Teaching & Learning Responsible AI
**Postponed to May 2022**
Tel Aviv University
The purpose of the workshop is to bring together educators from the fields of data science, computer science, engineering, law, social sciences and humanities interested in teaching students and professionals, to implement a “responsible and ethical approach” when developing AI systems in particular, and computing systems in general.
Learning from the experience of participants who have been teaching various courses to different disciplines and engaging in hands-on exercises, the workshop will discuss, exemplify, and provide tools for multidisciplinary dialogue among students and professionals from different “worlds” when designing responsible AI and computing systems.
The workshop’s key components and goals:
Community build-up: Creating a community for continuous exchange of teaching experience and insights, with an emphasis on joint courses for law students, data/computer scientists and other related disciplines. The community will facilitate collaborations between institutions in offering joint courses together.
Sharing teaching tools: The workshop will include a panel with short presentations by designated participants, sharing course designs, teaching strategies, case studies, class assignments, and innovative methodologies.
Learning responsible AI Together: The workshop will consist of a “hands-on” learning experience where legal and ethical issues pertaining to AI technologies are discussed and interactively resolved by lawyers, data scientists and other disciplines working together.
08:30 – 09:00 | Registration and light breakfast
09:00 – 09:30 | Welcome and contextualizing the workshop
09:30 – 10:30 | “A Multidisciplinary Approach to Teaching Responsible AI: Challenges and Opportunities” panel
- Hagit Messer-Yaron
- Shafi Goldwasser (TBC)
- Orit Hazzan
- Niva Elkin-Koren
- Katrina Ligett
Moderator: Avigdor Gal
10:30 – 11:00 | Coffee break
11:00 – 13:00 | Responsible AI – an interactive learning activity
The participants will be invited to actively engage in a Responsible AI learning activity that involves a multidisciplinary dialogue. The activity requires making decisions on the design of a data-driven system while balancing values and trading off engineering constraints.
The activity serves as a concrete context to reflect on the challenges and opportunities involved in teaching Responsible AI in a multidisciplinary setting.
13:00 – 14:00 | Lunch
14:00 – 14:45 | Lightning talks
Participants are welcome to give a 5-minutes talk and share their own experience, insights, tips and research about Responsible AI, and particularly about teaching this topic.
14:45 – 15:00 | Coffee break
15:00 – 17:15 | Round tables: building a community of Responsible AI educators
- How do we build a community of educators (Inclusivity, Collaboration, Materials, Training)?
- How should the first class of a multidisciplinary course look like?
- How do we evaluate multidisciplinary learning in CS/DS and Law?
- Which (additional) disciplines ought to take part?
17:15 – 17:30 | Workshop closing and farewell
Time: J̶a̶n̶u̶a̶r̶y̶ ̶1̶0̶,̶ ̶2̶0̶2̶2̶ Postponed to May 2022
Location: Tel Aviv University (Room TBC)
Intention to participate / contribute
Since place is limited, those interested in participating are requested to fill the following online form. Confirmations of participation will be sent on a rolling basis.
Limited travel budget may be available for those arriving from overseas with no travel budget.
The most updated regulations for entering Israel are published on this Ministry of Health website.
In short, entrance is allowed to persons who have been vaccinated with two doses (or one dose in the case of the Johnson and Johnson vaccine) and at least 14 days pass from the second dose on the day of arrival in Israel (but no more than 180 days at the day of departure from Israel) and to people who have been vaccinated with the booster shot and 14 days or more pass from vaccination day at the day of arrival in Israel.
These regulations are subject to change, but we don’t expect them to become more flexible in the near future.
Prof. Niva Elkin-Koren, Tel Aviv University
Prof. Avigdor Gal, Technion
Dr. Karni Chagal-Feferkorn, University of Ottawa
Shlomi Hod, Boston University
Hofit Wasserman Rozen, Tel Aviv University