Insights from the Research Team

Our Approach to Moral Weights

Published on
2022-11-30
Written by
Rosie Bettle
Vadim Albinsky
Tom Barnes

Photo by Piret Ilver on Unsplash.

This is an introduction to our approach to moral weights.

Introduction

At Founders Pledge, we aim to find the most effective ways to do good through charitable giving—this involves contrasting the impact of different charities and possible interventions. However, many of the charities that we evaluate improve different aspects of people’s lives. For example, charities such as the Against Malaria Foundation are able to reduce rates of mortality. Other charities, such as StrongMinds, improve beneficiaries’ mental wellbeing. Finally, charities such as Bandhan focus upon improving people’s economic circumstances.

Moral weights allow us to compare the effectiveness of charities that work across these different areas. Say that charity A focuses upon improving people’s economic circumstances in low income countries, whereas the benefit of another charity B comes through reductions in mortality. As well as working out how effective each charity is within its given area (the degree to which charity A is impactful in improving economic circumstances, and how effective charity B is at reducing mortality), we also need to establish the relative importance of these respective aims. That is, how important is it to improve the economic circumstances of people in low income countries, relative to reducing mortality? While these moral weights can be difficult to think about, any decision about prioritizing charities depends (at least implicitly)1 upon moral weights. At FP, we aim to be explicit about how we think about and use moral weights.

Thus far, we have modeled the expected impact of global health and development programs via metrics that correspond to four primary ways of doing good in the world—meaning that we need a set of moral weights that allow us to compare between these four metrics. The first is by reducing mortality, which we model using the expected number of lives saved (both for deaths of young children, and for people over the age of five). The second is by improving health more broadly, which we measure using Disability-Adjusted Life Years; a DALY is equivalent to the loss of one year of life in perfect health (see link). The third is by improving mental wellbeing, which we measure using WELLBYs; a loss of one WELLBY is a drop in life satisfaction of 1 point on a 1-10 scale, for one year. The fourth is by improving economic circumstances, which we typically measure in income doublings; one income doubling refers to doubling the income of one person in a low-income country for one year (i.e. giving someone a cash transfer equal to their annual income).

How can we estimate moral weights across these measures? One approach is to use surveys, to establish how people value these measures. This approach has been most extensively used to establish how people trade off between lives saved and economic benefits. For example, GiveWell has conducted a series of surveys to establish the moral weights of their donors2, and also commissioned IDInsight (a data-analytics and research organization) to run surveys with people living in extreme poverty in Kenya and Ghana3. Along similar lines, GiveWell and Founders Pledge have also previously used their staff members’ own moral weightings. There are reasons to expect all these viewpoints to be important. For example, it is donors who are providing the money—consequently, it is important to represent their moral preferences. At the same time, most of the charities we might support work with people in extreme poverty, and they may have preferences that differ from those of donors. Finally, staff members at charity evaluators such as GiveWell have the advantage that they have spent a considerable amount of time thinking about these questions and using these metrics.

Another approach, which to the best of our understanding has been less well used, is to use empirical data. This is only possible for certain comparisons, where data is available—such as understanding the trade off between economic benefits and wellbeing. Since there is existing data (via the Happier Lives Institute, among others) upon the wellbeing benefits of cash transfers4, it is possible to directly work out how wellbeing benefits equate to economic benefits. Along similar lines, it is also possible to equate health measures to mortality, since we can estimate the years of healthy life that make up the average lifespan.

In our updated approach to moral weights, we use a mixture of survey-based methods (including deferring to previous estimates from Open Philanthropy and GiveWell)5 and empirical methods to provide a set of moral weights across lives saved, WELLBYs, DALYs and income doublings. We do this via three steps (see Fig 1). In step one, we convert income doublings into wellbeing via the use of real-world data analysed by the Happier Lives Institute6. In step two, we convert between income doublings and the value of a life (under 5 years of age and over 5 years of age) through three approaches that we weight equally; deferring to Open Philanthropy and GiveWell, deferring to the viewpoints of people living in extreme poverty, and taking a utilitarian approach that equates the point where the happiness from one income-doubling cash transfer is equivalent to the happiness ‘saved’ by saving a life. In step three, we estimate the value of a life in health terms (DALYs). This provides us with moral weights across income doublings, wellbeing, health and lives saved.

Overall, we take a diverse approach that weights the opinions of typical charity recipients, donors and researchers, but is also grounded in empirical data. Establishing this wide set of moral weights allows us to flexibly use different metrics of ‘doing good in the world’, maximizing our ability to take advantage of different data sources that might be available to study a given intervention. While we expect methods towards estimating moral weights to further improve in the future, we think this improves our abilities to identify the most effective ways to do good in the world.

Continue reading to learn about how we calculate and compare different sources and see the full report.

Rosie Bettle

Rosie is an Applied Researcher based in London, focusing on Global Health & Development. Before joining Founders Pledge in March 2022, she attained a PhD in Biopsychology from the University of Michigan; her published work is on the topic of cognitive evolution (and involved a lot of running around after monkeys). She has a masters degree in Human Evolutionary Biology from Harvard University, and her BA is in Biological Sciences, from Oxford University.

Vadim Albinsky

I am an applied researcher. I studied applied math, economics and statistics in college, and have spent my career until now in finance, working at banks and hedge funds. I am very interested in effective altruism, reading broadly, and meditation.

Tom Barnes

Tom joined Founders Pledge in September 2021 as a Junior Researcher. He studied Philosophy, Politics and Economics at Warwick, getting involved with the Effective Altruism university group. After graduating in July 2021, he interned with Rethink Priorities, researching various longtermist causes.

Outside of EA, he enjoys philosophy chats, maps and cats.