Education for the Leaders of Today and Tomorrow
Working with faculty and expert practitioners, the HAI Education team creates multidisciplinary programs for both high-impact decision makers and emerging leaders. Our portfolio of programs helps people pursue cutting-edge research, create useful and responsible AI, and respond thoughtfully to the societal and ethical implications of global AI-- whether in government, business, higher education, K-12, civil society, or as informed citizens.
Featured 2022 Programs
Stanford faculty offer courses for senior executives and key decision-makers.
Summer program for current 9th graders aimed to increase diversity in the field of AI.
Stanford Affiliates
Launching courses and programs to enable cutting-edge research, create useful and responsible AI applications, and respond thoughtfully to the social implications of AI.
External Audiences
Focusing on the societal impact of AI technologies and the opportunities to share expertise through global connections.
Call for Proposals Now Open!
HAI is expanding its Education portfolio and welcomes proposals from Stanford faculty, departments, and centers for programs targeting Stanford Audiences or External Audiences.
Courses for Stanford Students
AI - Activism - Art (ARTHIST 168A, CSRE 106A, ENGLISH 106A, SYMSYS 168A)
The Rise of Digital Culture
Turner
Theoretical Neuroscience
Ganguli; Yamins
Artificial Intelligence Applications in the AEC Industry
Fischer
Computers, Ethics, and Public Policy
Winstein
AI for Social Good
Piech
Artificial Intelligence: Principles and Techniques
Various
General Game Playing
Genesereth
Computer Vision and Image Analysis of Art
Stork
Design for Artificial Intelligence
Stanford
Artificial Intelligence for Disease Diagnosis and Information Recommendations
Seminar on AI Safety
Sadigh
Data Science and AI for COVID-19
Zou
Digital Civil Society
Bernholz; Nothias; Pace; Panezi; Willse
Designing AI to Cultivate Human Well-Being
Aaker; Li
Digital Technology and Law
Engstrom
AI and Rule of Law: A Global Perspective
Engstrom; Schaake
Politics of Data: Algorithmic Culture, Big Data, and Information Waste
Edwards
HPC-AI Summer Seminar Series
Jones
Machine Learning and Causal Inference
Athey; Wager
Modern Applied Statistics: Data Mining
Friedman
Data-driven Modeling of COVID-19
Kuhl
(BIODS 220, CS 271)
Artificial Intelligence in Healthcare
Yeung
Discussion: Robot Ethics
Lemley
Computer Vision: Foundations and Applications
Niebles; Wu
The Economic Impact of Artificial Intelligence (Economic Policy Seminar)
Toloui
Technology and the 2020 Election
Reich; Shaake
Race in Technology
Edwards
A.I.-Activism-Art
Elam
Ethics, Public Policy, and Technological Change
Reich; Sahami; Weinstein
Designing Machine Learning: A Multidisciplinary Approach
Callaghan; Carney
Interactive and Embodied Learning
Haber; Li
Curiosity in Artificial Intelligence
Haber
Policy Practicum: Creating a National Research Cloud
Ho; Wald
Designing Machine Learning: A Multidisciplinary Approach
Callaghan; Carney
Frontier Technology: Understanding and Preparing for Technology in the Next Economy
Fischer; Fu
Philosophy of Artificial Intelligence
Etchemendy
Data-Driven Impact
Athey
Economics of Digitization
Brynjolfsson
Law for Computer Science Professionals
Hansen
The Ethics, Law and Politics of Artificial Intelligence (PHIL 78E)
Keeling
Knowledge Graphs
Chaudhri
Contemporary Moral Problems (ETHICSOC 185M, PHIL 72)
Karhu
Governing Artificial Intelligence: Law, Policy, and Institutions
Cuellar, Engstrom, Schaake
Artificial Intelligence in Medicine and Healthcare Ventures
Adeli
Intro to Logic Programming
Genesereth
Computational Law (Law 4019)
Genesereth
Technological, Economic and Business Forces Transforming the Private Practice of Law
Yoon
People Analytics
Goldberg
External Education & Distance Learning
The Value of Data and AI: Strategies for Senior Leadership
Zou, Athey, Brynjolfsson
Harnessing AI and Big Data: Analysis to Action
Oyer
Education Resources
Outreach Programs
Various
Various
Various
Harnessing Design Thinking, Ethics, and the Power of AI for Social Innovation
Various
Manning; See
Artificial Intelligence: Principles and Techniques
Wu; Hashimoto
Machine Learning
Charikar; Ma ; Re
Convolutional Neural Networks for Visual Recognition
Krishna; Li; Xu
Deep Learning
Katanforoosh; Ng
Human Computer Interaction Seminar
Bernstein
Interdisciplinary Training in Cognitive Science and AI Research
Various
Fundamentals of Data Science
Public Events
Public Events
If you would like to submit a course to be featured, please email hai-institute@stanford.edu