"At the front of the pack we have these frontier AI developers, and we want them to identify particularly dangerous models ahead of time. Once those mines have been discovered, and the frontier developers keep walking down the minefield, there's going to be all these other people who follow along. And then a really important thing is to make sure that they don't step on the same mines. So you need to put a flag down -- not on the mine, but maybe next to it.
And so what that looks like in practice is maybe once we find that if you train a model in such-and-such a way, then it can produce maybe biological weapons is a useful example, or maybe it has very offensive cyber capabilities that are difficult to defend against. In that case, we just need the regulation to be such that you can't develop those kinds of models." — Markus Anderljung
In today’s episode, host Luisa Rodriguez interviews the Head of Policy at the Centre for the Governance of AI — Markus Anderljung — about all aspects of policy and governance of superhuman AI systems.
Links to learn more, summary and full transcript.
They cover:
- The need for AI governance, including self-replicating models and ChaosGPT
- Whether or not AI companies will willingly accept regulation
- The key regulatory strategies including licencing, risk assessment, auditing, and post-deployment monitoring
- Whether we can be confident that people won't train models covertly and ignore the licencing system
- The progress we’ve made so far in AI governance
- The key weaknesses of these approaches
- The need for external scrutiny of powerful models
- The emergent capabilities problem
- Why it really matters where regulation happens
- Advice for people wanting to pursue a career in this field
- And much more.
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Producer: Keiran Harris
Audio Engineering Lead: Ben Cordell
Technical editing: Simon Monsour and Milo McGuire
Transcriptions: Katy Moore