Readings 

Pre-readings for session "AI and in silico social science"

• Argyle, L. P., Busby, E. C., Fulda, N., Gubler, J. R., Rytting, C., & Wingate, D. (2023). Out of one, many: Using language models to simulate human samples. Political Analysis, 31(3), 337-351.
• Bisbee, J., Clinton, J. D., Dorff, C., Kenkel, B., & Larson, J. M. (2024). Synthetic replacements for human survey data? The perils of large language models. Political Analysis, 1-16.
• Kozlowski, A., & Evans, J. (2024, September). Simulating subjects: The promise and peril of ai stand-ins for social agents and interactions, Sociological Methods and Research.

Pre-readings for session "Non-monetary incentives and organization design"

• Benabou R and Tirole J (2003) Intrinsic and extrinsic motivation. The Review of Economic Studies 70(3): 489-520.
• Cassar L and Meier S (2018) Nonmonetary Incentives and the Implications of Work as a Source of Meaning. Journal of Economic Perspectives 32(3): 215-238.
• Ai W, Chen Y, Mei Q, et al. (2023) Putting teams into the gig economy: A field experiment at a ride-sharing platform. Management Science 69(9): 5336-5353.

Preps for all participants

• Please come prepared to share one way in which advances in AI are affecting your work as researchers. Be it with regards to topic choices – e.g. how AI changes competition, organizational structure, or the nature of innovation – or be it with regards to how it shapes your way of working (e.g. by helping you run literature analyses, code speedier, collect data, etc.).