Generative artificial intelligence (AI) tools use machine learning models trained on massive pools of information to learn patterns from data to create novel content like text, images, audio, or video in response to a prompt. Unlike internet searches, generative AI tools do not use algorithms to locate and curate existing sources. Instead, they create new content by predicting what word, sound, or pixel would come next in a pattern.

The revolution in the capabilities and availability of generative AI tools has caused both excitement and consternation in higher education, not always in equal measure. At the Teaching Center, we acknowledge both the potential benefits and the challenges of using generative AI technologies to enhance our academic work, and especially to support our teaching and learning, across the entire Pitt community.

When considering academic integrity in the use of generative AI tools, we must consider inclusive teaching strategies as well as Ai detection tools. AI detection tool are becoming ubiquitous. However, their accuracy varies considerably. The creators of many of these tools claim extremely high accuracy rates in spotting AI-generated content.

The Ad Hoc Committee on Generative AI in Research and Education, a combined initiative of the Offices of the Provost and the Senior Vice Chancellor for Research, will coordinate with the Faculty Senate and includes faculty, staff, and student members. Its charge is to “explore the potential uses and abuses of this rapidly evolving new tool.”

Information on generative AI events, links to resources, tools and strategies, and other lists and bibliographies.

A longtime favorite of disciplines that rely on paper-and-pencil classwork and testing, Gradescope can support faculty efforts to solve for ChatGPT and other academic integrity risks during testing.