SOAS University of London

School of Law

Artificial Intelligence: Power, law and resistance

Module Code:
15PMSH042
Credits:
15
FHEQ Level:
7
Year of study:
Any
Taught in:
Term 2

Artificial Intelligence is one of the most relevant global challenges in the contemporary world. Unlike Climate Change and the Covid pandemic, AI is not visible, but its implications are felt in different ways, most importantly in racialized and gendered discourses and in its consequences for equality and equitable justice. This module offers a critical perspective grounded in legal, gender and communication perspectives around AI, its uses and implications for the regions we study and their diaspora. It will use case studies to examine the role of AI in surveillance and data gathering, on Human Rights (as much as how a possible AI Bill of Rights might be constituted), on courtroom practices; on gendered and racialized practices and on representational practices in media and other genres of communication. We also critically question the assumptions behind the ‘Metaverse’ and who sets the agenda.

In its critical interdisciplinary and intersectional approach and through case studies, this module shifts away from the techno jargon embedded in the discourses around AI, and consider everyday experiences and practices around it.

Objectives and learning outcomes of the module

On successful completion of this module, students will:

1. Acquire a critical and informed understanding of the debates surrounding AI in the fields of law, gender and media
2. Offer a grounded empirically-focused critique of AI and its consequence for racial, gendered and representational practices and lives.
3. Develop critical skills to challenge dominant discourses around AI
4. Address how critical law, gender and media theory can be used to inform AI debates
5. Develop the skills to think independently, and write and analyse the sociological, political, legal, gendered and racial consequences of AI

Workload

  • A weekly 2 hour lecture
  • A weekly 1 hour seminar

Scope and syllabus

1. AI: Origins and evolution. Early applications. Transport/Aeronautics. Communications. Databases and data processing, business/corporate and state/bureaucratic. Policing.

2. AI and Mediation: AI Theory and Media Theory. Advent of the Algorithm. Programming and Bias. Decision Logic. Digitalisation. Technical/Political. Time and Speed. Broadcast/print media v electronic/social media. Passive/interactive media-use. Mediated images/sounds.

3. Surveillance capitalism with particular reference to the Global South I: logic and mechanisms. Big Tech: Google and Facebook. Social media user (behavioural and personal) data mining. Algorithms.

4. Surveillance capitalism with particular reference to the Global South II: North-South political economy of social media. Content monitoring and takedown. Private power and political speech. Digital colonialism/imperialism.

5. Militarisation: Revolution in Military Affairs. Military applications. Targeting. Drone Warfare. Counter-terror strikes/targeted assassination. Militarised Policing.

6. Regulation: US legislation, enabling and constraining. Comparative national regulation. China and India. International standards and regulation. Data protection. Human Rights: expression, privacy, assembly etc. AI Bill of Rights. IHL (targeting, proportionality etc).

7. AI and advocacy in the Global South

8. AI, Mediation and Identity I: Gender/Sexuality, Race Geography. Coding and transcoding. Reinforcing/contesting bias. Essentialism and intersectionality.

9. AI, Mediation and Identity II: Cultures of AI in the Global South. Social media tribalism, nationalism, and transnationalism. Reactionary/emancipatory formations.

10. AI and Resistance: Hacking. Algorithm and content-monitoring subversion. Politics and anti-politics. Citizens and consumers. Collective action. Social intelligence v AI. Alternative futures. Language/Orthography. Digital de-colonisation.

Method of assessment

  • 800-1000 word critical review of book/film: 20%
  • 3000 word essay: 80%

Suggested reading

Core reading

1) Brayne, S. (2021) Predict and Surveil: Data, Discretion and the Future of Policing , OUP

2) Crawford, K. (2021,) Atlas of AI, Yale University Press

3) D’Ignazio and Klein, L, (2020) Data Feminism , MIT Press

4) Dubber, et al,2020, The Oxford Handbook of the Ethics of AI

5) Jefferson, B. (2020) Digitise and Punish: Racial Criminalization in the Digital Age, University of Minnesota Press

6) Lee, et al, (2021) Artificial Intelligence and Intellectual Property, OUP

7) Noble, S, (2018) Algorithms of Oppression: How Search Engines Reinforce Racism, NYU Press

8) Russell, S.J., and Peter Norvig (2009) Artificial Intelligence: A Modern Approach, Prentice Hall

9) Warwick, K. (2012) Artificial Intelligence: The Basics, Routledge

10) Zuboff, S. (2019) The Age of Surveillance, Profile Books

Additional reading

1)Balkin, Jack B. (2015) “The Path of Robotics Law”. The Circuit - California Law Review. Paper 72.

2) Asaro, P.M. (2007) “Robots and Responsibility from a Legal Perspective” 

3) Scherer, Matthew U. (2015) “Regulating Artificial Intelligence Systems: Risks, Challenges, Competencies, and Strategies” Harvard Journal of Law and Technology, Vol 29, No. 2

4) Muehlhauser, Luke (2016) “What Should We Learn From Past AI Forecasts?”, (Open Philanthropy Project.)

5) Kesavan Athimoolam, Solving the artificial intelligence race: mitigating the problems associated with the AI race, Paper finalist in the ‘Solving the AI Race’ challenge, GoodAI, Prague, 2018, p. 21, https://mirror.goodai.com/judges/Solving_the_AI_race_KA.pdf

 

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