World Data System
Responses
In your opinion, what outcomes would make the first Global Dialogue on AI Governance a success?
Establishment of agreed upon recommendations and even regulations that will lead to more trusted AI outputs, provenance and benefit-sharing for data inputs, and protection of human rights.
From your perspective, which of the following thematic areas identified by the General Assembly Resolution 79/325 for the AI Dialogue reflect your priorities for urgent action and active engagement?
- Safe, secure and trustworthy AI
- Interoperability of governance approaches
- Protection and promotion of human rights
- Open-source software, open data and open AI models
Please briefly explain your selection.
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It is imperative that we can trust AI outputs, which means we need trustworthy AI-ready open data for training, bench marking and ongoing usage. We also need coherent approaches between nations, particularly around legal and ethical usage of data inputs (otherwise it may not be made available in the first place). Moreover, we need better characterization of bias for data inputs, represented in a machine-actionable way, and then determine ways to mitigate that bias.
How are the governance gaps and related developments/advances in the thematic areas you selected above affecting your country, region, or sector? Please highlight the most significant challenges.
With regard to the research data repositories sector, there is certainly work to be done in terms of serving high-quality AI-ready data. There has been a great deal of progress with compliance to the FAIR Principles, but much more needs to be done to have the appropriate machine-actionability and interoperability to support the seamless usage of data at a greater scale.
What role can the AI Dialogue play in advancing international cooperation on AI governance?
This dialogue is an important opportunity to have a multi-sector engagement (e.g., government, industry, academia, Indigenous communities, etc) so that AI governance can be agreed upon in a global and multi-sectoral context.
What are some of the existing initiatives, partnerships, or mechanisms that the AI Dialogue should build upon or connect with, and what added value could the AI Dialogue bring?
There is intersection with the UN CSTD Data Governance working group in regards to data interoperability and cross-border data exchange. It would be useful also to take into account the work that the ISC has done regarding AI in national research ecosystems - https://council.science/our-work/ai-in-national-research-ecosystems/.
How can different stakeholders contribute to the AI Dialogue? Please share recommendations for the format and structure of the AI Dialogue.
While in-person dialogues are very helpful, it will be important to have virtual opportunities (spanning different time zones) and asynchronous means for inputs.
Which voices, communities, or perspectives are currently underrepresented in global discussions on AI governance? How could they be included?
Indigenous communities, research data infrastructure experts
Please share examples of policies, practices, platforms, or approaches that promote effective AI governance or offer concrete solutions to addressing its challenges.
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Creative Commons Signals - https://creativecommons.org/cc-signals/ Local Contexts Labels - https://localcontexts.org/