[2020.01.20] Harvard University-KU Joint Conference "AI, Ethics & Data Governance:From Inte

International Conference with specially invited Speakers

*AI, Ethics & Data Governance : From International trends to Korea's New Law

*Date & Time : January 20, 2020 (Mon) 10:30 ~ 16:30

*Location : Korea University, Veritas Hall, B1F, Seong-buk gu, Anam ro 145 Seoul

*Hosted by : Korea University's American Law Center / Open Net Korea / Global Network of Internet and Society Research Centers / Harvard University's Berkman Klein Center / Digital Asia Hub

**Application From : https://forms.gle/cZT5xBC9Fviy7QLg9

As powerful artificial intelligence (AI) and algorithmic technologies are deployed, people around the globe are asking where and why lines are drawn around key issues of ethics and privacy:

Google is using natural language processing algorithm to ‘read’ emails and suggest quick responses to them, and sometimes to report on child porn pushers, but stopped suggesting advertisers relevant to the contents of your emails, for instance, suggesting Mexican restaurants when your email asks your friend for dinner at one. Do we feel more or less infringed if machines make decisions as opposed to humans? Does this change our value judgments about upload filters or intermediary liability safe harbors?

Microsoft refused to install its face-recognition technology for American law enforcement agencies’ street monitoring equipment while providing the same to correctional facilities in China involving a much smaller number of face subjects. Is the dividing line between consent to collection versus consent to comparison, or is there any difference between the two? Does the consent-based framework deal efficiently with the US government’s impending plan to use facial recognition for border checks?

Amazon shut down its hiring algorithm when it could not fairly judge female applicants. Does a solution require adding more women into the training base that the software is trained upon? This could mean less privacy, at least at the collection stage, even if it is later anonymized. Facial recognition is being criticized for not recognizing racial minorities but some call it “a feature not a bug”. Is “inclusive” AI necessarily good? How do you make “good” inclusive AI?

The Global Network of Internet and Society Research Centers (NOC, in short) has conducted a series of conferences and seminars under the theme of AI and Inclusion. Digital Asia Hub has made efforts to bridge the gap between the Global South and the Global North from Asian perspectives. This year, Korea University Law School’s American Law Center join forces with Harvard University’s Berkman Klein Center for Internet & Society, to bring NOC and Digital Asia Hub at one place in Seoul, Korea, on January 20, 2020, together with Open Net Korea, a civil society organization that has worked on the technology and rights issues.

One of the centerpieces of the conference will be the launch of the Principled AI Project, a white paper and data visualization mapping prominent AI ethics principles, presented by Jessica Fjeld of Harvard University’s Cyberlaw Clinic.

Also, in focus will be data governance and AI and how data protection law and open data initiatives affect the inclusiveness of AI. As long as the current development of AI is taking place along the lines of machine learning, governance on the training data to be fed into machine learning will have a decisive impact on AI’s contribution to sustainable and equitable development.

We will also debate how Korea’s three data laws (the Personal Information Protection Act, the Information and Communications Network Act, and the Credit Information Act) that were amended on January 9 would affect AI and data governance in Korea. The main purpose of the amendments is to enable the processing of pseudonymous data for statistics and scientific research without the consent of the data subject.