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Dr Daniel Berliner

This course is available on the BSc in International Social and Public Policy with Politics, BSc in Politics, BSc in Politics and Economics, BSc in Politics and History, BSc in Politics and International Relations and BSc in Politics and Philosophy. This course is not available as an outside option nor to General Course students.

Students must have completed Introduction to Political Science (GV101).

How do information technology, social media, and big data shape politics and public policy? How are they, in turn, shaped by politics and public policy? How are data science tools used in politics and public policy themselves? This course offers students a critical understanding of these key intersections between data science and politics.

Major topics include debates over how social media shapes politics, the global confrontations over rules governing data, how data are used in administrative and policymaking processes, the dangers of algorithmic bias in public services, and how politics shapes government innovation and openness. The course will devote particular attention to how big data and algorithms risk exacerbating social and political inequities. The course will also offer a conceptual, non-technical overview of key data science tools and how they are applied by policymakers in settings such as decision-making, campaigns, public participation, anti-corruption, and international conflict and development. This course is global in scope, as topics will draw on examples and applications from around the world, including both global “north” and “south.” 

Outline of weekly topics:

1. Introduction to information technology and politics

2. Social media and politics

3. Domestic and international governance of data and privacy

4. Review of data science tools and their applications

5. Big data in public policy and administration

6. Algorithmic bias and algorithmic accountability

7. Open data and data sharing

8. Civic tech and democratic innovations

9. Data in world politics

10. The politics of government innovation

15 hours of lectures and 10 hours of classes in the LT.

Students will be expected to produce 1 essay in the LT.

Fung, Archon, Hollie Russon Gilman, and Jennifer Shkabatur. 2013. "Six models for the internet+politics." International Studies Review.

Nyabola, Nanjala. 2018. Digital democracy, analogue politics: How the Internet era is transforming politics in Kenya. Zed Books.

Farrell, Henry, and Abraham Newman. 2016. "The transatlantic data war: Europe fights back against the NSA." Foreign Affairs.

Vogl, Thomas M., Cathrine Seidelin, Bharath Ganesh, and Jonathan Bright. 2020. "Smart Technology and the Emergence of Algorithmic Bureaucracy: Artificial Intelligence in UK Local Authorities." Public Administration Review.

Perez, Caroline Criado. 2019. Invisible women: Exposing data bias in a world designed for men. Random House.

Richardson, Rashida, Jason M. Schultz, and Kate Crawford. 2019. "Dirty data, bad predictions: How civil rights violations impact police data, predictive policing systems, and justice." NYU Law Review Online.

Worthy, Ben. 2015. "The impact of open data in the UK: Complex, unpredictable, and political." Public Administration.

Peixoto, Tiago, and Micah L. Sifry. 2017. Civic Tech in the Global South: Assessing Technology for the Public Good. World Bank.

Ahn, Michael J., and Stuart Bretschneider. 2011. "Politics of egovernment: Egovernment and the political control of bureaucracy." Public Administration Review.

Essay (100%, 2000 words) in the ST.

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.