Seminar Overview | Schedule
All information is subject to change.
- 15/4 (16:00-18:00): Introduction
- 6/5 (16:00-18:00): Background in psychology of decision-making
- Bonaccio, S. and Dalal, R.S., 2006. Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences. Organizational behavior and human decision processes
- Dietvorst, B.J., Simmons, J.P. and Massey, C., 2015. Algorithm aversion: People erroneously avoid algorithms after seeing them err. Journal of Experimental Psychology: General
- Logg, J.M., Minson, J.A. and Moore, D.A., 2019. Algorithm appreciation: People prefer algorithmic to human judgment. Organizational Behavior and Human Decision Processes
- 27/5 (16:00-18:00): Comparing human and machine decisions
- Tan, S., Adebayo, J., Inkpen, K. and Kamar, E., 2018. Investigating human + machine complementarity for recidivism predictions. arXiv preprint arXiv:1808.09123.
- Kahneman, D., Rosenfield, A.M., Gandhi, L. and Blaser, T., 2016. Noise. Harvard Bus Rev
- Madras, D., Pitassi, T. and Zemel, R., 2018. Predict responsibly: improving fairness and accuracy by learning to defer. NeurIPS
- 17/6 (16:00-18:00): Human perceptions of machine decision aids
- Lee, M.K., 2018. Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data & Society
- Grgić-Hlača, N., Redmiles, E.M., Gummadi, K.P. and Weller, A., 2018. Human perceptions of fairness in algorithmic decision making: A case study of criminal risk prediction. The Web Conf
- Saxena, N.A., Huang, K., DeFilippis, E., Radanovic, G., Parkes, D.C. and Liu, Y., 2019. How do fairness definitions fare? Examining public attitudes towards algorithmic definitions of fairness. AIES
- 8/7 (16:00-18:00): Machine-assisted human decision-making
- Grgić-Hlača, N., Engel, C. and Gummadi, K.P., 2019. Human decision making with machine assistance: An experiment on bailing and jailing. CSCW
- Green, B. and Chen, Y., 2019. Disparate interactions: An algorithm-in-the-loop analysis of fairness in risk assessments. FAccT
- Yin, M., Wortman Vaughan, J. and Wallach, H., 2019. Understanding the effect of accuracy on trust in machine learning models. CHI