We discuss opportunities in applying the resource-rationality framework toward answering questions in emotion and mental health research. These opportunities rely on characterization of individual differences in cognitive strategies; an endeavor that may be at odds with the normative approach outlined in the target article. We consider ways individual differences might enter the framework and the translational opportunities offered by each.

Resource rationality is useful for choosing between models with the same cognitive constraints but cannot settle fundamental disagreements about what those constraints are. We argue that sampling is an especially compelling constraint, as optimizing accumulation of evidence or hypotheses minimizes the cost of time, and there are well-established models for doing so which have had tremendous success explaining human behavior.

Resource-rational analysis would profit from being integrated more explicitly with an evolutionary psychological perspective. In particular, by taking more strongly into consideration the fact that efficiency considerations are a key driver of the evolution of human and animal minds, it becomes clearer: (1) why it is reasonable to assume that cognitive mechanisms trade-off accuracy against effort, (2) how this trade-off occurs, and (3) how to overcome some of the challenges of resource-rational analysis.

Comprehensive accounts of resource-rational attempts to maximise utility shouldn't ignore the demands of constructing utility representations. This can be onerous when, as in humans, there are many rewarding modalities. Another thing best not ignored is the processing demands of making functional activity out of the many degrees of freedom of a body. The target article is almost silent on both.

The purpose of human cognition depends on the problem people try to solve. Defining the purpose is difficult, because people seem capable of representing problems in an infinite number of ways. The way in which the function of cognition develops needs to be central to our theories.

Lieder and Griffiths rightly urge that computational cognitive models be constrained by resource usage, but they should go further. The brain's primary function is to regulate resource usage. As a consequence, resource usage should not simply select among algorithmic models of “aspects of cognition.” Rather, “aspects of cognition” should be understood as existing in the service of resource management.

The commentaries raised questions about normativity, human rationality, cognitive architectures, cognitive constraints, and the scope or resource rational analysis (RRA). We respond to these questions and clarify that RRA is a methodological advance that extends the scope of rational modeling to understanding cognitive processes, why they differ between people, why they change over time, and how they could be improved.

Rationalization occurs when a person has performed an action and then concocts the beliefs and desires that would have made it rational. Then, people often adjust their own beliefs and desires to match the concocted ones. While many studies demonstrate rationalization, and a few theories describe its underlying cognitive mechanisms, we have little understanding of its function. Why is the mind designed to construct post hoc rationalizations of its behavior, and then to adopt them? This may accomplish an important task: transferring information between the different kinds of processes and representations that influence our behavior. Human decision making does not rely on a single process; it is influenced by reason, habit, instinct, norms, and so on. Several of these influences are not organized according to rational choice (i.e., computing and maximizing expected value). Rationalization extracts implicit information – true beliefs and useful desires – from the influence of these non-rational systems on behavior. This is a useful fiction – fiction, because it imputes reason to non-rational psychological processes; useful, because it can improve subsequent reasoning. More generally, rationalization belongs to the broader class of representational exchange mechanisms, which transfer information between many different kinds of psychological representations that guide our behavior. Representational exchange enables us to represent any information in the manner best suited to the particular tasks that require it, balancing accuracy, efficiency, and flexibility in thought. The theory of representational exchange reveals connections between rationalization and theory of mind, inverse reinforcement learning, thought experiments, and reflective equilibrium.

We agree with Cushman that rationalizations are the product of biological adaptations, but we disagree about their function. The data available do not show that rationalizations allow us to reason better and make better decisions. The data suggest instead that rationalizations serve reputation management goals, and that they affect our behaviors because we are held accountable by our peers.

Cushman claims that post hoc rationalization of habitual behavior can improve future reasoning. His characterization of habits includes two components: (1) habitual behavior is a non-rational process, and (2) habitual behavior is sometimes rationalized. We argue that Cushman fails to show any habits that are apt targets for rationalization. Thus, it's unclear when – if ever – rationalizing habits would improve reasoning.

Cushman argues that “rationalization is rational.” We show that there is reasonable empirical clinical and forensic psychological evidence to support viewing rationalization as a quite suboptimal defense mechanism. Rationalization has been found to be associated not only with poorer emotional development, but also with a broad range of antisocial behavior, including not only shoplifting, but also pedophilia and murder.

In making the case that “rationalization is rational,” Cushman downplays its signature liability: Rationalization exposes a person to the hazard of delusion and self-sabotage. In paradigm cases, rationalization undermines instrumental rationality by introducing inaccuracies into the representational map required for planning and effective agency.

If rationalization were ubiquitous, it would undermine a fundamental premise of human discourse. A review of key evidence indicates that rationalization is rare and confined to choices among comparable options. In contrast, reasoning is pervasive in human decision making. Within the constraints of reasoning, rationalization may operate in ambiguous situations. Studying these processes requires careful definitions and operationalizations.

In this commentary, I highlight the relevance of Cushman's target article for the popular dual-process framework of thinking. I point to the problematic characterization of rationalization in traditional dual-process models and suggest that in line with recent advances, Cushman's rational rationalization account offers a way out of the rationalization paradox.

According to Cushman, rationalization occurs when a person has performed an action and then concocts beliefs and desires that would have made it rational. We argue that this isn't the paradigmatic form of rationalization. Consequently, Cushman's explanation of the function and usefulness of rationalization is less broad-reaching than he intends. Cushman's account also obscures some of rationalization's pernicious consequences.

Although rationalization about one's own beliefs and actions can improve an individual's future decisions, beliefs can provide other benefits unrelated to their epistemic truth value, such as group cohesion and identity. A model of resource-rational cognition that accounts for these benefits may explain unexpected and seemingly irrational thought patterns, such as belief polarization.

This commentary extends the target article's useful concepts to consider collective instances of representational exchange. When groups collectively rationalize their actions, entire networks of beliefs and desires can be created and maintained in the form of shared moral narratives and system-justifying ideologies. These collective rationalization cases illustrate how adaptive advantages can come at the expense of the truth.

The action-based model of cognitive dissonance proposes an adaptive function for rationalization that differs from the one offered by Cushman. The one proposed by Cushman is concerned more with the cold construction of cognitions, whereas the one proposed by the action-based model is a motivated protection of a strongly held cognition.

Cushman uses rationalization to refer to people's explanations for their own actions. In system justification theory, scholars use the same term to refer to people's efforts to cast their current status quo in an exaggeratedly positive light. We try to reconcile these two meanings, positing that system justification could result from people trying to explain their own failure to take action to combat inequality. We highlight two novel and contested predictions emerging from this interpretation.

Cushman argues that the function of rationalization is to attribute mental representations to ourselves, thereby making these representations available for future planning. I argue that such attribution is often not necessary and sometimes maladaptive. I suggest a different explanation of rationalization: making representations available to other agents, to facilitate cooperation, transmission, and the ratchet effect that underlies cumulative cultural evolution.