Humans incorrectly reject confident accusatory AI judgments

TL;DR

This study investigates how human acceptance of AI deception judgments depends on the AI's accuracy and confidence levels, revealing complex interactions affecting decision-making.

Contribution

It provides empirical evidence on how AI accuracy and confidence influence human trust and decision-making in deception detection tasks.

Findings

Humans follow highly accurate AI judgments more than less accurate ones.

Higher AI confidence increases human deviation from AI predictions, especially for deception.

Interaction with AI predictions can impair or not improve AI performance.

Abstract

Automated verbal deception detection using methods from Artificial Intelligence (AI) has been shown to outperform humans in disentangling lies from truths. Research suggests that transparency and interpretability of computational methods tend to increase human acceptance of using AI to support decisions. However, the extent to which humans accept AI judgments for deception detection remains unclear. We experimentally examined how an AI model's accuracy (i.e., its overall performance in deception detection) and confidence (i.e., the model's uncertainty in single-statements predictions) influence human adoption of the model's judgments. Participants (n=373) were presented with veracity judgments of an AI model with high or low overall accuracy and various degrees of prediction confidence. The results showed that humans followed predictions from a highly accurate model more than from a less accurate one. Interestingly, the more confident the model, the more people deviated from it, especially if the model predicted deception. We also found that human interaction with algorithmic predictions either worsened the machine's performance or was ineffective. While this human aversion to accept highly confident algorithmic predictions was partly explained by participants' tendency to overestimate humans' deception detection abilities, we also discuss how truth-default theory and the social costs of accusing someone of lying help explain the findings.