Today, diagnostic reasoning combines common and specialized knowledge, elements of numeracy, some facility with the basics of probability theory and, last but not least, ease in interactions with AI tools. We present procedures and tools for constructing trees that lead to understandable, transparent, simple, and robust classifications and decisions. These tools are more heuristic than optimal models, inspired by the perspective of Bounded Rationality. We describe how the tenets of Bounded Rationality provide a framework for the human-machine interaction this paper is devoted to. We claim that, because of this rationality, our proposed tools facilitate machine-aided decision making that is smooth, transparent and successful.

Martignon, L., Erickson, T., Viale, R. (2022). Transparent, simple and robust fast-and-frugal trees and their construction. FRONTIERS IN HUMAN DYNAMICS, 4 [10.3389/fhumd.2022.790033].

Transparent, simple and robust fast-and-frugal trees and their construction

Viale, R
2022

Abstract

Today, diagnostic reasoning combines common and specialized knowledge, elements of numeracy, some facility with the basics of probability theory and, last but not least, ease in interactions with AI tools. We present procedures and tools for constructing trees that lead to understandable, transparent, simple, and robust classifications and decisions. These tools are more heuristic than optimal models, inspired by the perspective of Bounded Rationality. We describe how the tenets of Bounded Rationality provide a framework for the human-machine interaction this paper is devoted to. We claim that, because of this rationality, our proposed tools facilitate machine-aided decision making that is smooth, transparent and successful.
Articolo in rivista - Articolo scientifico
Arbor; fast-and-frugal tree; plugin; tree; uncertainty;
English
2022
4
790033
none
Martignon, L., Erickson, T., Viale, R. (2022). Transparent, simple and robust fast-and-frugal trees and their construction. FRONTIERS IN HUMAN DYNAMICS, 4 [10.3389/fhumd.2022.790033].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/395537
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