Big Data Ethics and Policy

Instructor Name

Jess Reia

Instructor Biography

Jess Reia is an Assistant Professor of Data Science at the University of Virginia and a Faculty Lead at the Digital Technology for Democracy Lab at the UVA Karsh Institute for Democracy. Reia is also a 2024-2025 Non-Residential Fellow at the Center for Democracy and Technology, based in Washington, D.C. Before joining UVA, they were appointed Andrew W. Mellon Postdoctoral Researcher at McGill University and BMO Fellow at the Centre for Interdisciplinary Research on Montreal (CIRM-McGill). Reia is an AI Fellow at NewCities, an advisor at Urban AI, a Coalition for Independent Technology Research member, and was part of MTL 24/24's Night Council in Montreal. From 2011 to 2019, Reia worked as a Professor and Project Manager at the Center for Technology & Society at FGV Law School (CTS-FGV) in Rio de Janeiro. Reia works on research and advocacy on technology policy, data ethics, and urban governance.

Course Description

Big data, artificial intelligence (AI), machine learning and large language models are words that are becoming part of our everyday lives. They shape how we interact with each other, purchase products and services, get hired, receive social benefits from governments and, increasingly, how we create various media content. Such important transformation also brings ethical and policy issues to the forefront, as we can see, for example, in global efforts to regulate AI and its outcomes. This course combines topics in data ethics, public policy, governance, and regulation. We will learn to articulate ethical principles by addressing various types of challenges in data science and policy, divided according to relevant topics and specific case studies from China and the world. Next, we will discuss how data-centric systems are deployed within socioeconomic ecosystems and how they shape life around us. Then, we will interrogate the connections between data science, governments, industry, civil society organizations, and communities.

Course Schedule

Ten Session Topics

  • Introduction to data ethics and course overview

  • Data collection, data sets and open data

  • The datafication of everything and ethical dilemmas

  • Key concepts I: fairness and accountability

  • Key concepts II: transparency and explainability

  • Key concepts III: privacy and data protection

  • Regulating AI globally

  • Governing AI and its outcomes

  • Urban data for megacities

  • Big data and climate resilience

Learning Outcomes

Upon successful completion of this course, students will be able to:

  • Understand fundamental concepts, theories, policies, and controversies around big data ethics transnationally.

  • Think critically about the governance challenges embedded in data-centric systems.

  • Question the various impacts of big data on individuals and communities, especially in the Global South and BRICS.

  • Discuss emerging data policies and regulatory frameworks in China and beyond.

  • Acquire critical reading skills useful to comprehend scholarly papers, policy documents, legislation, and news articles.

  • Articulate, through assignments, analyses regarding ethical issues related to big data.