Engineering Responsible AI
Recent achievements and advancements in AI have outpaced what anyone would have thought imaginable even five to ten years ago. For instance, we are fast approaching human parity across many tasks of AI — speech, vision and natural language, on many benchmark date sets. But many practitioners building AI technology and deploying AI products have not always thought through the societal implications such as fairness and transparency. Recently a number of principles have been proposed to help companies and countries navigate the complexities and implications of AI. But principles alone are no longer enough—industry, academia and government need to take actions now to move from principles to practices. In this talk, I will share some examples of what we have been practicing in Microsoft AI and Research from doing research in explainable and interpretable AI, to creating tools for bias error analysis in machine learning, to debiasing word embedding learnt from the web.
Harry Shum is executive vice president of Microsoft’s Artificial Intelligence (AI) and Research group.
He is responsible for driving the company’s overall AI strategy and forward-looking research and development efforts spanning infrastructure, services, apps and agents. He oversees AI-focused product groups including Bing. He also leads Microsoft Research, one of the world’s premier computer science research organizations, and its integration with the engineering teams across the company.
Dr. Shum is an IEEE Fellow and an ACM Fellow for his contributions to computer vision and computer graphics. He received his Ph.D. in robotics from the School of Computer Science at Carnegie Mellon University. In 2017, he was elected to the National Academy of Engineering of the United States.