ICS 691D: Human-Centered Artificial Intelligence
Graduate course, ICS Department, University of Hawaiʻi at Mānoa, 2022
This is a discussion-based course covering the latest research in human-centered artificial intelligence (HAI). Topics covered include: interactive ML systems, explainable & interpretable ML, AI for healthcare, fairness & bias, privacy, crowdsourcing, HCI evaluations of AI-powered systems, and ethical frameworks applied to AI.
This is an unofficial and condensed copy of the course syllabus for public viewing. The official syllabus with all formal UHM policies and assignment submission details is available to course students on Laulima.
Coursework: Coursework includes in-class discussions and presentations, leading a discussion on a chosen topic from the syllabus, research paper reading assignments with weekly structured one-page reflections, developing a structured project proposal with preliminary data, and writing a three-page review of one of the topics discussed.
Grading: Grading will consist of a combination of a written work, presentations, and participation. Specifically, the breakdown is as follows:
- Paper reflection paragraphs: 20% (up to 5 can be dropped; extra credit if not dropped)
- Topic review paper: 20%
- Project proposal: 30%
- In-class presentations: 10%
- Participation and attendance: 10%
- Leading discussion on chosen topic: 10%
Recommended prerequisites to get the most out of this course include ICS 235 (Machine Learning Methods), ICS 434 (Data Science Fundamentals), and ICS 435 (Machine Learning Fundamentals).
| Date | Topic | Pre-Class Readings (before class) | Assignment Due (midnight before class) |
|---|---|---|---|
| Mon Aug 22 | Course Overview | ||
| Wed Aug 24 | ML Review | Greener Nature Reviews 2022 | Greener reflection |
| Mon Aug 29 | Deep Learning Review | Dong Computer Science Review 2021 | Literature review + discussion leading topics |
| Wed Aug 31 | Reinforcement Learning | Arulkumaran IEEE Signal Processing 2017 | Proposal topic |
| Mon Sep 5 | Labor Day Holiday | ||
| Wed Sep 7 | Interactive ML | Haber NeurIPS 2018 | Haber reflection |
| Mon Sep 12 | Robotics | Akalin Sensors 2021 | Akalin reflection |
| Wed Sep 14 | Autonomous Vehicles | Kohli FICC 2019 | Kohli reflection |
| Mon Sep 19 | Active Learning | Olsson 2009 | Olsson reflection |
| Wed Sep 21 | Crowdsourcing | Vaughan JMLR 2017 | Vaughan reflection |
| Mon Sep 26 | Human-Computer Interaction | Dove CHI 2017 | Dove reflection |
| Wed Sep 28 | Interpretable ML | Došilović MIPRO 2018 | Došilović reflection |
| Mon Oct 3 | Literature Review Presentations | Literature review writeup (3 pages) | |
| Wed Oct 5 | Literature Review Presentations | ||
| Mon Oct 10 | Explainable ML | Alqaraawi IUI 2020 | Alqaraawi reflection |
| Wed Oct 12 | Communicating ML results | Varoquaux Neuroimage 2018 | Varoquaux reflection |
| Mon Oct 17 | Differential Privacy (remote on Zoom) | Chen Biocomputing 2020 | Chen reflection |
| Wed Oct 19 | Federated Learning | Rieke NPJ Digital Medicine 2018 | Rieke reflection |
| Mon Oct 24 | Bias | Mehrabi ACM Computing Surveys 2021 | Mehrabi relfection |
| Wed Oct 26 | Fairness | Holstein CHI 2019 | Holstein reflection |
| Mon Oct 31 | Proposal Checkin Presentations | Proposal outline | |
| Wed Nov 2 | Proposal Checkin Presentations | ||
| Mon Nov 7 | Ethics | Char NEJM 2018 | Char reflection |
| Wed Nov 9 | Generative Models | Lyu ICMEW 2020 | Lyu reflection |
| Mon Nov 14 | Natural Language Processing | Mishev IEEE Access 2020 | Mishev reflection |
| Wed Nov 16 | Biology | Zou Nature Genetics 2019 | Zou reflection |
| Mon Nov 21 | Medicine and Health | Hannun Nature Medicine 2019 | Hannun reflection |
| Wed Nov 23 | Digital Phenotyping | Omberg Nature Biotechnology 2022 | Omberg reflection |
| Mon Nov 28 | Social Network Analysis | Smith PNAS 2021 | Smith reflection |
| Wed Nov 30 | Course Summary | ||
| Mon Dec 5 | Final Proposal Presentations | Final project proposal (5 pages) | |
| Wed Dec 7 | Final Proposal Presentations |