Linkpost—Beyond Hyperanthropomorphism: Or, why fears of AI are not even wrong, and how to make them real

Link post

This post deserves deep reflection and response from those that believe that AGI needs tons of money to spend on alignment problems. I sadly suspect that that won’t really happen in the EA or LW communities.

One of the things that makes me an outlier in today’s technology scene is that I cannot even begin to understand or empathize with mindsets capable of being scared of AI and robots in a special way. I sincerely believe their fears are strictly nonsensical in a philosophical sense, in the same sense that I consider fear of ghosts or going to hell in an “afterlife” to be strictly nonsensical. Since I often state this position (and not always politely, I’m afraid) and walk away from many AI conversations, I decided to document at least a skeleton version of my argument. One that grants the AI-fear view the most generous and substantial interpretation I can manage.

Let me state upfront that I share in normal sorts of fears about AI-based technologies that apply to all kinds of technologies. Bridges can collapse, nuclear weapons can end the world, and chemical pollution can destabilize ecosystems. In that category of fears, we can include: killer robots and drones can kill more efficiently than guns and Hellfire missiles, disembodied AIs might misdiagnose X-rays, over-the-air autopilot updates might brick entire fleets of Teslas causing big pile-ups, and trading algorithms might cause billions in losses through poorly judged trades. Criticisms of the effects of existing social media platforms that rely on AI algorithms fall within these boundaries as well.

These are normal engineering risks that are addressable through normal sorts of engineering risk-management. Hard problems but not categorically novel.

I am talking about “special” fears of AI and robots. In particular, ones that arise from our tendency to indulge in what I will call hyperanthropomorphic projection, which I define as attributing to AI technologies “super” versions of traits that we perceive in ourselves in poorly theorized, often ill-posed ways. These include:

“Sentience”

“Consciousness”

“Intentionality”

“Self-awareness”

“General intelligence”

I will call the terms in this list pseudo-traits. I’m calling them that, and putting scare quotes around all of them, because I think they are all, without exception, examples of what the philosopher Gilbert Ryle referred to as “philosophical nonsense.” It’s not that they don’t point to (or at least gesture at) real phenomenology, but that they do so in a way that is so ill-posed and not-even-wrong that anything you might say about that phenomenology using those terms is essentially nonsensical. But this can be hard to see because sentences and arguments written using these terms can be read coherently. Linguistic intelligibility does not imply meaningfulness (sentences like “colorless green ideas sleeping furiously” or “water is triangular” proposed by Chomsky/​Pinker are examples of intelligible philosophical nonsense).

To think about AI, I myself use a super-pseudo-trait mental model, which I described briefly in Superhistory, not Superintelligence. But my mental model rests on a non-anthropomorphic pseudo-trait: time, and doesn’t lead to any categorically unusual fears or call for categorically novel engineering risk-management behaviors. I will grant that my model might also be philosophical nonsense, but if so, it is a different variety of it, with its nonsensical aspects rooted in our poor understanding of time.

Read the entire thing.