I like the donor compass (https://donorcompass.rethinkpriorities.org/) , but I see a lot of room for improvement - some comments here, and I'll put some others as public comments using the Hypothes.is tool within that page. I hope they're helpful.

Simple mode

1. Simple is too simple? For the simple mode I somewhat felt like you asked too few questions for me to feel I was meaningfully consulted.

I slightly suspect that the basic mode is not as appealing as it could be to the sort of intellectually rigorous people who would be using this tool in the first place.

I don't recall being asked anything about discounting long term future payoffs or population ethics (discounting payoffs resulting from 'creating more people than are alive today/would be alive counterfactually'). OK , you did ask about my discounting people alive 100 years from now, 500 years from now in 'notched' ways. That did seem arbitrary, but fairly easy to understand.

2. Wanted a better mapping from answers to results: The answer at the end gives a breakdown but no explanation of why that was reached as a result of my answers. Which makes me less likely to put faith in it.

3. Questions were hard to interpret and guage:

"How much should animal welfare factor into funding decisions?" This one was decent because I could unfold and the weightings I was giving to animals below it, and make some choices. -- But it would be nice to see an explanation of how the defaults were chosen, perhaps as a tooltip. Also, I was surprised to see the "humans with disability" buried there in a question that was otherwise about humans versus nonhuman animals.

How much priority should reducing existential risk from AI receive over other causes? If AI poses serious existential risks, the benefits of other interventions could be cut short so their value could reduce. Use the slider to apply a discount: 0% means no adjustment, 100% means only AI interventions are valued.

This one baffled me and confused a colleague I went through it with.

i. Intuitively, one might suspect 0% means "I'm not putting any value on mitigating existential risk from AI". That's what you might think if you answer quickly,

ii. But then, if you read it, you'd see that it was about applying some sort of extra prioritization to AI intervention. It's unclear why I would want to do this. The model should already be taking these things into account.

But now there's then a decent way to interpret what 0% and 100% mean here. But I have no way of understanding what 20% or 50% would mean in this context - I don't know what the units are.

A folding space explaining this and allowing you to choose the parameters more precisely here would help.

I want to spend on whatever pays off most on average, even if the chance of success is small and the work may do harm

I want to optimize for impact under the condition that I avoid doing harm or taking bets on very unlikely outcomes

iii. Again, it's very unclear to me what the units are here and how my response here affects the outcomes. In a strictly logical sense, I'd imagine that putting zero would mean that I couldn't really donate to anything, because you can never avoid a possibility of doing any harm. And again, the units here are very unclear to me.

Advanced mode

OK, I can move to 'advanced mode'; if it was something usable, I'd probably want to see that option at the start? I only see that after I've completed the simple one.

However, it doesn't seem particularly usable unless you're already deep in the weeds on this stuff. You basically give access to a raw spreadsheet with some unexplained technical terms and computations ("Lexicographic Maximin" etc). This would benefit, of course, from tooltips, explanations, and folds, or at least a link to a full explainer of how this advanced mode works. At least there should be some sort of signposting here explaining that this is just an experimental version.

Quick take only for now because this is basically a social media post:

Updates on the Animal Futures tournament in progress: https://uj-animal-futures-update.netlify.app/

Some highlights: Solid participation, one cultivated-meat approval question already resolved, and a mixed bag of forecasts for animals.

Some good "news" for advocates: Forecasters give the Save Our Bacon Act 3% and the Canary Islands octopus farm 1%, expect about half of Europe's top 20 grocers to have shrimp welfare commitments, and see in-ovo sexing spreading in the EU (~44% of layers) (but barely in the US ~3%).

Less good, especially for the US: ~80% for at least one more state cultivated-meat ban, 2% for plant-based reaching 10% of US retail by 2031, and low expected fulfillment of 2026 corporate chicken pledges.

But I think predicting the future doesn't help much unless it informs decisions.

Help us: Who should we be sharing this with? What forecast would change a grant, campaign, or policy decision? Decisionmakers: what threshold matters, and what evidence would you need? Add your comments here, on that page, or DM.

And you can still play: https://www.metaculus.com/tournament/33016/

Metaculus Sentient Futures

Help The Unjournal prioritize AI economics and governance research

(https://uj-prioritization-dashboard.netlify.app/ai-governance/)

The Unjournal (https://info.unjournal.org/) is prioritizing research on AI economics, governance, social and economic impacts, and risks from increasingly capable AI. (NB: We're not covering technical/CS/ML/AI-safety research.). We want to commission expert public evaluations and help synthesize, disseminate, and curate this work.

Much of this research seems 1) important/impactful/influential, (2) involves considerable 'firepower' from prominent researchers and practitioners, (3) not 'obviously true', and (4) time-sensitive: relevant for funding, policy, and research-steering now, but not after the "six months to six years" required for the traditional (economics) journal process

Our preliminary shortlist page (https://uj-prioritization-dashboard.netlify.app/ai-governance/) includes paper summaries, AI-generated audio walkthroughs, and an interface for giving feedback. We also invite suggestions fr other research (please check the broader list/interface to avoid duplication).

Especially looking for your input on:

• Usefulness and accuracy:* Is this useful? How could we improve it? What have we got wrong?
• Impact: Which research do you use, or think others use or should use?
• Scrutiny What claims and approaches need careful experts and practitioners critique? What sorts of experts? If you're that expert, please dm and join our pool.
• Participation: Who should be part of this discussion (nominate and nudge)?
• Gaps: What's missing (research, claims, etc.)?

Timing and next steps (our plan)

• Finalize an initial shortlist of at least three research outputs before the end of October, with more depending on interest and funding.
• Commission rapid, public, impact-focused evaluations/reviews by experts and practitioners, aiming for a first public evaluation within about two weeks of commissioning.
• Over the following two to four weeks, invite author and stakeholder responses and follow-ups, and facilitate private and public discussion

If it this works well, we hope to scale up and continue in the following months.

Alongside the evaluations, we want to help people find and use this research, and to help shape its direction. I hope the prioritization itself will be useful to students, researchers, practitioners, and other stakeholders. (NB: the "prioritization" here is mainly about "potential for impact and value for evaluation"; assessing the research credibility is for the evaluation part).

I wanted to share this quickly; planning a fuller post soon. (Feedback on this post itself is helpful too.)

Related: We’re also exploring sponsorship of evaluations/themes/questions (https://uj-prioritization-dashboard.netlify.app/sponsor/). Looking for feedback: Would this be useful, would you sponsor or recommend others to do so? Would sponsorship affect your trust in the evaluations (given the rules and safeguards mentioned in the link)?

And an (AI generated, at my prompting) comparison of the models here https://uj-ai-wealth-philanthropy-steelman.netlify.app/model-comparison/ ... I'll try to dig in more on this soon.

https://uj-ai-wealth-philanthropy-steelman.netlify.app/model-comparison/ comparing this to others' models and work (I'll try to dig in more on that later)

https://uj-ai-wealth-philanthropy-steelman.netlify.app/model-comparison/ comparing these (I'll try to dig in more on that later)

Proposing an improvement to otols like this -- suggestionh bounties w external judgment and/or 'enforcement' -- https://forum.effectivealtruism.org/posts/oxFncTiAaHBJCgBZP/anonymous-suggestion-boxes-with-a-committed-reward-pool-and?sharePopup=true

Also please see the model that I created, forking into a specific fork for development economics. Would be good to compare and potentially collaborate on these soon. Interesting to see what semi-independent modeling exercises come up with, how much they converge and diverge, etc.

https://forum.effectivealtruism.org/posts/RLWpq2oXPsunoqTEW/live-models-and-dashboards-of-anticipated-ai-wealth-going-to

https://uj-ai-wealth-philanthropy-steelman.netlify.app/global-development/

https://uj-ai-wealth-philanthropy-steelman.netlify.app/