Data & Society Fellow Jeanna Matthews speaks about algorithmic accountability and transparency within the context of the criminal justice system.
Important decisions in our society are being made evermore frequently by opaque algorithms and platforms. Matthews describes how algorithms are generally designed for efficiency and “reduced risk” for decision-makers, rather than for individuals or communities. She delves into examples of “mischief” within machine learning training and testing data sets, and what potential negative outcomes such data may invoke. For this reason, “we need to be iteratively improving, debugging these systems” particularly within the criminal justice system, where the consequences of our mistakes may be dire.
Data & Society’s Fellows Talks is a three-part Databite series showcasing our 2017-2018 fellows cohort. Each talk features 2-3 fellows speaking about their work, wide-ranging interdisciplinary connections, and a few of the provocative questions that have emerged this year. See the talks by Darakhshan Mir and Taeyoon Choi.
Jeanna Matthews is a 2017-18 Data & Society Fellow and associate professor of computer science at Clarkson University, where she does research in computer security and leads hands-on computing laboratories including the Clarkson Open Source Institute.
Data & Society’s “Databites” speaker series presents timely conversations about the purpose and power of technology, bridging our interdisciplinary research with broader public conversations about the societal implications of data and automation.