TL;DR
NOVAH (No Violence At Home) was incubated by Charity Entrepreneurship (now Ambitious Impact) in 2024 to test a promising idea: preventing intimate partner violence through edutainment, in our case a serialised radio drama. Over the past two years we have produced and aired two seasons in Rwanda.
We are currently evaluating our second season through a randomized controlled trial with 2,400 couples in Rwanda in partnership wi...
TL;DR
* The Long-Term Future Fund is closing down, and EA Funds is launching the Transformative AI Fund with a new full-time team.
* The fund's primary focus is technical AI safety and AI governance (including post-AGI governance), as well as supporting fields such as field-building and forecasting. We'll also consider non-GCR implications of transformative AI such as flourishing futures and digital...
The current Long Term Future Fund (LTFF) fund managers and I have decided to step back from our work on the LTFF. Because we believe LTFF donors trusted the fund managers to ensure that the funds would be used in line with the purposes of their donation, we've decided the right move is to close the fund.
While LTFF is closing, note that EA Funds has launched a new fund...
In Debiasing Decisions: Improved Decision Making With A Single Training Intervention they found that a 30-minute video reduced confirmation bias, fundamental attribution error, and bias blind spot, by 19%.
The video is super cheesy, and that makes me suspicious.
It should be noted that playing a 60-minute "debiasing" game debiased people more than the video.
The rest of this short form is random thoughts about debiasing.
I tried finding tests for these biases so that I can do it myself, but I didn't find any. This made me worry that we don't have standardized tests for biases, which strikes me as bad. Although I didn't spend too much time looking into it. (More on this here)
I don't think training people to reduce 3 biases a time is a good way to go, since we have 100s of biases. If we use a taxonomy of biases like Arkes (1991) (strategy-based, association-based, and psychophysical errors). maybe we could have three interventions for each type of bias? But it's not clear how you would teach people to avoid say association-based biases by lecturing about it.
You could nudge them in small ways. From Arkes (1991)
In Sedlmeier & Gigerenzer they taught people Bayes by using frequencies rather than probabilities. E,g. Instead of saying (1% of people use drugs and they test positive 80% of the time while non-users 5% of the time), you say From 1000 people, 10 use drugs, 8 drug users test positive, while 50 non-users test positive).
It seems to work.
If it's really hard, we should target really bad, really harmful biases.
From here
Perhaps finding out which are the worst biases, and what are the best interventions for them are would be useful. But increasing the effectiveness of changing beliefs is potentially dangerous, so maybe not.