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benleo

180 karmaJoined Feb 2016

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21

I think this is a great idea. I agree that it is much easier to shift giving within a cause area than between cause areas. 

I do wonder if there are ways to build in cross-causal giving using this platform. For example, I am curious whether the giving multiplier mechanism would be an effective way to achieve both 1) increased effectiveness within climate change donations and 2) substitute some donations to other cause areas. However, I would be hesitant to include this straight away, but if the EEA EF gets momentum it is something to consider. 

Also, I am curious what your strategy is in marketing the platform to non EAs who care about climate change. Have you had any success stories so far? 

Thanks for posting this, I have a few questions. 

Do you have any other metrics besides visiting the website? Is there a link such as "learn more about veganism" that you can track? 

Besides anecdotes, do you have evidence/data that the "dog meat" intervention works better than other interventions?

I do worry that while shock value may work for some people, it could push other people further away from veganism (especially if they felt deceived). But, I am unsure how serious (or important) this concern is. 

I'm also impressed by this post. HLI's work has definitely shifted my priors on wellbeing interventions. 

We strive to be maximally philosophically and empirically rigorous. For instance, our meta-analysis of cash transfers has since been published in a top academic journal. We’ve shown how important philosophy is for comparing life-improving against life-extending interventions. We’ve won prizes: our report re-analysing deworming led GiveWell to start their “Change Our Mind” competition. Open Philanthropy awarded us money in their Cause Exporation Prize

It's also great to see the organisation taking philosophical/empirical concerns seriously. I still have some concerns/questions about the efficacy of these interventions (compared to Givewell charities), but I am confident in HLI continuing to shed light on these concerns in the future. 

 

For example, projects like the one below I think are really important. 

  • Develop the WELLBY methodology, exploring, for instance, the social desirability bias in SWB scales

and

building the field of academic researchers taking a wellbeing approach, including collecting data on interventions. 

The reference classes I look at generate a prior for AGI control over current human resources anywhere between 5% and 60% (mean of ~16-26%).

 

Thanks for this Zach. I found it quite thought provoking, especially the quoted sentence. 

 

Based on your model,  AGI controlling human resources is much more likely to occur than extinction. Given that, what events do you think we should be worried about with losing autonomy over resources (and potentially institutions) and are you more concerned about that after this work? 

Here is a paper by Steve Levitt that argues that for people who are having difficulty making a decision (quitting your job, ending a relationship etc), those that do make a change are happier 6 months later. 

 

Here is an open access earlier version of the working paper. 

Participants donated their own money. They received a bonus of £1 and could choose how much of it they wanted to keep or donate. 

This is a fantastic idea. Congratulations to all involved. 

Out of curiosity, does GD have any data on whether other religions donate a portion of their tithe/tzdaka/etc to GD? 

This is fantastic news!

As an experimental economist, I hope this has spillovers to our field (as well as others).  

At the feedback level (referee reports, presentations etc), I believe there is significantly more value to be gained when discussing the experimental design itself before any data is collected. 

Congrats to Hauke, Chris, and all others involved.

Thanks Catherine. We just used the platform Prolific for subject recruitment.

Thanks David, that would be great! I'll check to see if there is a way to run it on STATA, but if not I can just run it on R. 

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