Teaching

I am teaching two courses this term at ' Graduate School of Public Policy (GSPP), Nazarbayev University'. Please sign up for courses on the university website. If you have any specific questions about course topics, feel free to message my office, and a teaching assistant staff member will respond as soon as possible.

MPE-632: Artificial Intelligence and Governance

Term: Fall

Offered: 2025

Course Objectives:

1) Understand key AI technologies and their relevance to governance.

2) Evaluate the ethical, legal, and societal implications of AI in public administration.

3) Analyze case studies of AI applications in digital government, smart cities, law enforcement, and citizen services.

4) Assess the governance of AI, including regulation, transparency, and accountability mechanisms.

5) Design policy recommendations for ethical and effective AI adoption in government settings.

Course learning outcomes (CLOs)

By the end of the course, the students are expected to be able to:

1. Critically evaluate major theories and frameworks in public administration and governance, and explain how these theories inform the integration and use of artificial intelligence (AI) in public sector decision-making.

2. Analyze the opportunities, challenges, and implications of adopting AI technologies in public sector domains such as policymaking, service delivery, crisis management, budgeting, and citizen engagement.

3. Assess the ethical, legal, and governance dimensions of AI deployment in democratic settings, with emphasis on public trust, transparency, algorithmic bias, and citizen rights.

4. Design and propose evidence-based policy recommendations for effective, equitable, and sustainable AI adoption in public administration, demonstrating awareness of technological, organizational, and societal factors.

MPE-688: New Technologies and Public Policy

Term: Spring

Offered: 2026

Course Description:

This course examines how emerging technologies such as AI, blockchain, quantum computing, and 5G are reshaping society, markets, and governance. It explores both opportunities, such as improved services, efficiency, and innovation, and challenges, including inequality, privacy risks, and ethical dilemmas. Through case studies and critical analysis, students will learn how public policy can address market and government failures, balance trade-offs, and design inclusive, evidence-based strategies that harness technological change for the public good.

Course Objectives:

This course aims to:

Critically assess the societal opportunities and risks posed by emerging technologies in diverse policy domains.
Develop analytical skills to identify market and government failures arising from technological disruption.
Examine governance approaches and regulatory frameworks that can foster innovation while safeguarding equity, accountability, and public trust.

Apply evidence-based reasoning to propose inclusive and forward-looking policy solutions for managing technological change.

Course learning outcomes (CLOs)

By the end of the course, the students are expected to be able to:

1. Analyze the impact of disruptive technologies on at least three policy areas such as education, healthcare, and governance, using real-world case studies.

2. Evaluate policy responses to technological challenges by applying frameworks of market failures (public goods, externalities, information asymmetry) and government failures (regulatory gaps, accountability limitations).

3. Design an evidence-based policy brief that proposes governance strategies to maximize public value while mitigating risks associated with a selected emerging technology.

MPE-632: Artificial Intelligence and Governance

Term: Fall

Offered: 2025

Course Objectives:

1) Understand key AI technologies and their relevance to governance.

2) Evaluate the ethical, legal, and societal implications of AI in public administration.

3) Analyze case studies of AI applications in digital government, smart cities, law enforcement, and citizen services.

4) Assess the governance of AI, including regulation, transparency, and accountability mechanisms.

5) Design policy recommendations for ethical and effective AI adoption in government settings.

Course learning outcomes (CLOs)

By the end of the course, the students are expected to be able to:

1. Critically evaluate major theories and frameworks in public administration and governance, and explain how these theories inform the integration and use of artificial intelligence (AI) in public sector decision-making.

2. Analyze the opportunities, challenges, and implications of adopting AI technologies in public sector domains such as policymaking, service delivery, crisis management, budgeting, and citizen engagement.

3. Assess the ethical, legal, and governance dimensions of AI deployment in democratic settings, with emphasis on public trust, transparency, algorithmic bias, and citizen rights.

4. Design and propose evidence-based policy recommendations for effective, equitable, and sustainable AI adoption in public administration, demonstrating awareness of technological, organizational, and societal factors.