Welcome to the AFOG Blog! We will use this space to post what we hope are accessible and provocative think pieces and reactions to academic research and news stories. Posts about what? Allow us to use this initial blog post to answer that question and introduce ourselves.
Algorithms and computational tools/systems, particularly as applied to artificial intelligence and machine learning, are increasingly being used by firms and governments in domains of socially consequential classification and decision-making. But their construction, application, and consequences are raising new concerns over issues of fairness, bias, transparency, interpretability, and accountability. The development of approaches or solutions to address these challenges are still nascent. And they require attention from more than just technologists and engineers, as they are playing out in domains of longstanding interest to social scientists and scholars of media, law, and policy, including social equality, civil rights, labor and automation, and the evolution of the news media.
In the fall of 2017, Professors Jenna Burrell and Deirdre Mulligan, professors at the UC Berkeley School of Information, began the Algorithmic Fairness and Opacity Group (AFOG), a working group that brings together UC Berkeley faculty, postdocs, and graduate students to develop new ideas, research directions, and policy recommendations around these topics. We take an interdisciplinary approach to our research, with members based at a variety of schools and departments across campus. These include UC Berkeley’s School of Information, Boalt Hall School of Law, Haas School of Business, the Goldman School of Public Policy, the departments of Electrical Engineering and Computer Sciences (EECS) and Sociology, the Berkeley Institute of Data Science (BIDS), the Center for Science, Technology, Medicine & Society (CSTMS), and the Center for Technology, Society & Policy (CTSP).
We meet roughly biweekly at the School of Information for informal discussions, presentations, and workshops. We also host a speaker series that brings experts from academia and the technology industry to campus to give public talks and take part in interdisciplinary conversations. AFOG is supported by UC Berkeley’s School of Information and a grant from Google Research.
Below is a sampling of some of the questions that we seek to address:
- How do trends in data-collection and algorithmic classification relate to the restructuring of life chances, opportunities, and ultimately the social mobility of individuals and groups in society?
- How does an algorithmically informed mass media and social media shape the stability of our democracy?
- How can we design user interfaces for machine-learning systems that will support user understanding, empowered decision-making, and human autonomy?
- What tools and techniques are emerging that offer ways to mitigate transparency and/or fairness problems?
- Which methods are best suited to particular domains of application?
- How can we identify and transcend differences across disciplines in order to make progress on issues of algorithmic opacity and fairness?
Look for more from us on the AFOG Blog in the weeks and months to come!