LEARN AI Conference

The rapid development of artificial intelligence is transforming economic
activity and raising fundamental questions about human behavior. While a
growing body of evidence shows that AI can substantially enhance produc-
tivity, the interaction between humans and AI remains complex and often
imperfect. Individuals may resist algorithmic recommendations, misuse AI
tools, or place excessive trust in their outputs.
A central but still underexplored question concerns the reverse causal
channel: how does the presence and use of AI reshape human cognition,
learning, effort, and ethical behavior?
This workshop aims to bring together these perspectives, structure this
emerging research agenda, and stimulate new contributions on the impact
of AI on human learning and behavior.


 

Open from July 15 to October 31

REGISTRATION

Topics of Interest

Topics include (but are not limited to):
• AI and human learning
• AI-assisted decision-making
• Human-AI interaction, trust, and overreliance
• Effort, skills, and human capital formation
• AI, cognition, and behavioral responses
• Algorithm aversion and algorithm appreciation
• AI and ethical behavior
• AI in education and education policy
• Experimental and behavioral approaches to AI



 

Keynote Speakers

• Daniel Martin (University of California, Santa Barbara)
• Nobuyuki Hanaki (The University of Osaka, Japan)