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One Dimensional Turing-Like Handshake Test for Motor Intelligence
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Human verifications: Computable with truth values outside logic.

Philip N Johnson-Laird1,2, Ruth M J Byrne3, Sangeet S Khemlani4

  • 1Department of Psychology, Princeton University, Princeton, NJ 08544.

Proceedings of the National Academy of Sciences of the United States of America
|September 25, 2023
PubMed
Summary
This summary is machine-generated.

Human verification of disjunctive statements is computable, but requires more than simple true/false logic. Findings suggest mental models and counterfactuals are key to understanding verification processes.

Keywords:
computabilitycounterfactualslogicmental modelstruth

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Area of Science:

  • Cognitive Science
  • Logic
  • Computational Theory

Background:

  • Verification is often viewed as a computation where descriptions matching reality are true.
  • Controversy exists regarding whether human verification is computable, with Gödel and Penrose arguing against it.
  • The theory of mental models proposes computability but finds standard true/false logic insufficient.

Purpose of the Study:

  • To investigate the computability of human verification of disjunctive assertions.
  • To explore whether standard logical truth values are sufficient for human verification.
  • To examine the role of counterfactuals in verification processes.

Main Methods:

  • Conducted three online experiments (n=208) on participants' verification of disjunctive statements (e.g., 'You arrived at Exeter or Perth').
  • Analyzed how observations and the status of alternative possibilities influenced verification judgments.
  • Implemented a computer program to model disjunctions and verify them using observed truth values.

Main Results:

  • Verification depended on observed matches and the status of other potential locations.
  • Participants utilized nuanced truth values beyond simple true/false, reflecting possibilities and impossibilities.
  • Specific truth values incorporating counterfactuals were observed when destinations were reached or impossible.

Conclusions:

  • Human verification of disjunctive assertions appears computable, utilizing truth values beyond standard binary logic.
  • Mental models incorporating counterfactual reasoning are essential for understanding these verification processes.
  • The computability of the awareness of a verification's outcome remains an open research question.