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I think you’re getting piled on here way too aggressively. This is literally “nostupidquestions”.

I’m assuming you asked because you’re open to explanations, not to argue. If that’s true, here are some reasons to be very skeptical and careful with AI (especially corporate AI; I’m neutral myself on fully local home AI);

They are privacy nightmares. Everything you say in moments of vulnerability will likely be used to sell you something or against you in the future.
They are not as good as you think they are, which is devious. They will convince you they are “smart” but they are just statistical models. So they will confidently tell you false things and if you trust them, you will believe false things. They can’t do math, they can’t actually “think.” You are just getting a statistical approximation of grammatically plausible language from the training data.
They train you to not think for yourself and rely on them. There is some ambiguity whether there may be complex benefits, but it’s clear how they’re being used now is harmful to learning and development, even used by people who think they’re being careful.
They asymmetrically benefit owners versus workers. Corporate AI is being pushed so hard because owners believe it will further funnel more income to them versus workers, and they benefit from this trade even if it can’t do tasks as well as workers. That means less jobs for the workers and worse experiences for the customers.
Huge environmental costs for all of this.
Data centers take up huge amounts of water from communities.
Data centers increase electrical costs to communities.
Huge increase in consumer hardware prices from corporate AI buying all the graphics cards, CPUs, hard drives, RAM, etc, leading to pricing out many people from home computing or gaming.

Are there benefits? I think there are. But AI has not been allowed to just grow and to be shown useful over time. It’s been shoved down our throats, which, with the above, motivates a lot of legitimate hate.

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dave@feddit.uk ⁨1⁩ ⁨week⁩ ago
Since yours was the first reply I came to that didn’t just ‘react’, I’d like to challenge 1 point in your list (the rest I pretty much agree with), and that is the first one. For context, I worked in AI (or ML as it was known then) in the 1990s. The models were very much based on ideas from neuroscience (my CS PhD supervisor was a biologist). Saying “they can’t think” requires a precise definition of what “thinking” is, and I’ve not seen one so far.

For sure, the most current LLMs are not what we might call human-level sentient, and have only seen a fraction of what a human baby would be exposed to in terms of training data. But as far as the way they process that data, perhaps they are “thinking” in the same way a brain would think if all it ever ‘saw’ was text. Perhaps they think in the same way an insect or small rodent thinks. And as they grow larger / more sophisticated, the same as a dog or cat? Or a small primate? You can see where that’s going.

Anyway, I enjoyed The Infinity Machine by Sebastian Mallaby. My PhD was based on the early work of Yann LeCun, and putting all those names and the motivations behind them into a full picture was eye-opening.

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