Until March 2023, I was the Communications Manager at the Happier Lives Institute. Before that, I was an Events Associate at the Centre for Effective Altruism, helping to produce EA Global and EAGx conferences.
I practice Vipassana meditation for two hours each day. Buddhist philosophy provides the foundation for my commitment to effective altruism and doing the best I can to reduce the suffering of others.
Hi Henry. Thanks for your feedback! I’ll let Joel respond to the substantive comments but just wanted to note that I’ve changed the “Appendix D” references to “Appendix C”. Thanks very much for letting us know about that.
I’m not sure why Appendix B has hyperlinks for some studies but not for others. I’ll check with Joel about that and add links to all the papers as soon as I can. In future, I plan to convert some of our data tables into embedded AirTables so that readers can reorder by different columns if they wish.
Thanks very much for your reply. I agree this topic is important and should be discussed more.
Re: paternalism
I guess all altruistic acts have some element of paternalism (despite our best intentions). I think we both agree that we should give people options to improve their wellbeing, rather than forcing them into something. However, we have to decide which option(s) to provide—increasing income, extending lives, treating mental illness etc. - and this is where we differ. You seem to be prioritising the options based on intuition, whereas I prefer to use evidence from self-reports.
Re: mental states
In the case of polling women, the results would be subject to all of the affective forecasting biases I mentioned before. To avoid paternalism, we should let the data speak for itself. If women in the 1970s said they were 8⁄10 and women in the 2020s say they are 7⁄10 (I’m using made-up numbers here) then we should try to identify the cause(s) of that decline rather than dismiss the data on the assumption that life for women is clearly better than it used to be. Some things have clearly improved, but those improvements might be cancelled out by other factors which are not immediately obvious.
Re: AI maximising happiness
You said: “We’ll all end up on some IV drug drip or the equivalent, and to me that’s a nightmare.” but that’s a very speculative claim. Personally, I would be very surprised if a happiness-maximising AI would put you in a situation that you perceived as a nightmare.
Re: religion
Here, I will defer to a blog post written by my colleague, Samuel Dupret, who thinks very deeply about this question.
Thanks very much for writing this. It’s helpful to have a clear and succinct summary of the capabilities approach on the Forum and I thought the post was constructive and well-written. It provides a nice counterpoint to HLI’s post, To WELLBY or not to WELLBY?
However, the capabilities approach (as you describe it here) strikes me as deeply paternalistic. How do we decide which capabilities to prioritise without asking people how much they value them? We can’t just defer to Nussbaum.
In the post you say:
The third approach, which I personally prefer, is to not even try to make an index but instead to track various clearly important dimensions separately
and also,
If you don’t know precisely what to maximize for people, then picking staying alive and having resources is a very good start.
To me, it looks like you’ve decided what the priorities should be based on what you think is “clearly important”. But as this post shows, humans are terrible at ‘affective forecasting’ i.e. we underestimate the importance of things that are resistant to hedonic adaptation and difficult to mentally simulate.
The thing is, we don’t have to guess. We can look at subjective wellbeing data from longitudinal studies to identify which capabilities have the most impact on people’s lives. The Origins of Happiness is the best example I’ve seen of this and is packed full of surprising insights. If adversity or discrimination had no effect on your subjective wellbeing, then those terms would be meaningless.
I think the crux of our different views is that I don’t see subjective wellbeing as one of many functionings. Instead, I place high credence on the view that wellbeing is the intrinsic good. Everyone cares about lots of things (positive emotions, achievements, having kids, art, knowledge, freedom, religious belief etc.) but you need to make trade-offs between them and that requires a common unit.
I’m nearly always a 7⁄10 or 8⁄10 on the common happiness-type questions. I guess that this means that I could “improve” this, but honestly I’m not trying to do this at all.
Here, I think you’re confusing emotional states with evaluations of life satisfaction. Most people don’t want to feel happy at a funeral. Instead, we want to be satisfied with our current experience, free from desires for a different state of affairs. When you chose to have kids, I expect you were trading off positive emotions for greater life satisfaction and that’s a totally reasonable thing to do. There’s a great clip of Daniel Kahneman discussing this here.
Using subjective measures to allocate aid means that targeting will depend in part on people’s ability to imagine a better future (and thus feel dissatisfaction with the present).
For me, dissatisfaction and suffering are synonymous so I would prioritise an unhappy billionaire over a happy rural farmer, even though this may seem counterintuitive to many. In practice, however, there are a lot of unhappy rural farmers and it’s much cheaper to help them. The reason I work at the Happier Lives Institute is that I want to understand what will really help them the most, rather than deferring to the common assumption that it must be income gains and lives saved.
(commenting in a personal capacity etc.)
That first point could be rephrased as “an exclusive SWB focus prioritizes providing resources to people who are less able to psychologically adapt to bad circumstances.”. That seems like a good approach to me.
In the example you give, I’m not sure the previous circumstances are relevant to the question. In that situation, I would prioritise the person who was suffering the most (all else equal).
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If you found this post helpful, please consider completing HLI’s 2022 Impact Survey.
Most questions are multiple-choice and all questions are optional. It should take you around 15 minutes depending on how much you want to say.
If you found this post helpful, please consider completing HLI’s 2022 Impact Survey.
Most questions are multiple-choice and all questions are optional. It should take you around 15 minutes depending on how much you want to say.
If you found this post helpful, please consider completing HLI’s 2022 Impact Survey.
Most questions are multiple-choice and all questions are optional. It should take you around 15 minutes depending on how much you want to say.
If you found this post helpful, please consider completing HLI’s 2022 Impact Survey.
Most questions are multiple-choice and all questions are optional. It should take you around 15 minutes depending on how much you want to say.
If you found this post helpful, please consider completing HLI’s 2022 Impact Survey.
Most questions are multiple-choice and all questions are optional. It should take you around 15 minutes depending on how much you want to say.
If you found this post helpful, please consider completing HLI’s 2022 Impact Survey.
Most questions are multiple-choice and all questions are optional. It should take you around 15 minutes depending on how much you want to say.
If you found this post helpful, please consider completing HLI’s 2022 Impact Survey.
Most questions are multiple-choice and all questions are optional. It should take you around 15 minutes depending on how much you want to say.
If you found this post helpful, please consider completing HLI’s 2022 Impact Survey.
Most questions are multiple-choice and all questions are optional. It should take you around 15 minutes depending on how much you want to say.
If you found this post helpful, please consider completing HLI’s 2022 Impact Survey.
Most questions are multiple-choice and all questions are optional. It should take you around 15 minutes depending on how much you want to say.
If you found this post helpful, please consider completing HLI’s 2022 Impact Survey.
Most questions are multiple-choice and all questions are optional. It should take you around 15 minutes depending on how much you want to say.
If you found this post helpful, please consider completing HLI’s 2022 Impact Survey.
Most questions are multiple-choice and all questions are optional. It should take you around 15 minutes depending on how much you want to say.
Hi Nick. I found more details about the Baird et al. RCT here. I’ve copied the section about the ‘cash alone’ arm below as I know you’ll be interested to read that:
One of the issues that can cause difficulties in the interpretation of the findings from this study comes from the fact that it does not have a classical 2x2 factorial design that includes a “cash alone” arm. While it would have been ideal, from a study design perspective, to have such a design, which would have enabled us to experimentally reject (or not) that cash alone would have been as effective as IPT-G+. Such benchmarking of the (cost-) effectiveness of a group therapy intervention to cash transfers alone would have been nice, the three-arm trial we designed for our setting, leaving out a “cash-only” arm, is an adequate study design for the following three reasons.
First, the extant evidence on the effects of economic interventions in general, or cash transfers in particular, do not support the idea of improved mental health outcomes past the short-run. For example, in their review, Lund et al. (2011) finds that the mental health effects of poverty alleviation programs were inconclusive. Blattman, Jamison, and Sheridan (2017) find no effects of lump-sum cash transfers alone on mental health outcomes in the short- or the medium-run. Short-term effects of cash transfers (monthly or lump-sum) on psychological wellbeing that were observed in the short-run dissipated a couple of years later (Baird, de Hoop, and Özler 2013; Baird, McIntosh and Özler 2019; Haushofer and Shapiro 2016, 2018). Hence, we do not think that there is sufficient equipoise to include a “cash only” arm when it comes to sustained effects on depression two-years after the end of the intervention.
Second, even if one could make a case that there may be a sustained income effect on mental health – for example, such as those indicated by studies of lottery winners (Gardner and Oswald 2007; Lindahl 2005) – the amounts offered to IPT-G participants here are too small to have this kind of an effect two years after they are transferred. A similar argument has been made in another experiment that lacked a pure unconditional cash transfer (UCT) arm: Benhassine et al. (2015) argue that the labelling of the cash transfer as an education support program increased school participation through its effect on the “...parents’ belief that education was a worthwhile investment,” rather than through a pure income effect, because the transfers were too small to cause the observed effects.
Finally, and related to the point above, one of the aims of our trial is to test the efficacy of a low-cost and scalable intervention through two NGOs that have a track record of implementing programs that are being utilized here (BRAC Uganda and StrongMinds Uganda). While BRAC Uganda is interested in taking advantage of its ELA girls’ clubs’ platform to provide mental health services across Uganda, it does not have any plans to provide UCTs, especially not in transfer sizes that might perhaps have sustained effects. Hence, the lack of evidence on the potential effectiveness of UCTs on sustained reductions in depression, combined with a lack of interest from the implementing partners, resulted in the study team designing a trial that has only three arms. Should the trial show that IPT-G+ is significantly more effective than IPT-G alone in reducing depression in the medium-run, our interpretation will be that there is a complementarity between the two interventions, and not that cash is effective on its own for sustained improvements in psychological wellbeing.
Love this! I found it really valuable to be reminded of all the posts I’ve read this year and to reflect on how they’ve shaped my thinking. Big props to everyone involved in making this.
That’s good to know, thanks for clarifying. A democratic process is definitely better than a top-down approach, but everyone who participates in that process will be subject to affective forecasting biases too. That’s why I favour using subjective wellbeing data, but I’m keen to hear about alternative options too.