Trust in the machine: How contextual factors and personality traits shape algorithm aversion and collaboration

This paper investigates the interplay between contextual factors, personal variables, and algorithm aversion in decision delegation behavior. In an experimental setting with four treatments —baseline, explanation, payment, and automation— subjects chose whether to delegate decisions to an algorithm, considering hidden expected values. Employing Random Forests, Gradient Boosting Machines, and causal analysis with the Uplift Random Forest, we probed key algorithm aversion drivers. In the personal dimension, we assessed Big Five Personality Traits, Locus of Control, Generalized Trust, and demographics. We find that payment reduced delegation, while full automation promoted it. Factors like Age, Extraversion, Openness, Neuroticism, and Locus of Control consistently emerged as significant in shaping delegation decisions. Female participants demonstrated a stronger reaction to algorithmic mistakes. This study offers insights for crafting user-centric AI design to enhance cooperation and minimize aversion.

• Publication year

  2024

• Venue

  Computers in Human Behavior Reports

• Publication date

  2024-12-01

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1016/j.chbr.2024.100578
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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