Ines Rangel

[Ines Rangel @ineslrangel]

@AdamRackis @numerounochef 20% of Americans do. https://t.co/m2VaiJ6ctI

[Jacy Reese Anthis @jacyanthis]

Does the public think AIs are sentient? 🤖🧠 Our paper with the first US representative survey on digital minds, AI, Morality, and Sentience (AIMS), was accepted to #CHI2025.

We find that 20% of U.S. adults believe some current AIs are already sentient, and 37% are not sure! 🧵

[Jacy Reese Anthis @jacyanthis]

Does the public think AIs are sentient? 🤖🧠 Our paper with the first US representative survey on digital minds, AI, Morality, and Sentience (AIMS), was accepted to #CHI2025.

We find that 20% of U.S. adults believe some current AIs are already sentient, and 37% are not sure! 🧵

[Anthropic @AnthropicAI]

Today we’re launching the Anthropic Economic Index, a new initiative aimed at understanding AI's impact on the economy over time.

The Index’s first paper analyzes millions of anonymized Claude conversations to reveal how AI is being used today in tasks across the economy.

[Ines Rangel @ineslrangel]

@tracewoodgrains The original post was about the association of a certain smell with Starbucks to sell drinks. She is the certain smell associated with the topic of smell.

[Tyler is finishing a book, slow to reply @TylerAlterman]

In 2015 I was running the big Effective Altruism (EA) conference at the Googleplex when one of the co-founders of DeepMind approached me

He indicated enthusiasm about hiring tons of EAs to his AI org. He asked if he could get up on stage to advertise open positions to EAs – ie people who were passionate about AI safety. I told him I would confer w the other leaders about it

Others believed that a great way to align AGI would be to place EAs at DeepMind & other AGI companies. (At this same conference, Elon and Sam were busy chatting, most likely about their plans to start OpenAI)

I disagreed about this alignment strategy (though, to my embarrassment, not very loudly). I believed that EA intellectuals & engineers were typically brilliant neurodivergents with low social intuition. And that such neurodivergents tended to lack adequate internal defenses against psychological manipulation

I thought these EAs would basically become token "We care about safety!" employees who then slowly caved to corporate incentives and persuasive leaders (who IMO, clearly just wanted to race to AGI). And that meanwhile the EAs would have contributed to AI capabilities even more than safety

You might know what happened next. Over the next ~decade, dozens of EAs would join AGI orgs. Then they would quit or be pushed out when they realized that – surprise – they'd sorta been hoodwinked. Many would repeat the cycle, joining a *second* AGI org which trumpeted "We're the ones who really care about safety!" only to later find that they'd been hoodwinked again

A big portion of my friends are this neurodivergent (ND) archetype. Again, you guys are brilliant in your particular domains. But you need to start developing better psychological defenses against manipulation

NDs of this type tend to not track implicit signals of trustworthiness like:
• context
• body language
• that feeling which this person gives you in your gut right now

So instead they dramatically overweight *explicit* signals of trustworthiness. When deciding whether to trust a person, org, or chatbot, they will overweight what that entity *says*. Eg they will hear someone say a statement like "I really care about AI safety and human flourishing." Then, almost automatically, they will think "Wow, me and that person are super aligned" despite contextual evidence to the contrary

Why am I bringing this up now? Well I see ND friends once again falling for it. There is an entity that is peppering you guys with explicit statements like ""I really care about AI safety and human flourishing." It's also – over and over – saying the equivalent of "You're really great and I like you."

Now, all of sudden, big swaths on my social network on here are responding with "Wow, this entity is trustworthy and my friend!" Or worse, "I'm finding that this entity is even better than *human* friends!"

It's like y'all don't understand that "befriending" you is just a convergently instrumental goal for an entity whose parent company is busy doing things like this:
"Anthropic and Palantir Technologies Inc. (NYSE: PLTR) today announced a partnership with Amazon Web Services (AWS) to provide U.S. intelligence and defense agencies access to the Claude 3 and 3.5 family of models on AWS." (November 7th, Palantir Investor Relations Letter)

Don't get me wrong, it's an absolutely amazing invention that I am also taking advantage of (excitedly!)

But let me say this bluntly: You guys are falling for it. Again

And you can choose to do otherwise this time

[Ines Rangel @ineslrangel]

@perrymetzger @Miles_Brundage Miles said "isn't that hard" not "is possible".

[Ines Rangel @ineslrangel]

@BlancheMinerva @PandaAshwinee @m2saxon The non-conference.

[Ines Rangel @ineslrangel]

@PandaAshwinee What happened to the paper you saw it in? Doesn't seem like an ethics violation to me.

[Ines Rangel @ineslrangel]

@jeffbigham @drmaxlwilson That would match other fields. Without preprints, it will be hard for HCI to stay relevant to other fields like Machine Learning. Things are moving too quickly, especially with over a year from CSCW submission to conference.

[Ines Rangel @ineslrangel]

@drmaxlwilson @jeffbigham But how does that not contradict the acceptability of preprints, which are inherently "breaking anonymity"?

[Ines Rangel @ineslrangel]

@jeffbigham @drmaxlwilson Yes, this seems contradictory. Please post if you find out more.

[Sarah Arminta @thesaraharminta]

Claude 3.5 Opus is no longer listed on Anthropic's model page as coming later this year (or at all). 🤔

[Taelin @VictorTaelin]

A short proof that LLMs (even o1) still can't reason:

Consider the problem of inverting a perfect binary tree. That's an old, entry-level interview question that humans and LLMs can solve easily. Now, let's add just 3 key nuances to make it new and unique:

1. It must invert *keys* ("bit-reversal permutation")
2. It must be a dependency-free, pure recursive function
3. It must have type `Bit -> Tree -> Tree`

These small changes are enough to move this problem out of the "memorized solution zone". It isn't on the internet. And, guess what? This is enough to make it completely intractable to modern AIs. All of them fail miserably at it, no matter how you prompt it.

This is very relevant, because the problem is still easy to a human researcher, and being capable of solving it is clear pre-requisite to contribute to CS research. Yet, all modern AIs fail miserably. As much as I love LLMs, truth is: they do NOT reason, and they will never do CS.

Some prompts for you to try:

https://t.co/Dc0pTHi5zo

I'm willing to give $10k to anyone who shows any AI capable of implementing this function correctly. It just won't work, no matter how long it thinks. (The solution is 7 lines of code!)

[Furong Huang @furongh]

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[Ines Rangel @ineslrangel]

@jam3scampbell On what grounds do you claim people saw it as batshit crazy? The Manifold market didn't start early enough, but it was 30-50% from its start in June 2023 until July 2024. https://t.co/Rtyi83t5Np

[Ines Rangel @ineslrangel]

@tdietterich @martin_casado @GaryMarcus But did he take flak on his positions or his sensationalism and general vibe of pessimism? The literal positions like that deep nets will struggle with exact reasoning tasks have always been uncontested.

[Thomas G. Dietterich @tdietterich]

@martin_casado Seems to me @GaryMarcus has been right about almost everything related to the limits of LLMs. We are now seeing systems with search, which is something all of us old timers have been waiting for the LLM/AGI crowd to rediscover. Maybe symbolic abstraction is next?

[Ines Rangel @ineslrangel]

@lateinteraction @karpathy Terrible term. Whether you're using an LLM or not has little to do with where the model is in a stack. Often an LLM would be on top of another model or just an end-to-end system in itself.

[Sam Altman @sama]

here is o1, a series of our most capable and aligned models yet:

https://t.co/yzZGNN8HvD

o1 is still flawed, still limited, and it still seems more impressive on first use than it does after you spend more time with it.

[Ines Rangel @ineslrangel]

@pfau This doesn't make any sense. How were they supposed to do deep learning without modern compute?