Harvard Hosts AI Pilot Series in Boston

The Harvard T.H. Chan School of Public Health recently concluded a four-part series on artificial intelligence.

Updated on Oct. 21, 2026 in Artificial Intelligence

Sunlit atrium of a classic brick academic building with polished wood floors and high glass windows, reflecting a quiet research institution. — The Harvard T.H. Chan School of Public Health recently completed a four-part pilot series guiding over 100 participants in the ethical use of artificial intelligence. AI Illustration. Upload story photo >

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Over 100 community members at the Harvard T.H. Chan School of Public Health participated in a pilot series exploring artificial intelligence applications. The program focused on building awareness and judgment regarding ethical AI usage in public health.

Why it matters

The series aimed to help researchers and students navigate the ethical implications and limitations of AI tools in academic and professional settings. It emphasized the importance of developing critical judgment when integrating AI into scholarly workflows.

The pilot series featured four sessions demonstrating generative AI tools and evaluating their performance against research standards. Participants analyzed AI-generated citations and datasets to identify hallucinations and errors.

The players

Harvard T.H. Chan School of Public Health

This is a graduate professional school within Harvard University that focuses on public health research and education.

Countway Library

It serves as the main library for Harvard Medical School and the Harvard T.H. Chan School of Public Health.

The details

Led by faculty and library staff, the program addressed generative AI's capacity for tasks like drafting emails and summarizing notes while highlighting its failure to communicate uncertainty or consistently provide factual text. Experts noted that proprietary subscription models often prevent LLMs from accessing key research databases.

The pilot series began in mid-September 2026.
The final session concluded in early October 2026.

The Tech Race

This initiative tracks with the growing effort by academic institutions to standardize AI literacy as generative models replace traditional research tools. It positions the university against the rapid, often unregulated adoption of LLMs in professional data analysis.

Students and faculty learned how to better verify the accuracy of AI-generated content, such as image captions and research summaries. This training helps users identify when AI tools fall short due to hallucination risks or limited database access.

The takeaway

Developing a critical eye for AI output is essential when the technology produces plausible but incorrect information. Users should treat AI as a collaborative tool that requires consistent human verification to ensure factual accuracy.