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An array of programs and classes bridge tech and human wisdom across campus, preparing students to leverage AI critically and ethically.
Dartmouth Engineering students can now pursue an AI track within the Master of Engineering program and a new undergraduate concentration in AI for the bachelor of engineering degree. These programs encompass machine learning, high-dimensional sensing, optimization, and reinforcement learning, emphasizing practical, project-based learning. They build on existing initiatives and focus on teaching students to ask critical questions about AI's human impact to ensure responsible and meaningful use.
The Tuck School of Business has integrated AI throughout its MBA curriculum and introduced several new AI-focused electives, including AI-Driven Analytics & Society, AI for Managers, NLP/Machine Learning in Finance, AI for the C-Suite, AI & Ethics, and Digital Operations. The Tuck Business Bridge Program for undergraduates also incorporates AI training, fostering critical thinking and effective real-world application by blending liberal arts education with practical AI experience. AI offerings are also extended to Tuck's Executive Education programs.
The Geisel School of Medicine is embedding AI into its medical education curriculum, preparing students for the evolving landscape of patient care. First- and second-year courses address the risks of cognitive outsourcing, and the critical and ethical use of AI tools. New platforms like an AI Patient Actor, NeuroBot TA, and ConsultCraft are utilized to enhance clinical skills practice and learning. Furthermore, Geisel's Master of Science in Health Data Science program is expanding training in applying advanced analytics and AI to real-world healthcare challenges.
Dartmouth undergraduates in the Arts and Sciences begin exploring AI early through First-Year Seminars, where they learn to compare AI-generated text with their own writing, assess summary accuracy, and identify 'AI hallucinations.' Computer science and math departments continue to offer foundational courses in machine learning theory and application, which evolve with the field's rapid advancements. Arts and humanities courses encourage imaginative uses of AI and critically examine its societal impacts, including inherent biases and ethical considerations, aligning with the human-centered AI focus of the 70th-anniversary celebration of the 1956 Summer Research Project on AI.