Beyond interpretability: developing a language to shape our relationships with AI

Been Kim is a staff research scientist at Google Brain. Her research focuses on helping humans to communicate with complex machine learning models: not only by building tools (and tools to criticize them) but also studying their nature compared to humans. She gave a talk at the G20 meeting in Argentina in 2019. Her work TCAV received UNESCO Netexplo award, was featured at Google I/O 19'. Her work was in a chapter of Brian Christian's book on "The Alignment Problem". Been gave keynote at ECML 2020, tutorials on interpretability at ICML, University of Toronto, CVPR and at Lawrence Berkeley National Laboratory. She was a co-workshop Chair ICLR 2019, and has been an (senior) area chair at NeurIPS, ICML, ICLR, AISTATS and others. She is a steering committee member of FAccT conference and former executive board member and VP of Women in Machine Learning. She received her PhD. from MIT.