AI is poised to have an enormous impact on society. What should that impact be and who should get to decide it? The goal of this course is to critically examine AI research and deployment pipelines, with in-depth examinations of how we need to understand social structures to understand impact. In application domains, we will examine questions like “who are key stakeholders?”, “who is affected by this technology?” and “who benefits from this technology?”. We will also conversely examine: how can AI help us learn about these domains, and can we build from this knowledge to design AI for "social good"? As a graduate-level course, topics will focus on current research including development and deployment of technologies like large language models and decision support tools, and students will conduct a final research project.
Prerequisites: At least one graduate-level computer science course in Artificial Intelligence or Machine Learning (including NLP, Computer Vision, etc.), two preferred, or permission of the instructor. Students must be comfortable with reading recent research papers and discussing key concepts and ideas.
The current class schedule is below. The schedule is subject to change, particularly the specific readings:
Attendance policy This is a graduate-level course revolving around in-person discussion. Students are expected to attend class and may notify instructors if there are extenuating circumstances.
Course Conduct This is a discussion class focused on controversial topics. All students are expected to respect everyone's perspective and input and to contribute towards creating a welcoming and inclusive climate. We the instructors will strive to make this classroom an inclusive space for all students, and we welcome feedback on ways to improve.
Academic Integrity This course will have a zero-tolerance philosophy regarding plagiarism or other forms of cheating, and incidents of academic dishonesty will be reported. A student who has doubts about how the Honor Code applies to this course should obtain specific guidance from the course instructor before submitting the respective assignment.
Discrimination and Harrasment The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, military status, immigration status or other legally protected characteristic. The University's Discrimination and Harassment Policy and Procedures provides information on how to report or file a complaint of discrimination or harassment based on any of the protected statuses listed in the earlier sentence, and the University’s prompt and equitable response to such complaints.
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