IGF 2023 WS #322 Data Governance and AI : Trade-offs & Challenges

Organizer 1: Pranesh Prakash, Anekaanta Advisory
Organizer 2: Helani Galpaya, 🔒

Speaker 1: JJ Disini, Private Sector, Asia-Pacific Group
Speaker 2: Helani Galpaya, Civil Society, Asia-Pacific Group
Speaker 3: Farzaneh Badii, Civil Society, Asia-Pacific Group
Speaker 4: Pranesh Prakash, Civil Society, Asia-Pacific Group
Speaker 5: Carolina Botero, Civil Society, Latin American and Caribbean Group (GRULAC)


Pranesh Prakash, Civil Society, Asia-Pacific Group

Online Moderator

Helani Galpaya, Civil Society, Asia-Pacific Group


Pranesh Prakash, Civil Society, Asia-Pacific Group


Round Table - 90 Min

Policy Question(s)

1. Data governance policies and architectures involve trade-offs among various objectives. What are they? How have different jurisdictions: (a) explicitly recognized the trade-offs or not; and (b) handled them?
2. When it comes to data that’s used as input for training AI models or the outputs of generative AI, how do different policy imperatives interact? What are the trade-offs involved, e.g., between copyright and innovation and safety and competition ?
3. Are there legislative or policy innovations with potential for replication? Are developing countries learning from each other, or are they learning from developed countries?

What will participants gain from attending this session? Participants will get a better understanding of the debates around the complex data governance questions around topics like data mining for AI, and governmental and industry policies for addressing these, especially from the global South.


Various forms of data governance — from data protection to copyright — are occupying centre stage in discussions around governance, cross-border transfer of data, and even emerging technologies like AI. For instance, there is a robust debate about the ethics of data mining for use in AI, with some asserting that data mining without permission is tantamount to ‘data theft’. This roundtable shall attempt to address the complex ethical and legal issues and trade-offs involved in data governance by using generative AI as a case study.

Expected Outcomes

The participants are expected to leave the conversation better informed about the trade-offs involved in data governance, especially when it comes to AI, as well as insights as to how countries, especially from the Global South, are dealing with these trade-offs in their policies. The discussions at the roundtable will feed into a multi-country report on data governance that’s being funded by IDRC.

Hybrid Format: * The organizers will take part in the preparatory meetings, if any, that are organized by the IGF Secretariat.
* Apart from the moderator, at least one more of the organizers will be present at the venue, and will coordinate participation among local and remote participants using the video-conferencing tools provided by the Secretariat.
* Prior to the roundtable, participants who have confirmed for the roundtable will be asked to provide some broad positions on an Etherpad so that the discussions during the roundtable can be more structured.
* The organizers will use an Etherpad for live collaborative note-taking and for getting questions from participants.