Our Story
Where AI was Born
In the summer of 1956, a small group of mathematicians and scientists gathered at Dartmouth to deliberate whether human intelligence could be recreated in a machine. Here, in classrooms and corridors, the term "artificial intelligence" was coined, debated, and defined for the first time. Dartmouth became the birthplace of a new scientific field.
Defining a Field
The workshop, formally titled the Dartmouth Summer Research Project on Artificial Intelligence, was convened under the leadership of John McCarthy, then a young mathematics professor at Dartmouth.
Ideas developed during the summer laid the intellectual groundwork that would take hold in universities and laboratories worldwide. Participants like Claude Shannon went on to shape early generations of AI research.
“Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.”
— John McCarthy et al., "A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence," 1955
Expanding Access to Technology
The legacy of 1956 at Dartmouth is a throughline that continues to guide our broader mission of pioneering and democratizing technology.
In the early 1960s, mathematicians John Kemeny and Thomas Kurtz pioneered the Dartmouth Time-Sharing System and created BASIC, a programming language intended to make computer use intuitive and approachable for undergraduates across disciplines, not just specialists. These innovations helped usher in an era when computing was no longer the domain of isolated labs but a tool students could access, learn from, and shape themselves.
Advancing Intelligence, Improving Lives
Today, Dartmouth is pushing that legacy forward by bringing AI into conversation with engineering, medicine, ethics, policy, and the arts—working not just to build smarter machines, but to ensure that intelligent systems are not only powerful, but humane, ethical, and shaped with intention.
Dartmouth researchers are key players in a new National Science Foundation–backed AI Research Institute focused on mental health, bringing together faculty from the Center for Technology and Behavioral Health with experts in computer science and cognitive science. Their work on next-generation, context-aware AI assistants designed for trustworthy behavioral and mental health support underscores our commitment to rigorous, use-inspired research with real-world impact.
At the forefront of Dartmouth’s AI and mental health research is Therabot, a generative AI therapy chatbot developed at the AI and Mental Health Lab led by Nicholas Jacobson, which recently completed the first randomized clinical trial of its kind. In the study, participants with depression, anxiety, and eating-disorder risk experienced significant reductions in symptoms—results that many clinicians say rival what would be expected from traditional outpatient therapy.
Across campus, Dartmouth researchers are applying AI to an unusually broad range of real-world problems. Computer scientists and linguists are building a suite of AI models that can help communities revitalize endangered languages and scripts worldwide. In health care, interdisciplinary teams are developing AI tools like PortalPal to triage and clarify patient portal messages, helping clinicians respond more efficiently. And students are pushing the frontiers of AI ethics and societal understanding, examining how language models’ biases and loyalties shape misinformation and political narratives.
This spirit of innovation also extends to educational research: Dartmouth scientists recently published a study demonstrating how curated AI tools can deliver personalized learning at scale, showing that students place greater trust in AI teaching assistants when they draw from expert-verified sources, pointing toward new paradigms in tailored education.
Ethical leadership is woven throughout these efforts. Dartmouth’s role as a founding member of the International AI Alliance reflects its dedication to fostering responsible innovation that prioritizes safety, trust, and societal benefit, while a Faculty Leadership Group on AI helps shape principled strategies for integrating AI into research and pedagogy.