DataLearn: AI Governance and You!

AI holds great promise to advance technology, increase efficiency and introduce revolutionary tools into our lives. However, AI and other data analytics systems have often been implemented without proper safeguards, and have exacerbated certain social ills. In recognition of the potential risks, the Personal Data Protection Commission (PDPC), a government agency, published “A Proposed Model AI Governance Framework” in January 2019. The Model Framework introduced some safeguards for the development and deployment of AI, and encouraged companies to adopt those safeguards in their internal governance. The PDPC called on the public to provide feedback, so as to improve upon the current proposed framework.

Answering the call for feedback, DataKind SG in partnership with Effective Altruism SG have prepared a detailed paragraph-by-paragraph response to the model framework. https://npwg-ai-sg.github.io/

In this DataLearn, we will start with a primer on AI Governance to get everyone quickly up to speed on the issues at hand. Then we dive into the meat of our response by inviting the key response contributors to discuss what drove them write this document and the major themes in within it.

Armed with this information, we hope you can better guide your respective organisations around the pitfalls of actual AI implementations to society as a whole.

Panelists:
Cheng Herng Yi
Doctoral Candidate, Department of Mathematics, University of Toronto

Tan Zhi Xuan
Board Member, Effective Altruism SG
Doctoral Candidate, MIT Electrical Engineering & Computer Science

Loke Jia Yuan
Research Associate, Centre for AI and Data Governance, SMU

Jeremy Osborn
Core Lead, DataKind SG

Moderator:
Chan Wai Mun, Raymond
Chapter Lead, DataKind SG

Timeline:
1400 - 1415 hrs: Registration/Networking
1415 - 1445 hrs: Primer on AI Governance
1445 - 1515 hrs: Panel Discussion
1515 - 1530 hrs: Q and A
1530 - 1545 hrs: Informal conversations