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Dima Damen

@dimadamen

Professor of Computer Vision, @bristolcs. Senior Staff Research Scientist @GoogleDeepMind - passionate about the temporal stream in our lives.
Bristol, UK dimadamen.github.io Joined April 2013
783 Following 12K Followers 4.1K Posts

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Dima Damen @dimadamen
It is the *best* time to start your own research group in AI @bristolcs
Why?
🌟 Bristol hosts the largest supercomputer in the UK - Isambard AI, 4th greenest in the world.
🧑‍🎓 New undergrad degree CS w AI &multiple masters
6⃣Nov DL to apply for position, Link in 🧵
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Dima Damen @dimadamen
Let’s stop the crying wolf rhetoric in AI….
Thanks @philiptorr for the clear write up,
philip Verified account @philiptorr Oct 5
I care a lot about AI safety

But I do find the constant “AI will kill us all by the end of the decade” commentary increasingly unhelpful, and, frankly, a little tiresome.

Sometimes I feel certain people in Silicon Valley have lost touch with reality and normal people.

There are so many other pressing problems. A relatively small, wealthy, technologically immersed community in the Bay Area can spend an extraordinary amount of cognitive bandwidth on scenarios that feel overwhelmingly important from inside that community, while a normal person is worrying about housing, healthcare, war (especially with all the new wars that seem to have started **by humans** recently), crime, their children, energy prices, employment, climate, poverty, or simply getting through the week.

In fact, I think the more extreme rhetoric can be actively counterproductive. It collapses a very broad field: robustness, misuse, autonomy, cyber/bio risk, deception, control, systemic risk, military applications, concentration of power into one spectacular endpoint. And because the endpoint is so extreme and so uncertain, it encourages people either to become quasi-religiously preoccupied with it or to dismiss AI safety altogether.

And there is an important technical distinction between:

“The tail risk is serious enough that we should invest heavily in understanding and reducing it”

and

“The median outcome is human extinction within a few years.”

The first proposition can be justified even when the second is very poorly supported. Nuclear safety is an obvious analogy: you don't need to believe nuclear war is virtually certain next Tuesday to think command-and-control, escalation, verification and weapons safety deserve enormous attention.

I also think a mature AI-safety programme should deliberately cover several timescales. Immediate harms and misuse matter because they are happening now. Emerging agentic risks matter because systems are becoming more autonomous. And genuinely catastrophic or existential risks matter because even a relatively small probability multiplied by an enormous consequence warrants serious research. Those positions aren't in competition.

There is a further strategic problem with constant doom rhetoric: it makes calibration almost impossible. If every capability advance is “the last warning”, every model is “terrifying”, and every year is supposedly the crucial year before catastrophe, observers eventually discount the signal. Safety researchers ought to be unusually disciplined about uncertainty, evidence, falsifiability and updating—not less disciplined because the stakes are high.

(no AI was harmed in the making of this post)
repost if you agree to restore some sanity to the debate
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