Artificial Intelligence and Persuasion: A Construal-Level Account.

Area of Science:

• Human-Computer Interaction
• Artificial Intelligence Ethics
• Social Psychology

Background:

• Increasing reliance on nonhuman agents (e.g., AI, robots) for information.
• Limited research on persuasion differences between human and artificial agents.

Purpose of the Study:

• To investigate how construal levels influence the effectiveness of persuasive messages from artificial agents.
• To determine optimal message framing for artificial agent persuasion.

Main Methods:

• Utilized construal-level theory to frame hypotheses.
• Conducted multiple studies with a total of 1,668 participants.
• Manipulated message construal (low-level vs. high-level).

Main Results:

• Individuals perceive artificial agents at a low level of construal.
• Low-level construal messages are more appropriate and effective for artificial agents.
• The effect is moderated by the agent's ability to learn independently.

Conclusions:

• Message framing (low-level construal) is crucial for effective persuasion by artificial agents.
• Understanding lay theories about AI learning is key to moderating persuasion effects.
• Research provides practical insights for designing persuasive AI systems.