Toward a Fair and Inclusive Future of Work with ChatGPT

Despite the growing use of ChatGPT and other emerging AI techniques, there is currently no systematic method to evaluate their performance and potential risks comprehensively. This gap in evaluation frameworks hampers our understanding of the full impact of generative AI on various communities and domains. To address these concerns and bridge the evaluation gap, we would like to study and analyze the impact of generative AI on a wide range of communities.

Toward a Fair and Inclusive Future of Work with ChatGPT, a DSI Emerging Data Science Program, is focused on the responsible development and ethical implementation of generative AI, specifically examining the impact of ChatGPT on diverse communities. By delving into the societal implications of using ChatGPT, the Program aims to equips researchers and users with a deeper understanding of the potential social impact and ethical considerations associated with these technologies. Through increased awareness and knowledge, users of ChatGPT will be able to navigate its usage with confidence, making informed decisions and employing responsible practices. This empowerment ensures that the broader community can harness the capabilities of generative AI while mitigating potential risks and promoting ethical use. By bridging the gap between academia and real-world applications, the project fosters a comprehensive understanding of the social implications of ChatGPT, benefiting both the academic community and the broader user base, and ultimately contributing to the responsible and impactful development of generative AI technologies.

As a starting point, we use ChatGPT as a study subject to design, develop, and evaluate a platform that aims to comprehensively assess the capabilities, limitations, and ethical considerations of generative AI. This will enable the development of guidelines, policies, and safeguards that can guide the responsible and ethical use of generative AI in various domains, promoting trust, accountability, and transparency in the AI ecosystem.

To achieve comprehensive insights, the Program will feature talks, discussions, and participatory design sessions, individuals from various backgrounds including students, instructors, practitioners, academics, and artists, will get the opportunity to share their perspectives and experiences with ChatGPT. Workshops and public-facing meetups will be organized in order to foster inclusivity and encourage open dialogue, amplifying the voices of minority communities.  The Program will also develop a comprehensive course syllabus module to equip students with a well-rounded understanding of the ethical considerations surrounding generative AI. By promoting collaboration and knowledge exchange, the Program aims to pave the way for responsible and informed AI practitioners across diverse domains.

News & Upcoming Events

Participate in our current interview study on Understanding the Role of Large Language Models in Scientific Software Development.

Stay tuned for upcoming events and activities. 

Events and opportunities

Speaker Series

Discussions with diverse communities to share their valuable insights and opinions on the opportunities and challenges posed by ChatGPT




Participatory Design Sessions

Students will engage in projects that incorporate the use of ChatGPT within their workflows. This will be showcased through a poster presentation, allowing students to share their experiences and findings with the wider community, fostering collaboration and knowledge exchange.

Academic Workshops

Co-located with other main conferences such as CHI, CSCW, and NeurIPS. These workshops will serve as platforms to share the results, methodologies, and insights gained from studying the impact of ChatGPT

January 26 – 27, 2024
Fairness – ChatGPT Workshop

Events

Meetups aimed at creating a welcoming environment for the public including minority communities to share their opinions on ChatGPT and generative AI




Co-Leads

Syed Ishtiaque Ahmed

Assistant Professor, Department of Computer Science, Faculty of Arts & Science, University of Toronto

Lisa Austin

Professor, Faculty of Law,
University of Toronto

Shion Guha

Assistant Professor, Faculty of Information, University of Toronto

Anastasia Kuzminykh

Assistant Professor, Faculty of Information, University of Toronto

Shurui Zhou

Assistant Professor, Edward Departments of Electrical & Computer Engineering, Computer Science, and Mechanical & Industrial Engineering, University of Toronto