Tobias H
2025 Q1 Pivotal Research Fellowship (Technical & Policy)
For sure, but that leads to much more individualised advice of the form “If you’re fine to be exposed to sun for up to 2h with SPF 50, you should not expose yourself for much more than 1h with SPF 30”. The quoted section makes it seem like “You’re fine as long as you wear SPF 50+ sunscreen, but SPF 45 just won’t cut it.”, which doesn’t generalise for most individuals and their level of sunlight exposure.
The linked sunscreen is SPF 45, which is not suitable if you’re using tretinoin.
Unlikely to be advice that can be generalised.
SPF is a measure of the reduction of UVB reaching your skin
SPF 30 means 96.7% protection
SPF 45 means 97.8% protection
SPF 50 means 98% protection
SPF 80 means 98.75% protection
There isn’t much difference between SPF 45 and SPF 50+.
Tretinoin increases sensitivity to UV light, but the biggest factor is still the underlying sensitivity of individual skin. For some people SPF 30 may be more than enough, for others, SPF 50+ may not be enough for prolonged sun exposure.
Still important to make sure that you’re using broad-spectrum (UVA + UVB) sunscreen, and that you apply it correctly.
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I recently found a 2-hour interview with Mo Gawdat titled “EMERGENCY EPISODE: Ex-Google Officer Finally Speaks Out On The Dangers Of AI!” from 2 months ago. It has 6.5 million views which is 1 million more views than Sam Altman’s interview on Lex Fridman.
I’ve only skimmed through it, but it seems that Gawdat frames AI developments as an emergency and is mainly concerned about potential misuse.
I likely won’t have time to actually listen to it for a while – but it seems pretty relevant for the AI Safety community to understand what kind of other extremely popular media narratives about dangers from AI exist.
I think the overall point you’re making is intriguing, and I could see how it might alter my home behaviour if I considered it more deeply. But I also strongly disagree with the following:
Just about every work behavior is an example of bad home behavior
There is a bunch of “work behavior” that has been very useful – in the right measure – for my personal life:
Task Management – This cut down on the time I spend on “life admin”.
Scheduling – Reaching out with “let’s find an evening to play tennis” helps me increase the number of fulfilling activities I do with friends.
Prioritization – Day-to-day life can obscure what’s really important. Thinking about what I really value and want to achieve can make my life more meaningful.
Creating Spreadsheets & Documents – Apart from the obvious use case in personal finance, Spreadsheets are also very valuable to me for evaluating crucial life decisions (“Where should we move?”). I use documents for private events I’m organising (e.g. a weekend trip to the mountains with friends).
Maybe some of them are too obvious and common. But they are things that my grandmother wouldn’t have done – and I suspect that they are mostly derived from work culture.
DC Rainmaker does incredibly detailed reviews of sports watches.
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I was thinking of money. :)
Interesting. Can you give us a sense of how much those asks (offer to pay for the extra labour) end up costing you?
Also: The last name is “Von Almen” not “Almen”
I always assumed that “Why don’t we give Terence Tao a million dollars to work on AGI alignment?” was using Tao to refer to a class of people. Your comment implies that it would be especially valuable for Tao specifically to work on it.
Why should we believe that Tao would be especially likely to be able to make progress on AGI alignment (e.g. compared to other recent fields medal winners like Peter Scholze)?
Just saw the inverse question was already asked and answered.
[I think this is more anthropomorphizing ramble than concise arguments. Feel free to ignore :) ]
I get the impression that in this example the AGI would not actually be satisficing. It is no longer maximizing a goal but still optimizing for this rule.
For a satisficing AGI, I’d imagine something vague like “Get many paperclips” resulting in the AGI trying to get paperclips but at some point (an inflection point of diminishing marginal returns? some point where it becomes very uncertain about what the next action should be?) doing something else.
Or for rules like “get 100 paperclips, not more” the AGI might only directionally or opportunistically adhere. Within the rule, this might look like “I wanted to get 100 paperclips, but 98 paperclips are still better than 90, let’s move on” or “Oops, I accidentally got 101 paperclips. Too bad, let’s move on”.In your example of the AGI taking lots of precautions, the satisficing AGI would not do this because it could be spending its time doing something else.
I suspect there are major flaws with it, but an intuition I have goes something like this:
Humans have in some sense similar decision-making capabilities to early AGI.
The world is incredibly complex and humans are nowhere near understanding and predicting most of it. Early AGI will likely have similar limitations.
Humans are mostly not optimizing their actions, mainly because of limited resources, multiple goals, and because of a ton of uncertainty about the future.
So early AGI might also end up not-optimizing its actions most of the time.
Suppose we assume that the complexity of the world will continue to be sufficiently big such that the AGI will continue to fail to completely understand and predict the world. In that case, the advanced AGI will continue to not-optimize to some extent.
But it might look like near-complete optimization to us.
Would an AGI that only tries to satisfice a solution/goal be safer?
Do we have reason to believe that we can/can’t get an AGI to be a satisficer?
There has been quite a lot of discussion over on the EA Forum:
https://forum.effectivealtruism.org/search?terms=phil%20torres
Avital Balwit linked to this lesswrong post in the comments of her own response to his longtermism critique (because Phil Torres is currently banned from the forum, afaik):
https://forum.effectivealtruism.org/posts/kageSSDLSMpuwkPKK/response-to-recent-criticisms-of-longtermism-1#6ZzPqhcBAELDiAJhw
The whole thing was much more banal than what you’re imagining. It was an interim-use building with mainly student residents. There was no coordination between residents that I knew of.
The garden wasn’t trashed before the letter. It was just a table and a couple of chairs, that didn’t fit the house rules. If the city had just said “please, take the table out of the garden”, I’d have given a 70% chance of it working. If the city had not said a thing, there would not have been (a lot of) additional furniture in the garden.
By issuing the threat, the city introduced an incentive they didn’t intend.
Some residents who picked up on the incentive destroyed the garden because they were overconfident in the authority following through with the threat – no matter what.
(Not sure if I got the maths right here.)
Manifold gives two interesting probabilities:
65% chance of ASI before 2031
28% chance that US life expectancy will reach 100+ in 2050.
Using the simplifying assumption that until 2050 dramatic longevity gains happen only if ASI ‘solves ageing’, we have:
P(solve aging∣ASI)=P(life expectancy≥100)P(ASI)=0.280.65≈43%
I couldn’t find a good number, but let’s assume Manifold also thinks there’s a 25% chance of doom (everyone is dead) until 2050 given ASI. This leaves:
P(ASI, no doom, no large increase in life expectancy∣ASI)=1−0.43−0.25≈32%
Multiplying by the overall chance of ASI (65%), the simplified unconditional outcomes are:
ASI with large longevity gains by 2050: 0.65×0.43≈28%
ASI with doom by 2050: 0.65×0.25≈16%
ASI but no large increase in life expectancy by 2050: 0.65×0.32≈21%
No ASI by 2031: 1−0.65=35%
This would imply that Manifold believes there to be a 32% chance that ASI by 2031, but by 2050 (19 years later), humanity survives but US life expectancy still hasn’t reached 100+ years.