Bounded Rationality and Artificial Intelligence: Grounding Human-Machine Collaboration in the Prospect of Artificial Intelligibility

Michael W. Raphael1, Nga Than1

1 The Graduate Center, City University of New York, New York City,  United States

Abstract: Bounded rationality is typically understood with respect to three limitations: time, information, and processing capacity (Simon, [1947] 1997; 1983; Cf. Kahneman, 2011). In response to these external constraints on human thinking, approaches to artificial intelligence have been developed in order to compensate for these limitations through the genesis of design thinking (Simon, 1981). Design thinking favors simplicity on the principle of near decomposability, which allows the breaking of complex systems down into part-whole relationships while still retaining the sense of their overall hierarchical organization (Simon, [1968] 1996; 1995). However, since the 1960s, design thinking has undergone a period of rationalization in which this sense of near decomposability has been reduced to total decomposability (Boden, 2016). This is a shift in which the design of heuristic problem-solving has become subjugated to the design of algorithms where heuristics are thought of as a sub-class of problem-solving methods. As a matter of means-ends relationships, this is a shift from satisficing a solution in a manner compatible with human problem-solving toward the optimization of a solution in a manner that is potentially unintelligible to human problem-solvers. This raises the question of the degree to which human-machine collaborations can be meaningful at the level of human participation rather than reducing human contributions to models of machine problem-solving. In that respect, this paper proposes a framework to evaluate the degree to which artificial intelligence achieves artificial intelligibility. This framework of artificial intelligibility operationalizes five criteria to describe the adaptive problem-solving capacity of a machine to meaningfully participate in the constitutive socially situated character of practical ritualistic activity, typically undertaken by human problem-solvers in relation to artifacts of design and discourse (Goffman, 1967; 1974; Brown, 2014; Raphael, 2017; Cf. Turner, 2018). Drawing on literature in the field of cognitive sociology, the paper details how the constitutive socially situated character of practical ritualistic activity describes criteria by which a machine can use, respond to, and invite the articulation of language, abstractions, and concepts in which its intelligence has to take into account the oscillation of the conditions of meaningfulness in an ongoing course of activity. Using these criteria, we argue and conclude that the study of human-computer interaction and its evaluation of the prospects for collaboration require (re)focusing on the socially situated character of discourse.

Keywords: artificial intelligibility, heuristic problem-solving, design thinking, situational rationality, practical ritualistic activity, cognitive sociology


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