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1 results

  • Chapter 3 - Trust

  • from Part I - AI and Consumer Psychology
  • Michael Clarke, New York University, Manuel Garcia-Garcia, Ipsos, Michael Joffe, New York University
  • Book:
    Smarter Together
    Published online:
    05 June 2026
    Print publication:
    18 June 2026, pp 39-58

  • Summary

    Trust is presented as a cornerstone of human–AI interaction. The chapter reviews psychological, sociological, and computational models of trust, including interpersonal and contractual trust, Luhmann’s theory of trust-as-prediction, and the Computers Are Social Actors theory that explains why people anthropomorphize machines. It examines risks of overtrust (automation bias, misplaced confidence) and undertrust (algorithm aversion, underuse of reliable systems). Strategies such as transparency, explainability, fairness, and accountability are discussed as ways to calibrate trust appropriately. The chapter concludes that trust in AI is dynamic, context-dependent, and must be designed into systems deliberately.