We are beginning to harness the power of AI, machine learning, and data science throughout many aspects of society. Indeed, these areas form core components of many Microsoft systems and products.
But these techniques also raise complex ethical and social questions: How can we best use AI to assist users and offer enhanced insights, while avoiding exposing them to different types of discrimination in health, housing, law enforcement, and employment? How can we balance the need for efficiency and exploration with fairness and sensitivity to users? As we move toward relying on intelligent agents in our everyday lives, how do we ensure that individuals and communities can trust these systems?
As researchers in this group, we work on the complex social implications of AI, machine learning, data science, large-scale experimentation, and increasing automation. Our aim is to develop computational techniques that are both innovative and ethical, while drawing on the deeper context surrounding these issues from sociology, history, and science and technology studies. As a new group, we are currently working on collaborative research projects that address the need for transparency, accountability, and fairness in AI and ML systems. We publish in a variety of disciplines, including machine learning, information retrieval, systems, sociology, political science, and science and technology studies.