Sessional Lecturer - PPG2012H-S-Topics: Applied AI Systems & Governance: Technology, Policy & Practi
About the role
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
About University of Toronto
Founded in 1827, the University of Toronto is Canada’s top university with a long history of challenging the impossible and transforming society through the ingenuity and resolve of our faculty, students, alumni, and supporters.
We are proud to be one of the world’s top research-intensive universities, bringing together top minds from every conceivable background and discipline to collaborate on the world’s most pressing challenges. As a catalyst for discovery, innovation, and progress, we prepare our students for success through an outstanding global education and commitment to inclusive excellence.
The ideas, innovations, and actions of more than 660,000 graduates advance U of T’s impact on communities across the globe.
Sessional Lecturer - PPG2012H-S-Topics: Applied AI Systems & Governance: Technology, Policy & Practi
About the role
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
About University of Toronto
Founded in 1827, the University of Toronto is Canada’s top university with a long history of challenging the impossible and transforming society through the ingenuity and resolve of our faculty, students, alumni, and supporters.
We are proud to be one of the world’s top research-intensive universities, bringing together top minds from every conceivable background and discipline to collaborate on the world’s most pressing challenges. As a catalyst for discovery, innovation, and progress, we prepare our students for success through an outstanding global education and commitment to inclusive excellence.
The ideas, innovations, and actions of more than 660,000 graduates advance U of T’s impact on communities across the globe.