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MIA Talks

AI audit to uncover blind spots of data

May 9, 2018
Depts. of Biomedical Data Science, Computer Science, and Electrical Engineering, Stanford University

Data science and data engineering often involve complex pipelines, and it’s not transparent where flaws are introduced. I will discuss the (simple) idea of AI audit, where we leverage the predictive power of machine learning to systematically perform quality control of various components of the data pipeline. I will illustrate this framework with three diverse examples: integrating single-cell RNA-Seqs, designing new proteins, and word embeddings.