I'm the Founder and Co-director of The Unjournal; We organize and fund public journal-independent feedback, rating, and evaluation of hosted papers and dynamically-presented research projects. We will focus on work that is highly relevant to global priorities (especially in economics, social science, and impact evaluation). We will encourage better research by making it easier for researchers to get feedback and credible ratings on their work.
Previously I was a Senior Economist at Rethink Priorities, and before that n Economics lecturer/professor for 15 years.
I'm working to impact EA fundraising and marketing; see https://bit.ly/eamtt
And projects bridging EA, academia, and open science.. see bit.ly/eaprojects
My previous and ongoing research focuses on determinants and motivators of charitable giving (propensity, amounts, and 'to which cause?'), and drivers of/barriers to effective giving, as well as the impact of pro-social behavior and social preferences on market contexts.
Podcasts: "Found in the Struce" https://anchor.fm/david-reinstein
and the EA Forum podcast: https://anchor.fm/ea-forum-podcast (co-founder, regular reader)
Twitter: @givingtools
Quick follow-up: I've worked with Claude Code (several iterations; wanted Fable, got blocked so pushed to Opus) to put up this page comparing and bridging Pablo's model to ours...
This is early -- I continue vetting and working on it and would love your feedback
There's a potential complementarity: we focus on is the cost distribution, Pablo on the demand response is Pablo's
(If you add hypothes.is comments there I'll respond and adapt.)
Thanks for this! We've been doing some related work through The Unjournal Pivotal questions -- see this modeling interface/calculator. I'm reading through your modeling and discussion carefully now, aiming to do some comparisons between our approaches, and it might be worth some conversation/collaboration (feel free to DM).
Also see the resources and evidence coming out of our recent workshop, which we're following up on, aiming to get a wider range of views and a productive crux-mappiung conversation between 'skeptics and optimists'. We plan to share further synthesis of stated beliefs as it comes together.
(Also see the how it works explainer and the TEA comparisons. Much/most of these were AI generated with repeated feedback, and may benefit from further human scrutiny.
I sometimes felt you were implying "no evidence" when I thought something closer to "very weak evidence" would be more appropriate.
Can you provide some specific examples, and I'll reconsider
However, in practice, I would agree the focus should overwhelmingly be on decreasing the uncertainty about the extent to which AI models have welfare, and how to measure it.
I'm not sure if we 'agree' here, or at least that's not the point I was making. I was accepting that AI models (either the information flow itself, or the physical electron flows or something) might indeed "have" or generate consciousness and welfare.
My main doubt was more:
So I'm not sure that we have useful ways to decrease the uncertainty about whether th AI models have welfare, and I'm not sure we really have any ways to measure it. But I guess agree we should try to decrease the uncertainty about 'whether we can now or will ever have ways to measure it' (or 'it's valence') ... which is what my post was sort of trying to do.
Perhaps the strongest argument against this would be "what if the model says it is conscious, it is in pain, the data suggests it is not lying and that it is confident in its statement?" I don't find this convincing. ... Even if the talker has no access to the valenced consciousness, it's model may simply lead it to a confident and wrong answer about this.
Did you mean "If" instead of "Even if"?
What I meant was that even if the AI is making a confident statement that it is in pain, and it is not deliberately lying, it doesn't mean that it actually knows the answer to 'is it (or is anything in it's system) in pain'.
So the 'even if' was setting off a contrast between 'not having a access to the answer' and 'making a confident statement'.
Thanks. I've read much of that "bullshit" paper and I think there's some interesting overlap. Some ways I think it relates:
Their "lack of external validation of AI welfare" problem seems at the root of the problem I name that "the signals we get from the AI may not tells us anything directional about the valence of the part of the AI that has consciousness" (if it does). If there is no ground truth (opportunity for 'falsification') here I don't see how we can credibly make that link.
The evidence they cite about the sensitivity of the measures signals of valence to seemingly irrelevant engineering choices reinforces my doubts.
In case helpful, I've been vibe coding a calculator and model og this potential influx here, with input from @MichaelDickens and others
Project Idea: 'Cost to save a life' interactive calculator promotion
What about making and promoting a ‘how much does it cost to save a life’ quiz and calculator.
This could be adjustable/customizable (in my country, around the world, of an infant/child/adult, counting ‘value added life years’ etc.) … and trying to make it go viral (or at least bacterial) as in the ‘how rich am I’ calculator?
The case
While GiveWell has a page with a lot of tech details, but it’s not compelling or interactive in the way I suggest above, and I doubt they market it heavily.
GWWC probably doesn't have the design/engineering time for this (not to mention refining this for accuracy and communication). But if someone else (UX design, research support, IT) could do the legwork I think they might be very happy to host it.
It could also mesh well with academic-linked research so I may have some ‘Meta academic support ads’ funds that could work with this.
Tags/backlinks (~testing out this new feature)
@GiveWell @Giving What We Can
Projects I'd like to see
EA Projects I'd Like to See
Idea: Curated database of quick-win tangible, attributable projects