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Sessional Lecturer - PPG2012H-S-Topics: Applied AI Systems & Governance: Technology, Policy & Practi
Date Posted: 08/15/2025
Req ID: 44712
Faculty/Division: Faculty of Arts & Science
Department: Munk School of Global Affairs & Public Policy
Campus: St. George (Downtown Toronto)
Description
Course number and title: PPG2012H-S – Topics in Public Policy: Applied AI Systems and Governance - Technology, Policy, and Practice
Course description: This interdisciplinary graduate seminar provides a practical and critical introduction to artificial intelligence (AI) systems and their governance. Designed for future policy leaders, technologists, and analysts, the course blends technical foundations with real-world policy applications to equip students with the knowledge and tools needed to engage with AI at both strategic and operational levels.
Students will learn how modern machine learning models work, explore the global AI supply chain (including chips, data, and compute infrastructure), and use contemporary AI tools to support their own policy research and analysis. The course covers major policy and governance issues, including AI safety and frontier model red-teaming, AI security, responsible AI, copyright and intellectual property, international regulatory approaches, platform governance, and a variety of different approaches and policy frameworks.
Each week combines conceptual learning, real-world case studies, and applied exercises. The course will feature industry leaders as regular guest speakers. Students will gain experience using generative AI, working with datasets, and evaluating AI systems. Final projects will allow students to develop applied policy interventions or technical prototypes that address contemporary challenges in AI governance.
By the end of the course, students will be able to:
* Understand how machine learning systems are developed, deployed, and governed;
* Analyze the implications of AI applications across sectors and geographies;
* Apply AI tools in service of research, policymaking, or program design; and
* Design policy responses grounded in technical realities and societal values.
This is a hands-on course. No coding experience is required, but students should be ready to experiment with AI tools, engage critically with technical concepts, and collaborate on applied assignments.
Estimated course enrolment: 25 students
Estimated TA support: N/A
Class schedule: Mondays 2-4pm
* The delivery method for this course is expected to be in-person. Please note that, in keeping with current circumstances, the course delivery method may change as determined by the Faculty or the Department.
Sessional dates of appointment: January 1, 2026 - April 30, 2026
Salary: Sessional Lecturer I - $9,820.70; Sessional Lecturer I, Long Term - $10,510.04; Sessional Lecturer II - $10,510.04; Sessional Lecturer II (Long Term) - $10,760.28; Sessional Lecturer III - $10,760.28; Sessional Lecturers III (Long Term) - $11,030.36
Please note that should rates stipulated in the collective agreement vary from rates stated in this posting, the rates stated in the collective agreement shall prevail.
Minimum qualifications: Graduate degree in Political Science or related field is required, with specialization in technology. Extensive knowledge of and experience in AI and technology.
Preferred qualifications: Teaching experience at the graduate level preferred. Completed PhD preferred.
Description of duties: Teaching at the graduate level, developing the syllabus, teaching two-hour classes, providing weekly office hours for academic counseling of students, preparing and delivering course material, preparing and delivering assignments and tests, marking student work and submitting grades.
Application procedure: All individuals interested in this position must submit an updated Curriculum Vitae and the CUPE 3902 Unit 3 application form available at https://uoft.me/CUPE-3902-Unit-3-Application-Form to p.jory@utoronto.ca.
Closing Date: 09/05/2025, 11:59PM ET
Employee Group: [[custEmployeeSubgroup]]
Appointment Type: [[custApptmentType]]
Schedule: [[custFullPartTime]]
Pay Scale Group & Hiring Zone: [[custPayScaleGrpHiringRate]]
Job Category: Sessional Instruction
Diversity Statement
The University of Toronto embraces Diversity and is building a culture of belonging that increases our capacity to effectively address and serve the interests of our global community. We strongly encourage applications from Indigenous Peoples, Black and racialized persons, women, persons with disabilities, and people of diverse sexual and gender identities. We value applicants who have demonstrated a commitment to equity, diversity and inclusion and recognize that diverse perspectives, experiences, and expertise are essential to strengthening our academic mission.
As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, please see http://uoft.me/UP.
Accessibility Statement
The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission.
The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.
If you require any accommodations at any point during the application and hiring process, please contact uoft.careers@utoronto.ca.
Job Segment: Public Policy, Political Science, Supply Chain, Government, Legal, Operations, Social Sciences, Research
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