A Generative View of Rationality and Growing Awareness†

Abstract

In this paper we contrast bounded and ecological rationality with a proposed alternative, generative rationality. Ecological approaches to rationality build on the idea of humans as “intuitive statisticians” while we argue for a more generative conception of humans as “probing organisms.” We first highlight how ecological rationality’s focus on cues and statistics is problematic for two reasons: (a) the problem of cue salience, and (b) the problem of cue uncertainty. We highlight these problems by revisiting the statistical and cue-based logic that underlies ecological rationality, which originate from the misapplication of concepts in psychophysics (e.g., signal detection, just-noticeable-differences). We then work through the most popular experimental task in the ecological rationality literature—the city size task—to illustrate how psychophysical assumptions have informally been linked to ecological rationality. After highlighting these problems, we contrast ecological rationality with a proposed alternative, generative rationality. Generative rationality builds on biology—in contrast to ecological rationality’s focus on statistics. We argue that in uncertain environments cues are rarely given or available for statistical processing. Therefore we focus on the psychogenesis of awareness rather than psychophysics of cues. For any agent or organism, environments “teem” with indefinite cues, meanings and potential objects, the salience or relevance of which is scarcely obvious based on their statistical or physical properties. We focus on organism-specificity and the organism-directed probing that shapes awareness and perception. Cues in teeming environments are noticed when they serve as cues-for-something, requiring what might be called a “cue-to-clue” transformation. In this sense, awareness toward a cue or cues is actively “grown.” We thus argue that perception might more productively be seen as the presentation of cues and objects rather than their representation. This generative approach not only applies to relatively mundane organism (including human) interactions with their environments—as well as organism-object relationships and their embodied nature—but also has significant implications for understanding the emergence of novelty in economic settings. We conclude with a discussion of how our arguments link with—but modify—Herbert Simon’s popular “scissors” metaphor, as it applies to bounded rationality and its implications for decision making in uncertain, teeming environments.

Opaque decision-making in organizations

“…Many phenomena – organizational phenomena are very representative – require generative rationality. Indeed, in uncertain environments, the cues are not “out there” but they require perceptual mechanism, and hence they are the product of the interaction of the decision maker – to be intended as a biological organism – with the environment (Mastrogiorgio et al , 2022; Felin and Koenderink, 2022). Opacity, as presented here, is a theoretical construct valid for such decision rules that admit a problem.…”

Microfoundations of ecosystems: The theory-led firm and capability growth

“…This is quite different from the common focus on information processing and the idea of scanning one’s surroundings, as these approaches inherently do not allow for unique sources of value to “pop out,” to catch one’s attention. Thus, we build on the premise that sensing and observation are always hypothesis-driven (Popper, 1967; also see Felin and Koenderink, 2022; Teece et al, 2016): what one sees or picks out in the environment depends on the theory or hypothesis one has in mind. As noted by Popper (1967), “we learn from our hypotheses what kind of observations we ought to make: whereto we ought to direct our attention” (p. 346).…”

Bounded rationality, enactive problem solving, and the neuroscience of social interaction

“…The latter deals solely with analytic judgements and choices, and it is not interested in how to frame problems, set goals and develop a suitable course of action ( Viale, 2021 , 2023a , b ). In the SEU approach empirical phenomena lose their epistemic and material identity and are symbolically deconstructed and manipulated as cues with only statistical meaning (tallied, weighted, sequenced and ordered) ( Felin and Koenderink, 2022 ).…”