Import AI 468: 23 RSI ideas; PostTrainBench+; and how trust and transparency interplay with AI racing

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Want to be able to deal with RSI? Here are 23 actionable policy ideas: …IFP serves up some “low-regret” policy recommendations… Policy experts with think tank IFP have published a set of ideas meant to help “policymakers begin addressing the risks of further automating AI R&D”. The recommendations involve 23 specific ideas falling across 7 specific categories. If adopted, these recommendations would also give countries, especially the United States, more moves they can make on the gameboard as powerful systems are developed, ideally giving them the ability to:

Accelerate “the diffusion of AI capabilities, by allocating compute and talent towards inference and the development of new AI applications”.

Looking ahead - dangerous capability training and iterative deployment: More speculatively, Thinking Machines is thinking about whether we can selectively filter out dangerous knowledge, for instance CBRN development guides at the point of pre-training, in such a way that it doesn’t damage general intelligence. Another idea of interest is iterative deployment, for instance releasing things in stages, first as a proprietary API, then perhaps as a fine-tuning API that backs onto the underlying model, then the model itself. Why this matters - liberty versus paternalism: What the world does with open weight models will define the level of individual sovereignty and liberty available to all of us with regard to AI. Our ability to “choose our own destiny” will run through having access to the proverbial means of production for AI systems, which means open weight models. However, having general access to models like this isn’t a simple or foregone conclusion as they bring with them meaningful dual use risks as well as other hard to anticipate issues. “This safe path to open models only works if the ecosystem’s defenses improve as quickly as the models do,” Thinking Machines writes. “We will do our part: deciding carefully what to release, and researching how to decouple intelligence from dangerous capability.” Read more : A Safe Path to Open Weights (Thinking Machines blog) . ***

Accelerate “R&D to make further AI research automation safer, either by improving model safety directly or by boosting societal resilience”.

Develop a risk management strategy for automated AI R&D that accelerates defensive and commercial AI uses

Create option value for international cooperation on managing automated AI R&D risks”