Hauke Hillebrandt

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ARC's GPT-4 evaluation is cited in the FT article, in case that was ambiguous.

Agreed, the initial announcement read like AI safety washing and more political action is needed, hence the call to action to improve this.

But read the taskforce leader’s op-ed

  1. He signed the pause AI petition.
  2. He cites ARC’s GPT-4 evaluation and Lesswrong in his AI report which has a large section on safety.
  3. “[Anthropic] has invested substantially in alignment, with 42 per cent of its team working on that area in 2021. But ultimately it is locked in the same race. For that reason, I would support significant regulation by governments and a practical plan to transform these companies into a Cern-like organisation. We are not powerless to slow down this race. If you work in government, hold hearings and ask AI leaders, under oath, about their timelines for developing God-like AGI. Ask for a complete record of the security issues they have discovered when testing current models. Ask for evidence that they understand how these systems work and their confidence in achieving alignment. Invite independent experts to the hearings to cross-examine these labs. [...] Until now, humans have remained a necessary part of the learning process that characterises progress in AI. At some point, someone will figure out how to cut us out of the loop, creating a God-like AI capable of infinite self-improvement. By then, it may be too late.”

Also the PM just tweeted about AI safety

Generally, this development seems more robustly good and the path to a big policy win for AI safety seems clearer here than past efforts trying to control US AGI firms optimizing for profit. Timing also seems much better as things looks way more ‘on’ now.  And again, even if the EV sign of the taskforce flips, then $125M is .5% of the $21B invested in AGI firms this year.

Are you saying that, as a rule, ~EAs should stay clear of policy for fear of tacit endorsement, which has caused harm and made damage control much harder and we suffer from cluelessness/clumsiness? Yes, ~EA involvement has in the past sometimes been bad, accelerated AI, and people got involved to get power for later leverage or damage control (cf. OpenAI), with uncertain outcomes (though not sure it’s all robustly bad - e.g. some say that RLHF was pretty overdetermined). 

I agree though that ~EA policy pushing for mild accelerationism vs. harmful actors is less robust (cf. the CHIPs Act, which I heard a wonk call the most aggressive US foreign policy in 20 years), so would love to hear your more fleshed out push back on this - I remember reading somewhere recently that you’ve also had a major rethink recently vis-a-vis unintended consequences from EA work?

Ian Hogarth is leading the task force who's on record saying that AGI could lead to “obsolescence or destruction of the human race” if there’s no regulation on the technology’s progress. 

Matt Clifford is also advising the task force - on record having said the same thing and knows a lot about AI safety. He had Jess Whittlestone & Jack Clark on his podcast. 

If mainstream AI safety is useful and doesn't increase capabilities, then the taskforce and the $125M seem valuable.

If it improves capabilities, then it's a drop in the bucket in terms of overall investment going into AI.

a large part of those 'leaks' are fake

 

Can you give concrete examples?

[Years of life lost due to C19]

A recent meta-analysis looks at C-19-related mortality by age groups in Europe and finds the following age distribution:

< 40: 0.1%

40-69: 12.8%

≥ 70: 84.8%

In this spreadsheet model I combine this data with Metaculus predictions to get at the years of life lost (YLLs) due to C19.

I find C19 might cause 6m - 87m YYLs (highly dependending on # of deaths). For comparison, substance abuse causes 13m, diarrhea causes 85m YLLs.

Countries often spend 1-3x GDP per capita to avert a DALY, and so the world might want to spend $2-8trn to avert C19 YYLs (could also be a rough proxy for the cost of C19).

One of the many simplifying assumptions of this model is that excludes disability caused by C19 - which might be severe.

Very good analysis.

I also thought your recent blog was excellent and think you should make it a top level post:

https://entersingularity.wordpress.com/2020/03/23/covid-19-vs-influenza/

Cruise Ship passenger are a non random sample with perhaps higher co-morbidities.

The cruise ships analysed are non-random sample: "at least 25 other cruise ships have confirmed COVID-19 cases"

Being on a cruise ship might increase your risk because of dose response https://twitter.com/robinhanson/status/1242655704663691264

Onboard IFR. as 1.2% (0.38-2.7%) https://www.medrxiv.org/content/10.1101/2020.03.05.20031773v2

Ioannidis: “A whole country is not a ship.”

Thanks Pablo for your comment and helping to clarify this point. I'm sorry if I was being unclear.

I understand what you're saying. However:

  • I realize that the Oxford study did not collect any new empirical data that in itself should cause us to update our views.
  • The authors make the assumption that the IFR is low and the virus is widespread and find that it fits the present data just as well as high IFR and low spread. But it does not mean that the model is merely theoretical: the authors do fit the data on the current epidemic.
  • This is not different from what the Imperial study does: the Imperial authors do not know the true IFR but just assuming a high one and see whether it fits the present data well.
  • But indeed, on a meta-level the Oxford study (not the modelling itself) is evidence in favor of low IFR. When experts believe something to be plausible then this too is evidence of a theory to be more likely to be true and we should update. An infinite number of models can explain any dataset and the authors only find these two plausible.
  • By coming out and suggesting that this is a plausible theory, especially by going to the media, the authors have gotten a lot of flag for this ("Irresponsible" - see twitter etc.). So they have indeed put their reputation on the line. This is despite the fact that the authors are prudent and saying that high IFR is also plausible and also fits the data.
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