The Future of AI: A Framework for Governance
The AI Revolution is Here
Artificial intelligence is advancing at a breakneck pace. What used to take computation models days can now be done in minutes, and while the training costs have gone up dramatically, they will soon go down as developers learn to do more with less. I’ve said it before, and I’ll repeat it — the future of AI is now.
A Framework for AI Governance
To anyone in the field, this is not surprising. Computer scientists have been hard at work; companies have been innovating for years. What is surprising — and eyebrow-raising — is the seeming lack of an overarching framework for the governance of AI. Yes, AI is progressing rapidly — and with that comes the necessity of ensuring that it benefits all of humanity.
Principles for the Future of AI Policymaking
As a technologist and educator, I feel strongly that each of us in the global AI ecosystem is responsible for both advancing the technology and ensuring a human-centred approach. It’s a difficult task, one that merits a structured set of guidelines. In preparation for next week’s AI Action Summit in Paris, I’ve laid out three fundamental principles for the future of AI policymaking.
Use Science, Not Science Fiction
The foundation of scientific work is the principled reliance on empirical data and rigorous research. The same approach should be applied to AI governance. While futuristic scenarios capture our imagination — whether utopia or apocalypse — effective policymaking demands a clear-eyed view of current reality.
Be Pragmatic, Rather than Ideological
Despite its rapid progression, the field of AI is still in its infancy, with its greatest contributions ahead. That being the case, policies about what can and cannot be built must be crafted pragmatically, to minimize unintended consequences while incentivizing innovation.
Empower the AI Ecosystem
The technology can inspire students, help us care for our ageing population and innovate solutions for cleaner energy — and the best innovations come about through collaboration. It’s therefore all the more important that policymakers empower the entire AI ecosystem — including open-source communities and academia.
Conclusion
The AI revolution is here — and I am excited. We have the potential to dramatically improve our human condition in an AI-powered world but to make that a reality, we need governance that is empirical, collaborative and deeply rooted in human-centred values.
FAQs
Q: What are the key principles for the future of AI policymaking?
A: Use science, not science fiction; be pragmatic, rather than ideological; and empower the AI ecosystem.
Q: Why is it important to focus on current reality when making AI policy?
A: It is necessary to ensure that policies are grounded in technical reality and not distracted by far-fetched scenarios.
Q: How can policymakers minimize unintended consequences while incentivizing innovation?
A: By crafting pragmatic policies that balance the needs of the technology with the needs of society.
Q: Why is open access to AI models and computational tools important?
A: Limiting access will create barriers and slow innovation, particularly for academic institutions and researchers.
