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AI assessment changes human behavior.

Jonas Goergen1, Emanuel de Bellis1, Anne-Kathrin Klesse2

  • 1Institute of Behavioral Science and Technology, University of St.Gallen, St.Gallen 9000, Switzerland.

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Summary
This summary is machine-generated.

When assessed by artificial intelligence (AI) instead of humans, individuals emphasize analytical traits and downplay emotional ones. This "AI assessment effect" stems from the belief that AI prioritizes logic over feelings.

Keywords:
AI assessmentalgorithmsartificial intelligencebehavioral changeslay beliefs

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Area of Science:

  • Psychology
  • Human-Computer Interaction
  • Artificial Intelligence Ethics

Background:

  • Artificial intelligence (AI) is increasingly used in decision-making roles, including hiring and admissions.
  • Transparency mandates require disclosure of AI assessment tool usage to individuals being assessed.

Purpose of the Study:

  • To investigate how human behavior changes when assessed by AI versus human evaluators.
  • To identify and label the phenomenon of behavioral shifts under AI assessment as the 'AI assessment effect'.

Main Methods:

  • Conducted twelve studies with over 13,000 participants (N=13,342).
  • Eight studies were text-based, and four were included in the Supporting Information.
  • Investigated behavioral changes and underlying psychological mechanisms.

Main Results:

  • Documented the 'AI assessment effect,' where individuals emphasize analytical characteristics and minimize intuitive/emotional ones under AI assessment.
  • Identified the underlying mechanism: a common belief that AI prioritizes analytical traits.
  • Demonstrated systematic behavioral changes, distinct from prior research on AI perceptions or productivity.

Conclusions:

  • AI assessment influences individual behavior, leading to a strategic emphasis on analytical self-presentation.
  • Understanding the 'AI assessment effect' is crucial for organizations utilizing AI in evaluations.
  • Findings contribute to the psychology of AI and offer practical implications for assessment practices.