This is a recording of a public roundtable discussion. Originally, this event was streamed online and questions were taken from the Twitter hashtag (#algoaudit) and the BKC Live Question Tool.
- Eric Gilbert, University of Michigan
- Cedric Langbort, University of Illinois
- Jeff Larson, ProPublica
- Casey Pierce, University of Michigan
- Christo Wilson, Northeastern University
FRIDAY, September 29, 2017
10-11:30 a.m. Eastern Daylight Time (UTC/GMT -4 hours)
6050 Institute for Social Research (map/directions)
University of Michigan
Ann Arbor, MI USA
The equations of big-data algorithms have permeated almost every aspect of our lives. A massive industry has grown up to comb and combine huge data sets — documenting, for example, Internet habits — to generate profiles of individuals. These often target advertising, but also inform decisions on credit, insurance and more. They help to control the news or adverts we see, and whether we get hired or fired. They can determine whether surveillance and law-enforcement agencies flag us as likely activists or dissidents — or potential security or criminal threats….Largely absent from the widespread use of such algorithms are the rules and safeguards that govern almost every other aspect of life in a democracy. There is an asymmetry in algorithmic power and accountability…Fortunately, a strong movement for greater algorithmic accountability is now under way. Researchers hope to find ways to audit for bias….Society needs to discuss in earnest how to rid software and machines of human bugs.
–Unsigned Editorial, Nature (2016)
[We] need to create a new field around the social algorithm, which examines the interplay of social and computational code.
–David Lazer, Op-Ed, Science (2015)
A full-color, printable version of this flyer suitable for 8.5 x 11″ or 11 x 17″ printing is available in PDF format.
(CORRECTION to the flyer: Unfortunately, due to circumstances beyond his control, Ashkan Soltani was unable to attend this panel. He was replaced by Jeff Larson.)
Held at the University of Michigan. Presented by the Center for Political Studies at the Institute for Social Research and co-Sponsored by the Department of Communication Studies and the School of Information. This material is based upon work supported by the National Science Foundation under Grant No. ITR-1665151. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.