This course examines artificial intelligence through interdisciplinary lens, connecting political, philosophical, and economic perspectives. Students develop understanding of AI's societal impact while also gaining practical experience with AI tools and governance challenges. The course emphasizes evidence-based reasoning about technological governance, economic disruption, and ethical considerations in AI development and deployment.
Last update: Špecián Petr, Ing., Ph.D. (16.09.2025)
Aim of the course
By the end of this course, students will be able to:
Analyze AI systems using integrated economic, philosophical, and political science approaches.
Apply AI toolsfor research, analysis, and problem-solving while understanding their capabilities, limitations, and appropriate use cases.
Evaluate AI governance policies using interdisciplinary insights.
Assess economic impacts of AI adoption on labor markets, productivity, innovation systems, and distributional outcomes across society.
Examine ethical implications of algorithmic decision-making in social and political contexts.
Last update: Špecián Petr, Ing., Ph.D. (29.07.2025)
Course completion requirements
Midterm Test (30%): Multiple choice and open questions covering lectures 1-5 and related seminar material.
Final Test (30%): Multiple choice and open questions covering the remaining lectures and related seminar material.
Individual Policy Brief (15%): Analysis of a specific AI governance / diffusion / implementation challenge.
Seminar Participation & AI Tool Exercises (25%): Active participation in seminars plus completion of hands-on AI exercises.
Last update: Špecián Petr, Ing., Ph.D. (16.09.2025)
Literature
Russell, Stuart. Human Compatible: Artificial Intelligence and the Problem of Control. Viking, 2019. Selected chapters.
Brynjolfsson, Erik & Andrew McAfee. The Second Machine Age. W. W. Norton, 2014. Selected chapters.
Christian, Brian. The Alignment Problem. W. W. Norton, 2020. Selected chapters.
For specific instructions on readings, see Moodle.
Last update: Špecián Petr, Ing., Ph.D. (29.07.2025)
Teaching methods
AI Use Policy for This Course
In this course, you are expected to engage directly with AI, and you are encouraged to experiment with various tools to understand their capabilities and limitations as you prepare for your assessments.
Permitted & Encouraged Uses (for Preparation):
Using AI tools as specified in seminar exercises and out-of-class assignments.
Brainstorming ideas, exploring topics, and gathering initial research in preparation for your in-class Policy Brief.
Summarizing complex articles to aid your understanding of course material.
A sparring partner for practicing your writing and argumentation.
Limitations: The Final Test and the Policy Brief are designed to assess your ability to synthesize and apply course concepts under exam conditions. Therefore, the use of generative AI or any other unauthorized external assistance is strictly prohibited during these in-class assessments. All work for these assessments must be your own, produced entirely during the allotted time in the classroom. Any violation of this rule will be considered serious academic misconduct.
Instructor's Use of AI and Student Rights
For Teaching and Feedback: The instructor may use AI tools to prepare teaching materials and to provide feedback on student work.
Commitment to Academic Integrity and Privacy: Any use of AI by the instructor will be to supplement, not replace, personal evaluation. Student submissions will not be used to train AI models, and personal data will be protected at all times.
Student's Opt-Out Right: Students have the right to express their disagreement with their work being processed by AI tools for assessment or feedback. If you wish to exercise this right, you must notify the course instructor: either via email sent before your submission, or as a disclaimer clearly visible in your written assignment. This request will be fully respected, and your work will be assessed manually without penalty. All other course requirements and evaluation standards remain identical for all students.
Last update: Špecián Petr, Ing., Ph.D. (22.09.2025)
Syllabus
Week 1: Toward Situational Awareness
What is artificial intelligence? Historical development and current capabilities
Definitional challenges and competing approaches to understanding AI
The challenge of analyzing societal impacts of technological change
Week 2: Economic Foundations of Technological Change
Innovation economics: adoption curves, network effects, and market structures in tech industries
Economics of automation and technological unemployment theories
Creative destruction and productivity paradoxes in digital transformation
Week 3: Intelligence, Rationality, and Decision-Making
Concepts of intelligence, rationality, and consciousness
Comparison between human and artificial reasoning processes
Limitations and promises of current AI systems
Week 4: Political Dimensions of Technological Governance
Political economy of innovation: how governments shape technological development
Regulatory approaches to emerging technologies and democratic participation
Stakeholder analysis in tech policy: industry, government, civil society, academia
Week 5: AI and Labor Markets
Evidence on automation's impact on employment and wages
Skills-biased technological change and polarization of labor markets
