Expert opinions on AI Ethics

The first is the danger that AI becomes so capable that humans lose control of it. This is the existential-risk scenario that dominates Silicon Valley’s safety debate. The ultimate threat is not China, the US or any particular lab. Rather, it is an a...

Much has been said about whether AI poses an ultimate existential threat to humanity. The more immediate existential challenge may be whether technologies that simulate relationships weaken our capacity for the relationships that foster our own human...

I’m not a doomer. This talk about human extinction is over the top. [...] The idea that these swarms of AI agents might jump the fence and take over a banking system or take over a water system or, God forbid, take over a hospital.

Before, or concurrently with, deploying a new frontier model or a substantially modified version of an existing frontier model, a large frontier developer shall include in the transparency report required by paragraph (a) of this subdivision, summari...

For the most advanced frontier AI models, an independent, federally overseen, industry-backed organization could set safety standards and verify independent, voluntary audits, similar to how other critical sectors are managed.

I believe we're there now, and I believe the current models will take us there. The future is just so amazing that we are lucky enough to be born at this moment of time, right when everything is like bursting into a big bang of consciousness.

We will not just one day have an easy answer where everybody will agree.

AI cannot become conscious, nor can any machine aspect of technology or humanity.

This suggests pacing the advances: not training or deploying AIs without a strong safety case that convinces independent experts.

I believe that attempting to deliberately pace AI development will be extremely difficult, and could do more harm than good if done without proper care. However, I am signing this statement because, if an attempt at pacing does occur, it would be bet...

Banning advances in artificial intelligence would be a profound mistake. More capable AI systems could accelerate medical breakthroughs, advance scientific research, improve productivity, and lower costs for American families. With policymakers focus...

Middle powers should combine complementary national assets and pool the capabilities that require scale, while preserving national and commercial control over applications, deployment, language, and sector-specific use. Shared efforts could include m...

The answer isn't convergence for its own sake. We can push too hard on one thing. But if you have one standard, you could risk a lowest common denominator outcome that can cost us the innovation system as well and might have a risk on the national in...

A model that explains itself less isn't more aligned, it's just harder to catch when it goes wrong.

We have a very natural instinct to say: we want as much interpretability as possible. One of the sci-fi worry cases is that agents start speaking in languages to each other that we don't understand. [...] I bet there are ways to define boundaries tha...

Explainable AI (XAI) is often offered as the answer to the black box problem and is broadly defined as “machine learning techniques that make it possible for human users to understand, appropriately trust, and effectively manage AI.” Around the world...

Gemini, of course, is very much focused on building AGI and delivering the goals. [...] To build AGI, something that you can put in front of people that they can work with. [...] Success in building AGI still depends on innovation and exploration and...

Many leading companies are engaged in a single-minded pursuit of artificial general intelligence (AGI). [...] Rather than racing to replace people, we should build AI tools that amplify human expertise and expand opportunity.

The way to get there is a shared machine-readable format. I call it a Safety Framework Card.

Countries should not restrict open-weight AI models.

One of its more interesting recommendations is something called Mutually Assured Compute Destruction. America would build its new datacentres in Mongolia and China would build theirs in Canada. If the agreement collapsed, each side would destroy its ...

A doctrine whose trigger mechanism can be this thoroughly disputed cannot function as a deterrent. Deterrence requires certainty. MAD worked because both sides knew, with something close to certainty, what a launch would produce. MACD, as currently s...