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Ethics and Social Implications of Data Science

Information on all members of society now exists in various databases, and the ability to analyze enormous amounts of data is reshaping how governments, businesses and other entities made decisions. However, ethical standards for data designed for a pre-computer age are of limited utility, and the use of “big data” raises a host of social and ethical questions.

In conjunction with the Halıcıoğlu Data Science Institute and Division of Social Sciences, the Institute for Practical Ethics sponsored an inagural workshop in February 2019 addressing the rise of big data: the combination of the production and retrieval of large amounts of digital information with powerful algorithms on a hardware platform of ever-increasing capacity.

The workshop gathered social and computer scientists, activists and practitioners interested in the ethics and policy implications of this technological revolution.

These industry leaders surveyed the achievements, promises and technical challenges of big data, its effects on social inequalities and democracy, the cultural shift it is generating in the way we value knowledge, create art and conduct science, and the ways we may control it and influence its progress.

Working Group on Data Analytic Governance and Accountability

Governance and accountability are important because governments are adopting data analytic technologies to maintain social order and to enhance or replace existing instruments of regulation and social control, just as markets are relying more and more on data analytics to organize economic activity. 

As a result, algorithms are deployed often without transparency or accountability. Most data analytic tools are “dual use,” allowing for socially beneficial and socially pernicious uses.

Important issues in this domain include: data privacy and security, algorithmic fairness and discrimination, the replacement of human discussion and deliberation with narrowly focused algorithmic decision making, the masking of human decision making with data analytic operations, the lack of transparency and interpretability of algorithmic processes, and the various unintended consequences of the deployment of new information technology for social ends.

To understand how these powerful tools work and to ensure that they are applied in ways that enhance rather than curtail human agency, social justice, democracy and economic development, we must articulate and investigate how data analytics govern and transform social life.

Working Group Members

Amanda Datnow

Amanda Datnow

Department of Education Studies

Kelly Gates

Kelly Gates

Department of Communication

Caroline Jack iamge

Caroline Jack

Department of Communication

Irani iamge

Lilly Irani

Department of Communication

Navon iamge

Daniel Navon

Department of Sociology

Pardo Guerra iamge

Juan Pablo Pardo-Guerra

Department of Sociology

Rajogopalan iamge

Ramya Rajogopalan

Institute for Practical Ethics

Roberts iamge

Margaret Roberts

Department of Political Science

headshot iamge

Akos Rona-Tas

Department of Sociology

Spring Quarter 2022 Events

Monday, April 4 | 12 – 2 p.m.
Frank Pasquale, Brooklyn Law School, author of "The Black Box Society" and "New Laws of Robotics
Organized by the Working Group on Data Analytic Governance and Accountability, a joint event with the Science Studies Program

Friday, April 15 | 12 – 2 p.m.
Anna Lauren Hoffman, University of Washington School of Information, author of "Where Fairness Fails" and "Terms of Inclusion"
Organized by the Working Group on Data Analytic Governance and Accountability

Friday, April 29 | 12 – 2 p.m.
Davide Carpano and Bolun Zhang, UC San Diego Dept of Sociology, presenting on open-source software as a model for standards
Organized by the Working Group on Data Analytic Governance and Accountability

Friday, May 13 | 9 – 11 a.m.
Julie Cohen, Georgetown University School of Law, author of "Between Truth and Power" and "Configuring the Network Self"
Organized by the Working Group on Data Analytic Governance and Accountability

Friday, May 27 | 11 a.m. – 12:30 p.m.
Kadija Ferryman, Johns Hopkins University School of Public Health, author of "Fairness in Precision Medicine" and "Ethical Machine Learning in Health Care"
Organized by the Working Group on Data Analytic Governance and Accountability

 

*All event locations to be determined at a later date. For more information on attending, contact Stuart Geiger.