The dancing bear, part 1

I don’t believe the greatest societal risk is that a sentient artificial intelligence is going to kill us all. I think our undoing is simpler than that. I think that most of our lives are going to be shorter and more miserable than they could have been, thanks to the unchecked greed that’s fed this rally. (Okay, this and crypto.)

I like this analogy:

AI is like a dancing bear. This was a profitable sideshow dating back to the middle ages: all it takes is a bear, some time, and a complete lack of ethics. Today, our carnival barkers are the AI startups and their CEOs. They’re trying to convince you that if they can show you a bear that can dance, then you’ll believe it can draw, write coherent sentences, and help you with your app’s marketing strategy.

Part of the curiosity of a dancing bear is the implicit risk that it’ll remember at some point that it’s a bear, and maul whoever is nearby. The fear is a selling point. Likewise, some AI vendors have even learned that the product is more compelling if it’s perceived as dangerous. It’s common for AI startup execs to say things like, “of course there’s a real risk that an army of dancing bears will eventually kill us all. Anyway, here’s what we’re working on…” How brave of them.

The dancing bear, part 1

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The Gist: AI, a talking dog for the 21st Century.

My main problem with AI is not that that it creates ugly, immoral, boring slop (which it does). Nor even that it disenfranchises artists and impoverishes workers, (though it does that too).

No, my main problem with AI is that its current pitch to the public is suffused with so much unsubstantiated bullshit, that I cannot banish from my thoughts the sight of a well-dressed man peddling a miraculous talking dog.

Also, trust:

They’ve also managed to muddy the waters of online information gathering to the point that that even if we scrubbed every trace of those hallucinations from the internet – a likely impossible task - the resulting lack of trust could never quite be purged. Imagine, if you will, the release of a car which was not only dangerous and unusable in and of itself, but which made people think twice before ever entering any car again, by any manufacturer, so long as they lived. How certain were you, five years ago, that an odd ingredient in an online recipe was merely an idiosyncratic choice by a quirky, or incompetent, chef, rather than a fatal addition by a robot? How certain are you now?

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What happens to what we’ve already created? - The History of the Web

We wonder often if what is created by AI has any value, and at what cost to artists and creators. These are important considerations. But we need to also wonder what AI is taking from what has already been created.

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What I’ve learned about writing AI apps so far | Seldo.com

LLMs are good at transforming text into less text

Laurie is really onto something with this:

This is the biggest and most fundamental thing about LLMs, and a great rule of thumb for what’s going to be an effective LLM application. Is what you’re doing taking a large amount of text and asking the LLM to convert it into a smaller amount of text? Then it’s probably going to be great at it. If you’re asking it to convert into a roughly equal amount of text it will be so-so. If you’re asking it to create more text than you gave it, forget about it.

Depending how much of the hype around AI you’ve taken on board, the idea that they “take text and turn it into less text” might seem gigantic back-pedal away from previous claims of what AI can do. But taking text and turning it into less text is still an enormous field of endeavour, and a huge market. It’s still very exciting, all the more exciting because it’s got clear boundaries and isn’t hype-driven over-reaching, or dependent on LLMs overnight becoming way better than they currently are.

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AI and Asbestos: the offset and trade-off models for large-scale risks are inherently harmful – Baldur Bjarnason

Every time you had an industry campaign against an asbestos ban, they used the same rhetoric. They focused on the potential benefits – cheaper spare parts for cars, cheaper water purification – and doing so implicitly assumed that deaths and destroyed lives, were a low price to pay.

This is the same strategy that’s being used by those who today talk about finding productive uses for generative models without even so much as gesturing towards mitigating or preventing the societal or environmental harms.

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Declare your AIndependence: block AI bots, scrapers and crawlers with a single click

This is a great move from Cloudflare. I may start using their service.

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