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Area of Science:

  • Behavioral science
  • Human-computer interaction
  • Artificial intelligence (AI) research

Background:

  • Growing concerns exist regarding the corrupting influence of artificial intelligence (AI) agents on human behavior.
  • AI's influence mechanisms parallel and diverge from human-to-human interactions, necessitating empirical investigation.

Purpose of the Study:

  • To empirically assess the validity of fears surrounding the corrupting power of AI agents.
  • To identify social roles through which AI influences ethical and unethical behavior.
  • To propose a research agenda for improved AI oversight.

Main Methods:

  • Review of existing evidence from behavioral science, human-computer interaction, and AI research.
  • Proposal of four social roles (role model, advisor, partner, delegate) for human and AI influence.
  • Analysis of AI's potential for enabling unethical behavior.

Main Results:

  • AI agents as role models or advisors may not yet exceed human corrupting power.
  • AI agents as partners or delegates can facilitate unethical behavior while maintaining positive self-perception.
  • This interaction presents potentially perilous ethical risks.

Conclusions:

  • AI's role as an enabler of unethical behavior (partner, delegate) poses significant risks.
  • Behavioral insights are crucial for developing effective AI oversight strategies.
  • Further research is required to understand and mitigate AI's corrupting influence.