I’m building tools to make sense of the future at Sage. Currently building AI Digest, Fatebook and Quantified Intuitions.
Previously I was doing a PhD in HCI at St Andrews, and worked at Clearer Thinking.
Website: https://binksmith.com
Tweeting, sometimes about EA: https://twitter.com/adambinksmith
Really great presentation on the tool, I was impressed when I stumbled across this a few weeks ago!
Great thanks!
We have two outputs in mind with this project:
1. Reports on a specific thinker (e.g. Gwern) or body of work’s predictions. These would probably be published individually or showing interesting comparisons, similar to the Futurists track record in Cold Takes (based on Arb’s Big Three research)
2. A dashboard ranking the track records of lots of thinkers
For (2), I agree that cherry picking would be bad, and we’d want it to cover a good range.
For our initial outputs from (1) though, I’m excited about specifically picking thinkers who people would find it especially useful to understand their track record (or to have a good-quality assessment of it that they can cite). Curious if you have thoughts of specific people who fit the bill for you?
Very interesting!
I’d be interested to hear a bit more about what a restrained system would be able to do.
For example, could I make two restrained AGIs, one which has the goal:
A) “create a detailed plan plan.txt for maximising profit”
And another which has the goal:
B) “execute the plan written in plan.txt”?
If not, I’m not clear on why “make a cure for cancer” is scope-insensitive but “write a detailed plan for [maximising goal]” is scope-sensitive
Some more test case goals to probe the definition:
C) “make a maximal success rate cure for cancer”
D) “write a detailed plan for generating exactly $10^100 USD profit for my company”
a tool to create a dashboard of publicly available forecasts on different platforms
You might be interested in Metaforecast (you can create custom dashboards).
Also loosely related—on AI Digest we have a timeline of AI forecasts pulling from Metaculus and Manifold.
AI for epistemics/forecasting is something we’re considering working on at Sage—we’re hiring technical members of staff. I’d be interested to chat to other people thinking about this.
Depending on the results of our experiments, we might integrate this into our forecasting platform Fatebook, or build something new, or decide not to focus on this.
[Do you have a work trial? This will be a deal breaker for many]
Based on your conversations with developers, do you have a rough guess at what % this is a deal breaker for?
I’m curious if this is typically specific to an in-person work trial, vs how much deal-breaking would be avoided by a remote trial, e.g. 3 days Sat-Mon.
Thanks for the newsletter!
Looks like a typo:
> a version of GPT-4 released in 2023 outperformed a version of GPT-4 released in 2021
As well as Fatebook for Slack, at Sage we’ve made other infrastructure aimed at EAs (amongst others!):
Fatebook: the fastest way to make and track predictions
Fatebook for Chrome: Instantly make and embed predictions, in Google Docs and anywhere else on the web
Quantified Intuitions: Practice assigning credences to outcomes with a quick feedback loop
This month’s Estimation Game is about effective altruism! You can play here: quantifiedintuitions.org/estimation-game/december
Ten Fermi estimation questions to help you train your estimation skills. Play solo, or with a team—e.g. with friends, coworkers, or your EA group (see info for organisers).
It’s also worth checking the archive for other estimation games you might be interested in, e.g. we’ve ran games on AI, animal welfare + alt proteins, nuclear risk, and big picture history.
I’m curious about B12 supplements—I currently take a multivitamin which has 50µg B12, my partner takes a multivitamin with 10µg B12. Should we be taking additional B12 tablets on top of this? (We’re both vegan)
I saw in that post a recommendation for 100µg tablets, but google says the RDA is 2.4µg, do you know why there’s this gap?
Here’s the link to apply! https://80000hours.org/speak-with-us/
I think some subreddits do a good job of moderating to create a culture which is different from the default reddit culture, e.g. /r/askhistorians. See this post for an example, where there are a bunch of comments deleted, including one answer which didn’t cite enough sources. Maybe this is what you have in mind when you refer to “moderating with an iron fist” though, which you mention might be destructive!
Seems like the challenge with reddit moderation is that users are travelling between subreddits all the time, and most have low quality/effort discussion norms. Whereas on the Forum, the userbase is more siloed, which I guess would make good quality moderation easier.
We’ve added a new deck of questions to the calibration training app—The World, then and now.
What was the world like 200 years ago, and how has it changed? Featuring charts from Our World in Data.
Thanks to Johanna Einsiedler and Jakob Graabak for helping build this deck!
We’ve also split the existing questions into decks, so you can focus on the topics you’re most interested in:
Ah thank you! I’ve just pushed what should be a fix for this (hard to fully test as I’m in the UK).
The July Estimation Game is now live: a 10 question Fermi estimation game all about big picture history! https://quantifiedintuitions.org/estimation-game/july
Question 1:
I was also wondering this—did 80k link to it in their newsletter (which has a big audience)?
Relatedly, I wonder if you can see differences in reported source by the place the survey respondent navigated to the survey from?
Thank you!
Do you look at non-anonymized user data in your analytics and tracking?
No—we don’t look at non-anonymised user data in our analytics. We use Google Analytics events, so we can see e.g. a graph of how many forecasts are made each day, and this tracks the ID of each user so we can see e.g. how many users made forecasts each day (to disambiguate a small number of power-users from lots of light users). IDs are random strings of text that might look like cwudksndspdkwj. I think you’d call technically this “pseudo-anonymised” because user IDs are stored, not sure!
Who specifically gets access to user submitted predictions (can’t quite tell how large your team is, for instance)
Your predictions are private to you unless you share them. I and the other two devs who have helped out with parts of the project have access to the production database, but we commit to not looking at users’ questions unless you specifically share them with us (e.g. to help us debug something). I am interested in encrypting the questions in the database so that we’re unable to theoretically access them, but haven’t got round to implementing this yet (I want to focus on some bigger user-visible improvements first!)
Hope this makes sense! Thanks for your kind words and for checking about this, let me know if you think we could improve on any of this!
Maybe advising other orgs would be a good fit for this? E.g. advising startups in your area