Sessional Lecturer, INF2207H - Practical Elements of Responsible AI Development

Toronto, ON, CA

University of Toronto

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University of Toronto
Faculty of Information

Sessional Lecturer

Fall Term 2025 (September - December)

 

INF2207H - Practical Elements of Responsible AI Development

Course Description: Responsible Artificial Intelligence (RAI) is about ensuring that socioenvironmental responsibility is a fundamental and permeating consideration in all stages (conception, evaluation, deployment, monitoring, etc.) of AI development and governance. This is necessary to address and prevent harms and injustices, setting the course of AI development in a direction of sustainable benefit to our interconnected world. RAI requires a thoughtful and pragmatic synthesis of approaches from wide-ranging fields. The course (INF2207H: Practical Elements of Responsible AI Development) covers an evolving set of relevant topics such as user studies, participatory design, statistical significance testing, model comparison, generalization, randomized control trials, bias, interpretability and explainability, FAccT (fairness, accountability, transparency), equity, ethics, safety, alignment, robustness, scientific communication, stakeholder consultations, data governance, power and exploitation, digital labour, peer review, reliability engineering, information security, privacy, verification, auditing, reproducibility, red-teaming, unit-testing, sandboxing, scenario planning, risk, and impact analysis.

 

INF2207H - Practical Elements of Responsible AI Development

 

Estimate of the course enrolment: 35

 

Estimate of TA Support: None anticipated. Estimate of 75 hours with enrollment of 36 or greater. Allocation of TA hours, if any, will be based on enrolment numbers. 

 

Class Schedule: TBD. You are required to be located in geographical proximity to the applicable University premises in order to attend and perform your duties on University premises as of the Starting Date.

 

Sessional dates of appointment: September 1, 2025 – December 31, 2025

 

Salary: 
Sessional Lecturer I: $10,300
Sessional Lecturer I Long Term: $10,764
Sessional Lecturer II $11,021
Sessional Lecturer II Long Term: $11,227
Sessional Lecturer III: $11,279
Sessional Lecturer III Long Term: $11,485

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.

 

Qualifications: Preferably candidates will have a completed, or nearly completed, PhD degree in an area related to the course or a Master’s degree plus extensive professional experience in an area related to the course. Teaching experience is preferred.

 

Brief description of duties: Preparing course materials; delivering course content (e.g., seminars, lectures, and labs); developing and administering course assignments, tests & exams; grading; holding regular office hours. 

 

Application Deadline: May 22, 2025

 

Application Process: Applicants must submit a CV and a completed CUPE 3902 Unit 3 application form in one pdf file to the attention of:  

 

Melissa Szopa, Administrative Coordinator, Academic
Faculty of Information, 140 St. George Street 
University of Toronto
sessional.ischool@utoronto.ca

This job is posted in accordance with the CUPE 3902 Unit 3 Collective Agreement. Preference in hiring is given to qualified individuals advanced to the rank of Sessional Lecturer II and Sessional Lecturer III in accordance with Article 14:12.

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Category: Deep Learning Jobs

Tags: Data governance Engineering PhD Privacy Responsible AI Security Statistics Teaching Testing

Perks/benefits: Equity / stock options

Region: North America
Country: Canada

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