Artificial Intelligence and Democracy

Module title	Artificial Intelligence and Democracy
Module code	POL3322
Academic year	2025/6
Credits	30
Module staff	Dr Simge Andi (Convenor)

Duration: Term	1	2	3
Duration: Weeks	11	11

Number students taking module (anticipated)	40

Module description

"Artificial Intelligence and Democracy" is a dynamic module that delves into the intersection of technology and political science, ideal for students interested in the societal impacts of AI. The course features unique activities like policy simulations, and debates, which make learning engaging and highly relevant to current global issues. Although some knowledge in political science is beneficial, the module is accessible to both specialists and non-specialists and does not require prerequisites. It is particularly recommended for students in interdisciplinary pathways, as it integrates concepts from technology, ethics, political science, and public policy, preparing students for diverse real-world applications and broadening career and academic opportunities.

Module aims - intentions of the module

You will learn:

How AI influences democratic processes through a comprehensive curriculum that merges theoretical knowledge with practical applications.
About the latest studies and developments in AI, ethics, and political theory through research-enriched learning experiences.
Critical thinking and problem-solving skills by engaging in interactive methods like case studies and hands-on projects that reflect real-world scenarios.
Policy analysis and ethical decision-making skills necessary for navigating the complex landscape of technology policy and public administration.
Valuable competencies for the job market, preparing you for careers in technology policy, public administration, or roles within NGOs focused on digital rights and governance.

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

1. Analyse and interpret the role of artificial intelligence in shaping democratic processes and institutions.
2. Critically assess ethical implications of AI deployment in politics

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

3. Apply knowledge from political science and ethics to understand and solve problems at the intersection of AI and democracy.
4. Utilise current research and methodologies to formulate informed arguments and policy recommendations concerning AI and its governance.

ILO: Personal and key skills

On successfully completing the module you will be able to...

5. Develop communication skills to effectively articulate complex ideas and policy implications to diverse audiences.
6. Enhance adaptability and problem-solving capabilities in addressing ethical and practical challenges in AI applications within democratic contexts.

Syllabus plan

Whilst the module’s precise content may vary from year to year, it is envisaged that the syllabus will cover some or all of the following topics:

Introduction to Artificial Intelligence and Its Implications for Democracy

Overview of AI Technologies: Understanding AI, machine learning, and data analytics.
Historical and Theoretical Foundations: Exploring how AI technologies have evolved and their applications in democratic contexts.

Ethical, Legal, and Social Implications of AI

Ethics in AI: Addressing issues of privacy, surveillance, bias, fairness, and accountability.
Regulatory Frameworks: Examining laws and guidelines governing AI domestically and internationally.

AI's Impact on Political Processes and Public Policy

Election Integrity and Political Campaigning: The role of AI in voter targeting, campaign strategies, and information dissemination.
Public Administration and Governance: Utilization of AI to enhance public services, policymaking, and citizen engagement.

Case Studies and Real-World Applications

Sector-Specific Studies: Focusing on health, security, education, and finance sectors to illustrate impacts and challenges.
Global Perspectives: Comparative analysis of how different democracies are adapting to and regulating AI.

Critical Debates and Current Issues

Role of Big Tech: Exploring power dynamics between large AI corporations and governmental oversight.
Future Trends and Technologies: Discussing emerging AI technologies and their potential impact on democratic structures.

Research and Methodologies in AI and Democracy

Research Techniques: Methods for conducting interdisciplinary research at the intersection of AI and political science.
Analytical Tools: Training on software and tools for data analysis relevant to political and AI research.

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching Activities	Guided independent study	Placement / study abroad
44	256

Details of learning activities and teaching methods

Category	Hours of study time	Description
Scheduled Learning and Teaching	44	(22 x 2 hour) The weekly lectures detail conceptual frameworks, key issues and debates in artificial intelligence and democracy, and help guide your reading. The lectures also include group discussion or in-class exercises.
Guided Independent Study	146	This study is continuous throughout the course and should take 6-8 hours a week. Coursework and independent study includes the following below
Guided Independent Study	66	Reading 3 hours per week
Guided Independent Study	22	Note taking 1 hour per week
Guided Independent Study	22	Sketching answers to class discussions 1 hour per week. Preparing for formative assignments, research plan preparation 1 to 3 hours per week

Formative assessment

Form of assessment	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Group discussion lead (x2)	15 minutes	1-6	Oral

Summative assessment (% of credit)

Coursework	Written exams	Practical exams
100	0	0

Details of summative assessment

Form of assessment	% of credit	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Policy brief 1	15	750 words	1-4	Written
Group presentation	30	15 minutes	1, 5, 6	Written
Policy brief 2	15	750 words	1-4	Written
Final essay	40	2500 words	1-6	Written

Details of re-assessment (where required by referral or deferral)

Original form of assessment	Form of re-assessment	ILOs re-assessed	Timescale for re-assessment
Policy brief 1 (750 words)	Policy brief 1 (750 words)	1-4	August referral/deferral period
Policy brief 2 (750 words	Policy brief 2 (750 words)	1, 5, 6	August referral/deferral period
Group presentation (15-20 minutes)	Individual Video presentation (15-20 minutes)	1-4	August referral/deferral period
Final essay (2500 words)	Essay (2500 words)	1-6	August referral/deferral period

Indicative learning resources - Basic reading

Bobbio, N. (1987). The future of democracy: A defence of the rules of the game (R. Dellamy, Ed.; R. Griffin, Trans.). University of Minnesota Press. Trans. of Il futuro della democrazia. (1984). Einaudi.
Dahl, R. A. (1998). On democracy. Yale University Press.
Przeworski, A. (2018). Why bother with elections? Polity Press.
Risse, M. (2023a). Artificial intelligence and the past, present, and future of democ- racy. In Political theory of the digital age: Where artificial intelligence might take us (47–72). Cambridge University Press. https://doi.org/10.1017/9781009255189. 004
Mitchell, M. (2019). Artificial intelligence: A guide for thinking humans. Farrat, Straus; Giroux. Chapters 1-3 (pp. 17-65).
Barocas, S., Hardt, M., & Narayanan, A. (2023). Fairness and machine learning: Limitations and opportunities. The MIT Press.
Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford Univer- sity Press.
Christian, B. (2020). The alignment problem: Machine learning and human values. W. W. Norton & Company.

Key words search

Artificial intelligence, AI, democracy, politics

Credit value	30
Module ECTS	15
Module pre-requisites	None
Module co-requisites	None
NQF level (module)	6
Available as distance learning?	No
Origin date	06/02/2025