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The use of AI algorithms are becoming more prevalent in business, education and medicine. How do people perceive feedback and advice from algorithms? How do we combine human and machine intelligence in new and interesting ways? What do algorithmic biases come from and how do we design algorithms that produce results that are considered fair? We explore these Human-AI interaction questions through different projects.
M. Schaekermann, G. Beaton, E. Sanoubari, A. Lim, K. Larson and E. Law. Ambiguity-aware AI Assistants for Medical Data Analysis. In CHI 2020.
C. Vandenhof. A Hybrid Approach to Identifying Unknown Unknowns of Predictive Models. In HCOMP 2019
T. Tse, J. Salamon, A. Williams, H. Jiang and E. Law. Ensemble: A Hybrid Human-Machine System for Generating Melody Scores from Audio. In ISMIR 2016.