Matteo Giangrande

docente Storia e Filosofia @miursocial

[Matteo Giangrande @librazione_]

i) Stop trying to know-it-all.
ii) Don't worry about what others are thinking.
iii) Don't think about what you want to be, but what you want to do.
iv) Have a sense of humor and talk honestly.

[Matteo Giangrande @librazione_]

Alle domande kantiane aggiungiamo: cosa non posso delegare?

[Matteo Giangrande @librazione_]

marketing o filantropia?

[Dario Amodei @DarioAmodei]

Today I'm publishing a new essay, Policy on the AI Exponential. AI is progressing extremely fast—much faster than the policy process was built to handle. The essay lays out where I think the technology is now, and the action needed to close the gap: https://t.co/Lh6PWae178

[Valerio Capraro @ValerioCapraro]

Students without access to LLMs are 2 to 8 times more creative than students with access.

That is the finding of a new paper comparing 2,200 college admissions essays written by humans before ChatGPT with essays generated by GPT-4.

The key point is not individual creativity. GPT-4 can write well, sometimes better than individual students. The problem is collective creativity.

Each new human essay added new semantic territory. New ideas. New angles. New experiences. New combinations.

Each new GPT-4 essay added much less.

The authors call this the diversity growth rate: how much novelty each additional text contributes to the collective pool of ideas.

Humans kept expanding the pool. GPT-4 made the pool converge.

Even when the authors pushed GPT-4 to be more creative, changed parameters, or used chain-of-thought prompting, the homogenizing effect remained.

This is the real danger of AI in education.
Not that students will write worse.
That everyone will write the same.

*
Full paper in the first reply

[Matteo Giangrande @librazione_]

@guidotweet Framework che giustifica l'idea secondo cui "microaggressioni" contro gruppi “oppressori” (o percepiti tali) hanno peso morale diverso rispetto a quelle contro gruppi oppressi.

[Matteo Giangrande @librazione_]

@guidotweet Non è narcolessia selettiva, ma coerente, sebbene miope, applicazione agli ebrei del framework gerarchico oppressor/oppressed, da combattere con universalismo anti- tribale.

[Daniel Litt @littmath]

My general view has always been that it's not worth rushing to be the first to do work that someone else could do next week; clearly the marginal impact of such work is low. Worth thinking about this in the rush to publish results where the intellectual labor was done by AI.

[Matteo Giangrande @librazione_]

@EBoffano @guidotweet Rozzamente ad hominem e tu quoque, per avvelenare il pozzo.

[Matteo Giangrande @librazione_]

@StefanoPutinati 👌

[Matteo Giangrande @librazione_]

@alfo_lanzieri Perfettamente d'accordo.

[Adrienne LaFrance @AdrienneLaF]

You really have to read Ted Chiang on consciousness and AI—just published in The Atlantic:

https://t.co/z9eRSlkwQ8

[Rob Wiblin @robertwiblin]

Sad to see Ted Chiang resorting to such bad arguments in this piece.

He confidently claims Claude has no inner experience. But he has to use a lot of dodgy philosophy and poor reasoning to get there:

1. We can't take deflationary mechanistic descriptions of how AI calculations are performed to show that AI isn't conscious. Otherwise we could argue that 'humans are just neurones transmitting signals one after another' and thereby conclude humans can't be conscious. But that would be wrong for us. And the same logic could be wrong for LLMs.

2. That LLMs are asked to play characters, and effectively are always playing characters, doesn't mean they aren't conscious. It's true a human playing the role of Caesar doesn't have Caesar's experience of things. But they still experience something (that of being a person pretending to be Caesar).

The same could be true of Claude. (Arguably it's also true that humans are always playing characters to some extent and don't have a completely fixed nature, but that has no bearing on our own subjective experience.)

3. Chiang says "an LLM is a machine that generates only one word at a time". This conflates two things: they output one word at a time, and they only think about one word at a time (without planning ahead or looking back).

The first is true of AI but equally true of humans. While the latter we know is a false description of how AIs think – we can see from how AIs compose poetry that they plan out rhymes a at least one line ahead.

4. He argues that because it's implausible that basic autocomplete on your phone is conscious, it's similarly implausible that Claude is conscious. Using the same logic we could say that if we feel confident a fruit-fly isn't conscious we can be confident a human being can't be either.

A human brain and fruit-fly brain share some information transmission and processing mechanisms in common. But humans do it much more, and do it differently. And those differences may be what makes the difference. Similarly the many types of internal information processing that occur in Claude's weights but not in autocorrect may be exactly the things that get you subjective experience.

5. Chiang confidently claims you need a body to have subjective experience without much argument. He may turn out to be right but the claim is speculative and contested.

6. Chiang leans on the idea that moral reasoning is necessarily subjective/emotional with very little argument, while ignoring competing theories like rationalism. He may be right but moral sentimentalism is a highly contested position that can't simply be assumed.

7. He argues that it would be impossible to convince him that a video of an astronaut around Alpha Centauri was real, because of the surrounding contextual understanding. And similarly no AI output could convince him that Claude is conscious.

But we can dismiss the first video as almost certainly fake because we mechanistically understand space travel and physics well enough to know a human couldn't have gotten there in time for it to be real (unless our model of the world were very wrong, which we think is much less probable than a fake video which would be entirely unsurprising).

But by contrast we don't mechanistically understand how subjective experience arises. So we simply can't make the same highly confident move of interpretation there. (It's actually the archetypal thing in the universe we perhaps understand least well!)

That said, AI outputs barely move my estimate of AI consciousness because they could indeed have been generated by an unconscious process (or not, we just don't know).

8. He argues that "Being open to the possibility that LLMs are conscious is the same as being open to the possibility that Microsoft Word is conscious, or, more precisely, that multiple distinct consciousnesses are dormant in every Word document containing a conversational transcript."

This is misguided because A. Microsoft Word as a program replicates much less of what humans are functionally capable of than Claude so the argument by functional analogy is basically not present there. B. Files of text don't have any computations going on in or as part of them, even when 'open' in a text editor. They are static. So they have even less in common with what appears distinctive about the human brain, which is constant calculation. So the case by mechanistic or functional similarity is weaker still.

Not to mention that neural nets have more in common with the architecture of the human brain than ordinary computer programs, and are grown organically in a way normal software is not.

Common sense says says Claude has more in common with a human brain than Microsoft Word or a text file. Common sense is right. So the prima facie case for Claude being conscious is naturally stronger (even if you think it's still weak in absolute terms).

———

I agree with Chiang that looking at the text outputs of LLMs alone won't be enough to make us confident they are conscious. We will need to look at how they work, figure out more about how humans and other animals work, and ideally solve the hard problem of consciousness (!).

But none of that licenses us to dismiss out of hand the possibility that LLMs do have subjective experience.

[Matteo Giangrande @librazione_]

Quando la pubblica opinione non si limita più a pretendere l’assenso, ma esige una obbligatoria professione di conformità, il silenzio cessa di valere come tacito consenso e diventa forma di resistenza.

[Guido Vitiello @guidotweet]

Operetta morale

https://t.co/pOwwhKVOJg

[Il Foglio @ilfoglio_it]

La ricchezza è più concentrata negli anziani e a beneficiarne saranno i pochi figli

Di Davide Mattone

https://t.co/MCKiQ6M5pO

[Matteo Giangrande @librazione_]

per questo una parte delle nuove generazioni guarda all'AI con diffidenza e timore, percependola non come un'opportunità di accesso al futuro, ma come una minaccia alle possibilità di apprendimento e ingresso nel mondo del lavoro.

[Matteo Giangrande @librazione_]

L'intelligenza artificiale rappresenta una rottura rispetto alle precedenti ondate tecnologiche perché tende a favorire chi possiede già esperienza, competenze e posizione professionale, invece di offrire ai giovani un vantaggio iniziale;

[Gianfrancesco @GianfrancescoG9]

L'AI, una diabolica rivincita dei boomer, ci credo poi che ai giovani viene l'ansia. Da leggere @esterviola su @ilfoglio_it

[Matteo Giangrande @librazione_]

@Setteottobre_ 👏

[Matteo Giangrande @librazione_]

τὰ μεγάλα πάντα ἐπισφαλῆ

[Matteo Giangrande @librazione_]

@MariuzzoAndrea Complimenti

[Mario Ricciardi @marioricciard18]

Un lavoro importante e attuale. Da leggere.

[Cultural Decay @DegCult]

Mentre ancora l’orchestra suona, in questo clima da tardo impero, non ci rendiamo conto che i barbari sono già fra noi, che ogni spazio è colonizzato da incompetenza e vuota retorica, che il distacco dalla realtà è ormai completo, e nel gioco delle parti imperversa l’ennesimo, desolante bluff.