Algorithmic Accountability & Transparency in the News Media
Hamburg, 15.12.2016, 10-11:30 pm. Workshop with Nick Diakopoulos, University of Maryland, at the Hans-Bredow-Institut, Registration required
Algorithms now adjudicate decisions in nearly all facets of the public and private sector, from employment practices, to criminal sentencing, and of course the media system itself. The goal of algorithmic accountability is to articulate, explain, or justify the ways in which algorithms are exerting power in specific human contexts: perpetuating biases and discrimination, making errors, filtering or censoring information, or otherwise violating expectations. Journalists are engaging in algorithmic accountability as an extension of investigative reporting, seeking to uncover the power structures, biases, and influences that computational artifacts play in society. I will present recent algorithmic accountability work focused specifically on the role that search engines play in making political information available in elections. I’ll then present the development of a model for algorithmic transparency that describes dimensions of information that may be disclosed about algorithms, suggesting ways in which it can be employed to guide transparency by good-faith actors, as well as inform investigative or critical approaches to algorithms. In the course of the talk I’ll trace various legal, technical, regulatory, and normative challenges that remain, offering new openings for research in this domain.
Nicholas Diakopoulos is an Assistant Professor at the University of Maryland, College Park Philip Merrill College of Journalism with courtesy appointments in the College of Information Studies and Department of Computer Science. He is Director of the Computational Journalism Lab at UMD, a member of the Human-Computer Interaction Lab (HCIL) at UMD, a Tow Fellow at Columbia University School of Journalism, and Associate Professor II at the University of Bergen Department of Information Science and Media Studies. His research is in computational and data journalism with emphases on algorithmic accountability and social computing in the news. He received his Ph.D. in Computer Science from the School of Interactive Computing at Georgia Tech where he co-founded the program in Computational Journalism.