano and Khalil (2012) explain, E_i is actually optimal, if we (as we should) take into account the lock-in arrangements, such as the body-plan of the organism or the technological/institutional/legal make up of the community. E^*_c is optimal in the “ideal” sense, in a world that forcefully ignores transitional cost as if we live in arrangement-free world.

In the given optimization problem above, the binary operator at k-level (TF) cannot be the subject of the optimization method (OM). However, what guarantees that the binary operator is fit or efficient? In the above representation, there is no guarantee. It is taken as a given and, hence, cannot be assessed at this level of selection or choice. It can, however, be the subject of selection or choice when it is the object of rational choice or evolutionary selection. This could be the case, as Figure 3 demonstrates, if the binary operator is acting at a deeper level, say at k+1 level:

Figure 3. The Binary Operator at k+1 Level.

The binary operator, which consists of technology, rules/instructions, or body-plans, involves a hierarchy. It can be at k-level or deeper such as k+1 level. We do not find such a hierarchy with respect to the binary relator (OM) specifying the optimum.

While the elements of the input set, and corollary the output set, are different, the binary relator (OM) does not change, performing the same function irrespective of the level of hierarchy of the binary operator, i.e., whether it is TF_k or TF_k+1. In the above schemata, OM selects or chooses x_iTF_k^* as the optimum input that corresponds to the optimum end, E^*_k. While the binary operator (TF_k) cannot play the role of natural selection (binary relator), it is the product of natural selection at a deeper level, at k+1 level. However, when the binary relator functions, i.e., as OM, it must take the binary operator, whether TF_k or TF_k+1, as given. Such a limited optimization function should not be taken, à la “soft” neo-Darwinians or à la critics of standard economists (see Khalil, 2013), as a shortcoming that undermines or repudiates the notion of optimization per se. To wit, the raison d'être of optimization is the existence of limits taken as given. So, the term “limited optimization” is pleonasm.

There are other nuances, which this paper ignores, of the common structure that underpins the Organismus automaton and Organismus oeconomicus hypothesis. What matters for this paper, the structure of either hypothesis is the same and can handle different kinds of complications and qualifications at secondary and tertiary approximations. What is most important in this proposed structure is that the trait-as-technology, i.e., the binary operator, functions as a transformation function that varies according to the level of the hierarchy. In contrast, the binary relator (OM) remains constant, i.e., irrespective of the level of hierarchy.

The conflation of the binary operator and the binary relator sheds another insight regarding the controversy between “soft” and “hard” neo-Darwinians--as well as between “soft” and “hard” neoclassical economists. This cannot be detailed here. What concerns this paper is the seperation of rationality or any OM from the object of optimization. As shown next, such separation has one important ramification, rationality cannot be a trait.

Could rationality ever be a trait?

The incoherence problem

The proposed distinction between OM, which acts as binary relator, and transformational function (TF_k), which functions as binary operator, entails the incoherence of what can be called “Rationality-qua-Trait Thesis”.

It should be immediately clear that OM (the binary relator) can be either the standard rational choice or, equivalently, the neo-Darwinian natural selection. In contrast, TF_k (the binary operator) is the given technology or cognitive faculty, such as intelligence, memory, and other so on. OM cannot be TF_k, as OM is not about transforming inputs to output in the technical sense.

More importantly, rational choice or OM cannot be trait-as-input, that is, an element of the left-hand inputs set. OM (binary relator) cannot be a member of the set—when its function is about making sure that the elements are consistently ranked. To treat OM as a member of itself leads to self-contradiction, i.e., incoherence.

As shown above, TF_k—such as intelligence, memory, or other cognitive faculties—can be an element of the left-hand inputs set—but then the transformation is taking place at a deeper level. There is a hierarchy of technology or body-plan. The transformation function (TF) cannot apply to OM, as OM cannot become a member of the left-hand inputs set. There is no hierarchy of rationality as the case with TF. What applies to TF cannot apply to OM. And if we conceive OM as a member of the inputs set, this leads to incoherence à la Russell Paradox.

The Russell Paradox

The Russell Paradox (Russell, 1956) emerges when one conceives a set as a member of itself. To treat rational choice as a member of the set that is the object of rational choice is an example of the Russell Paradox.

One helpful illustration of the Russell Paradox is the well-known Cretan liar paradox and, better, the Barber Paradox (Irvine & Deutsch, 2021). The only barber in a village has a sign posted in his shop that states, “I cut the hair of everyone in the village that does not cut his own hair.” But who cuts the hair of the barber? If he cuts his own hair, then the barber cannot cut it. And if he does not cut his own hair, then the barber cuts it. Such a self-contradiction arises from treating the set, which is the barber’s statement, as a member of itself. Such treatment entails that the barber is an element of the set of people who do not cut their own hair, on one hand, and the barber is the set itself as the one who cuts the hair of such people, on the other.

The Russell Paradox arises from what philosophers recognize as the problem of self-reference. In the case of the Rationality-qua-Trait Thesis, it treats rationality both as OM as well as an element of the set that is the subject of OM. This self-reference is best illustrated by some of the drawings of M.C. Escher (see Hofstadter, 1980). The first role of the binary relator (OM) is to make sure that the output is consistently ranked and, corollary, the corresponding inputs are also consistently ranked. Such an organization of inputs cannot also include OM: how could the OM calls for the substitution of one input in favor of another when the OM itself is one such input?

Who’s afraid of the Organismus Oeconomicus hypothesis?

The implication of the above analysis is that rationality cannot be selected or chosen. Rationality cannot be a trait such as musical skill, intelligence, or any cognitive faculty. As an OM, it is analytically akin to natural selection.

It is obvious that some species, such as Homo sapiens, behave rationally. A difficulty arises when a researcher draws a line between such species and supposedly species deemed to be non-rational. Such a line, most obviously, leads to the creation of a fictitious dichotomy that juxtaposes “rational species” and “non-rational species.” This dichotomy is fictitious as it supposes a natural set that includes species such as bacteria and, say, lower primates as having a common trait that sets them apart from another set that includes only upper primates. To avoid such fictious sets, researchers need to examine whether rationality is a trait in the first place. The Organismus oeconomicus hypothesis certainly avoids such pittfalls, as it ascribes rationality to all living entities (Khalil, 2023).

However, if we treat rationality as OM, and hence, cannot be seen as a trait, this gives rise to questions about the status of rationality with respect to living entities, if not to questions that conjure the specter of metaphysics—the specter of conceiving rationality as existing separately from living entities.

Biologists need not fear the Organismus oeconomicus hypothesis for at least five reasons.

1. The rationality concept, at least as used by economists (e.g., Becker, 1978; Gilboa, 2012; Khalil, 2023), amounts to a rule or a method that does not specify any particular content—not to mention free will, imagination, creative action, or ambition. Rational choice means organisms generally make the best decision possible given the environmental constraints and their technological capacities that include cognitive faculties, physiological traits, technologies, and institutions.
2. Biologists and psychologists usually restrict rationality to mental or cognitive processes (e.g., Chater et al., 2018; Felin et al., 2017). They conclude that organisms with limited cognitive processes, and especially plants and other brainless organisms, cannot be rational. However, once one understands rationality properly, one cannot conflate it with cognitive faculties (see Khalil, 2010).
3. Biologists (e.g., Gardner, 2009) are afraid of what philosophers call “reification”—that is, the thinking of an idea such as rationality and supposing it is true, i.e., choices made by organisms express rational choice. This raises the specter of metaphysics (see Winn, 1939)—the belief in an “uncaused cause” (Dennett, 1995). For instance, the supposed reification of rationality may conjure up uncaused cause and, hence, uphold creationism, that is, the idea there must be an external agent (e.g., a god) who created rationality. However, the specter of reification need not arise if one can trace rationality to a defining feature of being a living being. But this task is outside the scope of this paper.
4. Biologists who use the foraging theory pioneered by Eric Charnov (e.g., 1976; see Stephens & Krebs, 1986) or who employ the tools of “bioeconomics” (e.g., Ghiselin, 1974; see also Tullock, 1971, 1994; Khalil & Marciano, 2010) already use cost-benefit calculations, that is, rational choice. A few biologists have recently taken the first step to recognizing openly the relevance of rationality to the understanding of behavior or organisms (e.g., Vermeij, 2004; Hurley & Nudds, 2006).
5. Biologists implicitly employ the rational choice approach when they explain behavior as elastic, that is, as responsive to changes in environmental constraints. They call such elasticity “phenotypic plasticity” (Gould, 1997, 2002; Stanley, 1979; Matsuda, 1987; West-Eberhard, 1989; Raff, 1996; Müller & Newman, 2003; Hall et al., 2004; DeWitt & Scheiner, 2004). They are making great strides in showing how even invertebrate organisms make decisions in light of uncertainty (e.g., Oberhauser & Czaczkes, 2018). They are documenting how animals generally make decisions in reaction to the so-called “contrast effect” (e.g., McNamara et al., 2013).

Regarding phenotypic plasticity, biologists need to recognize explicitly and openly the fact that it amounts to rational choice. As shown elsewhere (Khalil, 2009, 2010), rational choice theory is simply the proposition that the organism’s choice changes in light of changes in environmental constraints or, in short, incentives. With each choice, the organism maximizes the benefit (fitness) given the cost or, what is the same thing, minimizes the cost given the benefit.

Conclusions

1. There is an incongruent gap in the natural sciences. On one hand, the sciences that focus on the study of non-human organisms do not largely give weight to rationality. On the other hand, the sciences, especially economics, that focus on the study of human organisms pay great attention to rationality.
2. The sciences that focus on non-human organisms do not need to appeal to rationality, as they largely appeal to natural selection as the optimization method. Still, they have to explain rationality if they are natural sciences, i.e., sciences that cannot exclude humans from nature. Such sciences, if pushed, tend to explain rationality as a trait—i.e., similar to intelligence and other cognitive faculties. However, such explanation leads to the self-reference problem, a variety of incoherence à la Russell paradox: how could rationality that is an optimization method be a trait, i.e., the subject of natural selection that is an optimization method?
3. We can easily avoid the Russell paradox regarding rational choice or any optimization method if we employ a distinction from set theory, namely, the difference between “binary relators” and “binary operators”.
4. Rationality cannot be a trait given that it is a binary relator that allows us to identify the optimum. In contrast, cognitive faculties are traits, as they are binary operators that transform inputs into outputs.
5. Once we distinguish between binary relators and binary operators, we can conceive rationality as an OM (binary relator) that cannot be a trait (binary operator). Hence, there would be no need to appeal to another OM to explain its origin.

Data availability

No data are associated with this article.

Acknowledgments

Older versions received comments from Steven Orzack, Ulrich Witt, Steve Abedon, Jack Vromen, Timothy Crippen, Elliott Sober, Casey Mulligan, Franjo Weissing, Yew-Kwang Ng, Martin Burd, Avi Waksberg, Deby Cassill, David Haig, and especially Davide Vecchi. It also received comments from participants of sessions at the Australian National University, Monash University, the Konrad Lorenz Institute of Evolution and Cognition Research, the European Association of Evolutionary Political Economy, and the International Society for the History, Philosophy and Social Studies of Biology. The paper benefited from the research assistance of Steven Gardner, Michael Dunstan, and Maks Sipowicz.

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Footnotes

1 This core thesis—viz., rational choice is a method of selecting among options--is widely accepted (e.g., Becker, 1978; Gilboa, 2012; Khalil, 2023). However, this should not entail that rationality is an exhaustive description of all human behavior. Behavior may involve imagination, creativity, aspiration, or what economists recognize as “entrepreneurship” that goes beyond mechanical rules of optimization (see Khalil, 1997, 2010). Further, behavior involves biases that arise from failed heuristics (see Thaler & Sunstein, 2009; Kahneman, 2011; Khalil, 2022; Khalil & Amin, 2022). However, these issues need not undermine the rationality concept—but may in fact open opportunities to expand it.

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School of Economics, Administration and Public Policy, Doha Institute for Graduate Studies, Doha, 70, Qatar

Elias L. Khalil
Roles: Conceptualization, Formal Analysis, Writing – Original Draft Preparation, Writing – Review & Editing

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No competing interests were disclosed.

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Khalil EL. Is rationality a cognitive faculty? [version 1; peer review: 1 approved with reservations, 1 not approved]. F1000Research 2023, 12:83 (https://doi.org/10.12688/f1000research.129786.1)

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Open Peer Review

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PUBLISHED 23 Jan 2023

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1

Reviewer Report 23 Aug 2025

Sergio Alejandro Rodríguez Jerez, Universidad Sergio Arboleda, Bogotá, Bogota, Colombia

Approved with Reservations

https://doi.org/10.5256/f1000research.142498.r400468

Summary Evaluation

This article presents a bold and original thesis: rationality is not a cognitive trait but rather a binary relator—an optimization method—that functions analogously to natural selection. The author’s effort to distinguish between binary operators (transformational ... Continue reading

Summary Evaluation

This article presents a bold and original thesis: rationality is not a cognitive trait but rather a binary relator—an optimization method—that functions analogously to natural selection. The author’s effort to distinguish between binary operators (transformational functions) and binary relators (optimization processes) offers a novel theoretical lens. The paper is interdisciplinary and engages deeply with set theory, evolutionary theory, and decision science.
However, the article falls short in integrating contemporary neuroscientific and computational perspectives that are essential to a robust understanding of rationality. Addressing these omissions would significantly improve the paper’s clarity, relevance, and theoretical depth.

Major Concerns and Suggestions

1. Corticocentric Assumptions
The article implicitly associates cognitive faculties—and by contrast, rationality—with cortical operations. This stance neglects foundational insights from neuropsychoanalysis and affective neuroscience, particularly the work of Mark Solms, who argues that rational behavior emerges from subcortical affective systems rather than from cortical cognitive faculties alone. Solms explicitly identifies consciousness and rational evaluation with homeostatic regulation and subjective feeling, not abstract cortical computation.

Suggestion: The author should engage with this body of work to clarify whether rationality, as an optimization method, can be decoupled from conscious, sentient, and affective processes, as Solms argues.

2. Lack of Bayesian Formalization
Although the paper discusses rationality as a form of optimization, it does not address the well-established Bayesian brain hypothesis or the free-energy principle (Friston). These models formalize rationality as probabilistic inference under uncertainty—a process that is dynamic, adaptive, and not tied to any fixed cognitive trait. This approach aligns with the idea of rationality as a “method” but provides a stronger computational and neuroscientific foundation.
Suggestion: At minimum, include a discussion of Bayesian rationality to contextualize the relator-operator distinction within ongoing models of brain function.

3. Neglect of Non-Shannonian Computation
The author assumes a somewhat abstract, symbolic notion of computation. However, recent research by Miguel Nicolelis challenges the dominance of Shannon-based signal processing models and introduces the notion of two complementary modes of neural computation:

Shannonian: signal-based, channel-like transmission;
Boolean-like: emergent logical operations within distributed neural ensembles.

This framework supports the author’s relator/operator distinction but grounds it in empirically observed computational structures of the brain.
Suggestion: Reference Nicolelis’ theory of dual computation to substantiate the distinction between transformational (operator) and optimization (relator) mechanisms in embodied systems.

Positive Contributions

The distinction between binary relators and binary operators is conceptually useful and has potential applications in evolutionary biology and economic modeling.
The analogy between rational choice and natural selection as optimization methods is compelling.
The article offers a valuable philosophical challenge to the idea that rationality evolves as a discrete trait.

Conclusion and Recommendation

This article makes a significant theoretical contribution by challenging widely held assumptions about the nature of rationality. However, to meet the standards of interdisciplinary rigor, it must engage more explicitly with current neuroscientific and computational research. These revisions do not require rewriting the central thesis but rather contextualizing and supporting it more effectively.

Is the topic of the opinion article discussed accurately in the context of the current literature?

Yes
Are all factual statements correct and adequately supported by citations?

Partly
Are arguments sufficiently supported by evidence from the published literature?

Partly
Are the conclusions drawn balanced and justified on the basis of the presented arguments?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Philosophy of Mind, Sentient Rationality, Neurosemiotics, Cognitive and Affective Neuroscience, Artificial Intelligence and Human Cognition, Epistemology of Innovation, Transemiosis, and the Philosophy of Technology.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Views

11

Reviewer Report 24 Jan 2024

Piotr Kozak, University of Bialystok, Białystok,, Poland

Not Approved

https://doi.org/10.5256/f1000research.142498.r232942

The paper focuses on the concept of rationality in economics and (probably) cognitive psychology. According to the main thesis, rationality is not a cognitive faculty. Instead, it is a method of optimization. The author argues that rationality (as a method ... Continue reading

The paper focuses on the concept of rationality in economics and (probably) cognitive psychology. According to the main thesis, rationality is not a cognitive faculty. Instead, it is a method of optimization. The author argues that rationality (as a method of optimization) can be cashed out in terms of binary relators, i.e., binary relations partially ordering a set. In contrast, cognitive faculties should be understood as binary operators, i.e., transformation functions. According to the author, such a distinction gives a reason to believe that rationality (in terms of an optimization method) is “a constant feature of any organism, i.e., simply what makes an entity a living entity.”
Although I deeply admire the wide scope and gravity of the author’s analyses, I have serious objections to the way the analyses are presented in the paper. First, it is challenging to assess the paper's scientific domain: economics, cognitive psychology, epistemology, theory of evolution, or all of them. It does not have to be a problem. One of the main advantages of the paper is that it attempts to cover (probably) all these areas. However, it is done without going into any serious debate with the positions discussed in these areas. For instance, there is no reference to the so-called Great Rationality Debate, the positions of Gigenrenzer and Stanovich are not even mentioned, etc. Thus, it is very difficult to say what kind of ideas the author debates with. Not to mention the fact that the author doesn’t give any hints or references regarding the positions he argues against.
Second, the author opposes the idea that rationality is a cognitive faculty or a skill. It’s not clear what kind of a position he argues against. In philosophy and cognitive psychology, we commonly distinguish between the concept of rationalism in descriptive and normative understanding of the term. The descriptive understanding of rationality covers, e.g., the idea of tests on rationality one can be better or worse at. The normative understanding covers, e.g., the logical validity of an argument. Both understandings are not equal but are complementary. For instance, one can act irrationally, but a product of one’s actions, by chance, can be rational. It is unclear what kind of novel feature or description of rationality the distinction between binary relators and binary operators brings to the table.
Third, the distinction between binary relators and binary operators is unclear. Although the idea that the concepts of binary relators and transformation functions are not the same is correct, it doesn’t follow that these concepts are opposite. Binary relators and binary operators are both some kind of a binary relation since every function is a relation. Thus, even if rationality is a binary relator, it does not follow that it cannot be a binary operator.
Fourth, the argument from the Russell’s Paradox seems invalid. It would apply to the argument, if we assumed that rationality cannot be a cognitive skill. However, that is something that has to be proven by this very argument.
Fifth, the conclusion that evolution is somehow rational in terms of being an optimized method of selection is far unsupported. The author does not engage in discussions with contemporary authors in evolution theory. At this point, it is rather an author’s statement, which we can take at its face value or not, but not a conclusion of an argument.
To sum up, although the paper shows some promise, it does not seem likely to be presenting a sound and well-supported argument. I strongly recommend narrowing down the paper's goal and focusing on a certain part of a debate in economics and/or cognitive psychology. The author should supplement the paper with the context of the debate. He should at least mention the authors he is discussing with or against. It would make his arguments clearer and more understandable.

Is the topic of the opinion article discussed accurately in the context of the current literature?

No
Are all factual statements correct and adequately supported by citations?

No
Are arguments sufficiently supported by evidence from the published literature?

No
Are the conclusions drawn balanced and justified on the basis of the presented arguments?

No

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Philosophy, Cognitive Psychology

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

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Version 1

VERSION 1 PUBLISHED 23 Jan 2023

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Version 1 23 Jan 23	read	read

Piotr Kozak, University of Bialystok, Białystok,, Poland
Sergio Alejandro Rodríguez Jerez, Universidad Sergio Arboleda, Bogotá, Colombia

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Reviewer Report

1 Views

23 Aug 2025 | for Version 1

Sergio Alejandro Rodríguez Jerez, Universidad Sergio Arboleda, Bogotá, Bogota, Colombia

1 Views Cite this report Responses(0)

Approved With Reservations

Summary Evaluation

This article presents a bold and original thesis: rationality is not a cognitive trait but rather a binary relator—an optimization method—that functions analogously to natural selection. The author’s effort to distinguish between binary operators (transformational functions) and binary relators (optimization processes) offers a novel theoretical lens. The paper is interdisciplinary and engages deeply with set theory, evolutionary theory, and decision science.
However, the article falls short in integrating contemporary neuroscientific and computational perspectives that are essential to a robust understanding of rationality. Addressing these omissions would significantly improve the paper’s clarity, relevance, and theoretical depth.

Major Concerns and Suggestions

1. Corticocentric Assumptions
The article implicitly associates cognitive faculties—and by contrast, rationality—with cortical operations. This stance neglects foundational insights from neuropsychoanalysis and affective neuroscience, particularly the work of Mark Solms, who argues that rational behavior emerges from subcortical affective systems rather than from cortical cognitive faculties alone. Solms explicitly identifies consciousness and rational evaluation with homeostatic regulation and subjective feeling, not abstract cortical computation.

Suggestion: The author should engage with this body of work to clarify whether rationality, as an optimization method, can be decoupled from conscious, sentient, and affective processes, as Solms argues.

2. Lack of Bayesian Formalization
Although the paper discusses rationality as a form of optimization, it does not address the well-established Bayesian brain hypothesis or the free-energy principle (Friston). These models formalize rationality as probabilistic inference under uncertainty—a process that is dynamic, adaptive, and not tied to any fixed cognitive trait. This approach aligns with the idea of rationality as a “method” but provides a stronger computational and neuroscientific foundation.
Suggestion: At minimum, include a discussion of Bayesian rationality to contextualize the relator-operator distinction within ongoing models of brain function.

3. Neglect of Non-Shannonian Computation
The author assumes a somewhat abstract, symbolic notion of computation. However, recent research by Miguel Nicolelis challenges the dominance of Shannon-based signal processing models and introduces the notion of two complementary modes of neural computation:

Shannonian: signal-based, channel-like transmission;
Boolean-like: emergent logical operations within distributed neural ensembles.

This framework supports the author’s relator/operator distinction but grounds it in empirically observed computational structures of the brain.
Suggestion: Reference Nicolelis’ theory of dual computation to substantiate the distinction between transformational (operator) and optimization (relator) mechanisms in embodied systems.

Positive Contributions

The distinction between binary relators and binary operators is conceptually useful and has potential applications in evolutionary biology and economic modeling.
The analogy between rational choice and natural selection as optimization methods is compelling.
The article offers a valuable philosophical challenge to the idea that rationality evolves as a discrete trait.

Conclusion and Recommendation

This article makes a significant theoretical contribution by challenging widely held assumptions about the nature of rationality. However, to meet the standards of interdisciplinary rigor, it must engage more explicitly with current neuroscientific and computational research. These revisions do not require rewriting the central thesis but rather contextualizing and supporting it more effectively.

Is the topic of the opinion article discussed accurately in the context of the current literature?

Yes
Are all factual statements correct and adequately supported by citations?

Partly
Are arguments sufficiently supported by evidence from the published literature?

Partly
Are the conclusions drawn balanced and justified on the basis of the presented arguments?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Philosophy of Mind, Sentient Rationality, Neurosemiotics, Cognitive and Affective Neuroscience, Artificial Intelligence and Human Cognition, Epistemology of Innovation, Transemiosis, and the Philosophy of Technology.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

Respond to this report

Responses (0)

Back to all reports

Reviewer Report

11 Views

24 Jan 2024 | for Version 1

Piotr Kozak, University of Bialystok, Białystok,, Poland

11 Views Cite this report Responses(0)

Not Approved

The paper focuses on the concept of rationality in economics and (probably) cognitive psychology. According to the main thesis, rationality is not a cognitive faculty. Instead, it is a method of optimization. The author argues that rationality (as a method of optimization) can be cashed out in terms of binary relators, i.e., binary relations partially ordering a set. In contrast, cognitive faculties should be understood as binary operators, i.e., transformation functions. According to the author, such a distinction gives a reason to believe that rationality (in terms of an optimization method) is “a constant feature of any organism, i.e., simply what makes an entity a living entity.”
Although I deeply admire the wide scope and gravity of the author’s analyses, I have serious objections to the way the analyses are presented in the paper. First, it is challenging to assess the paper's scientific domain: economics, cognitive psychology, epistemology, theory of evolution, or all of them. It does not have to be a problem. One of the main advantages of the paper is that it attempts to cover (probably) all these areas. However, it is done without going into any serious debate with the positions discussed in these areas. For instance, there is no reference to the so-called Great Rationality Debate, the positions of Gigenrenzer and Stanovich are not even mentioned, etc. Thus, it is very difficult to say what kind of ideas the author debates with. Not to mention the fact that the author doesn’t give any hints or references regarding the positions he argues against.
Second, the author opposes the idea that rationality is a cognitive faculty or a skill. It’s not clear what kind of a position he argues against. In philosophy and cognitive psychology, we commonly distinguish between the concept of rationalism in descriptive and normative understanding of the term. The descriptive understanding of rationality covers, e.g., the idea of tests on rationality one can be better or worse at. The normative understanding covers, e.g., the logical validity of an argument. Both understandings are not equal but are complementary. For instance, one can act irrationally, but a product of one’s actions, by chance, can be rational. It is unclear what kind of novel feature or description of rationality the distinction between binary relators and binary operators brings to the table.
Third, the distinction between binary relators and binary operators is unclear. Although the idea that the concepts of binary relators and transformation functions are not the same is correct, it doesn’t follow that these concepts are opposite. Binary relators and binary operators are both some kind of a binary relation since every function is a relation. Thus, even if rationality is a binary relator, it does not follow that it cannot be a binary operator.
Fourth, the argument from the Russell’s Paradox seems invalid. It would apply to the argument, if we assumed that rationality cannot be a cognitive skill. However, that is something that has to be proven by this very argument.
Fifth, the conclusion that evolution is somehow rational in terms of being an optimized method of selection is far unsupported. The author does not engage in discussions with contemporary authors in evolution theory. At this point, it is rather an author’s statement, which we can take at its face value or not, but not a conclusion of an argument.
To sum up, although the paper shows some promise, it does not seem likely to be presenting a sound and well-supported argument. I strongly recommend narrowing down the paper's goal and focusing on a certain part of a debate in economics and/or cognitive psychology. The author should supplement the paper with the context of the debate. He should at least mention the authors he is discussing with or against. It would make his arguments clearer and more understandable.

Is the topic of the opinion article discussed accurately in the context of the current literature?

No
Are all factual statements correct and adequately supported by citations?

No
Are arguments sufficiently supported by evidence from the published literature?

No
Are the conclusions drawn balanced and justified on the basis of the presented arguments?

No

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Philosophy, Cognitive Psychology

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

Respond to this report

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Is rationality a cognitive faculty?

Abstract

Keywords

Introduction

Optimization method contra transformation function

The Organismus automaton hypothesis

Figure 1. The structure of the Organismus automaton.

The symmetry of the two hypotheses

When the optimum is disturbed

Figure 2. The selection of the optimum end.

Figure 3. The Binary Operator at k+1 Level.

Could rationality ever be a trait?

The incoherence problem

The Russell Paradox

Who’s afraid of the Organismus Oeconomicus hypothesis?

Conclusions

Data availability

Acknowledgments

References

Footnotes

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