Responsible AI challenges require a multidisciplinary approach, in which tech and law are natural partners. In our talk we will present our approach of facilitating the dialogue between Data Scientists and Lawyers, stemming from a course we taught in 2020. Our experience and insights from the course are relevant in the broader context of building a bridge between both professions, in a manner that could be implemented in other settings, such as in policy-making, civil society organizations and the tech industry.
Website: http://learn.responsibly.ai/
SkillShare video (10 min): https://vimeo.com/showcase/8165282/video/523160994
Q&A Session: https://gradu.al/mozfest/sessions/data-science-meets-law-learning-responsible-ai-together/
Getting familiar with a methodological toolbox for facilitating a multidisciplinary dialogue about Responsible AI.
We're hoping that many efforts and discussions will continue after Mozfest. Share any ideas you already have for how to continue the work from your session.:- In 2021 we will release the materials of the course under CC license.
2 We will set up a mailing list of participants and others that are interested in using our methods ad
It is a short presentation with a Q&A session, so it scales well for different sizes of audience.
Shlomi is a computer science Ph.D. student at Boston University working on responsible AI. In his previous life, Shlomi was a social entrepreneur and research team leader in cybersecurity.
Karni Chagal-Feferkorn is a Scotia Bank post-doctorate fellow at the University of Ottawa where she researches AI regulation.