casebash

How did you find them?

Oh, they're actually the bad guys, just folks haven't thought far enough ahead to realise it yet.

Authors of original paper: Samuel G. B. Johnson, Amir-Hossein Karimi, Yoshua Bengio, Nick Chater, Tobias Gerstenberg, Kate Larson, Sydney Levine, Melanie Mitchell, Iyad Rahwan, Bernhard Schölkopf, Igor Grossmann

I'll copy my LinkedIn comment:

"Well done to the UK for not signing the fully compromised Statement on Inclusive and Sustainable Artificial Intelligence for the People and the Planet. Australia shouldn't have signed this statement either given how France intentionally derailed attempts to build a global consensus on how we can develop AI safely.

For those who lack context, the UK organised the AI Safety Summit at Bletchley Park in November 2023 to allow countries to discuss how advanced AI technologies can be discussed safely. There was a mini-conference in Korea, France was given the opportunity to organise the next big conference, a trust they immediately betrayed by changing the event to be about promoting investment in their AI industry.

They renamed the summit to the AI Action Summit and relegated safety from the sole focus to being just one of five focus areas, but not even one of five equally important focus areas, but one that seems to have been purposefully minimized even further.

Within the conference statement safety was reduced to a single paragraph that undermines safety if anything:

“Harnessing the benefits of AI technologies to support our economies and societies depends on advancing Trust and Safety. We commend the role of the Bletchley Park AI Safety Summit and Seoul Summits that have been essential in progressing international cooperation on AI safety and we note the voluntary commitments launched there. We will keep addressing the risks of AI to information integrity and continue the work on AI transparency.”

Let’s break it down: • First, safety is being framed as “trust and safety”. These are not the same things. The word trust appearing first is not as innocent as it appears: trust is the primary goal and safety is secondary to this. This is a very commercial perspective, if people trust your product you can trick them into buying it, even if it isn't actually safe. • Second, trust and safety are not framed as values important in and of themselves, but as subordinate to realising the benefits of these technologies, primarily the "economic benefits". While the development of advanced AI technologies could theoretically create a social surplus that could be taxed and distributed, it's naive to assume that this will be automatic, particularly when the policy mechanisms are this compromised. • Finally, the statement doesn’t commit to continuing to address these risks, but only narrowly to “addressing the risks of AI to information integrity” and “continue the work on AI transparency”. In other words, they’re purposefully downplaying any more significant potential risks, likely because discussing more serious risks would get in the way of convincing companies to invest in France.

Unfortunately, France has sold out humanity for short-term commercial benefit and we may all pay the price."

Most of the comments here only make sense under a model where AI isn't going to become extremely powerful AI in the near term.

If you think upcoming models aren't going to be very powerful, then you'll probably endorse business-as-usual policies such as rejecting any policy that isn't perfect or insisting on a high bar of evidence before regulating.

On the other hand, if you have a world model where AI is going to provide malicious actors with extremely powerful and dangerous technologies within the next few years, then instead of being radical, proposal like this start appearing extremely timid.

Released 9th October, 2023

Will Oprah screw up the AI story?

Quite possibly, but likely not as bad as this article.

Complete clickbait title, assumes that the author's hobby horses are the most important thing in the world, bizarrely argues that crypto hype is an "attack on labour".

I'm not going to try to recap all of that, but, as an example, if you have a sufficiently strong understanding of arithmetic, learning basic modular arithmetic should be effortless, pigeonhole principle completely obvious.

I was quite surprised when I tried applying for a Microsoft internship in uni and they gave me a question on the pigeon-hole principle.

Just thought I'd add a comment as someone who came top of the state in my grade in multiple olympiad competitions:

I always felt that a large part of my advantage came from having a strong understanding of maths from the ground up.

I felt that a lot more people could have gained the same level of understanding as I did if they had been willing to work hard enough, but I also felt that almost no-one would, because it'd be an incredibly hard sell to convince someone to engage in years-long project where they'd go all the way back to kindergarten and rebuild their knowledge from the ground up.

In other words, excellence is often the accumulation of small advantages over time.

I expect this to end up having been one of the worst timed blog posts in history. Open source AI has mostly been good for the world up until now, but we're getting to the point where we're about to find out why open-sourcing sufficiently bad models is a terrible idea.

I'm just going to say it.

The author is an idiot who is using insults as a crutch to make his case.

Did you read the report? It's answer for basically anything contentious was, "views differ"