The role of time in comparing diverse benefits

By Michelle_Hutchinson @ 2015-04-13T20:18 (+2)

        Every week or so, the CEA office holds a lunch on a particular topic – whether a presentation or just a discussion led by someone on a particular topic. Last week, the Global Priorities Project hosted one on how to compare very different goods, and I thought people on the forum might be interested in some of the considerations that came up. This is just a couple of the points which I remember being made – it’s not a defence of a particular view, or a particular person’s stance. I did try to pick out a somewhat coherent thread to make it a more interesting post.

Time and units of benefit

        One thing that makes it more difficult to compare between benefits is that they seem to have different natural units. That’s just true because some ways of helping people improve their lives in different ways. It’s also because different benefits seem to naturally manifest at different times.

For example, say that I’m trying to decide between treating TB or trying to reduce the impact that climate change will have in hundreds of years time. A natural way to compare these might seem to be to ask how many lives I could save over the next year by treating TB, and how many lives I could save in, say, 300 years time (in expectation) by reducing carbon emission. However, doing that wouldn’t be comparing like to like. One reason is that treating TB this year would also have an impact on the state of the world in 300 years time. What that impact would be is very hard to determine. But so is the impact of a particular intervention aimed at reducing climate change’s harm in hundreds of years time. Treating TB this year seems likely to have positive flow through effects on the future – whether that’s through economic benefit which lasts into the future, or the burden from TB being slightly reduced over the long-term. (Additionally, both of these would also make society more able to adapt to climate change.)

So how should our reasoning change if we want to make sure that we compare like with like when it comes to interventions aimed at different time periods? One upshot is that it means that questions surrounding how many people will exist in the future are less important than we might have thought. If we compared how many lives we can save from TB next year to how many we could save from climate change in 300 years time, it would be very important how many people there are around in 300 years time to save. But if we take into account the fact that saving people from TB this year will have an impact in 300 years time too, comparing difference in effectiveness of the two interventions no longer depends straightforwardly on the number of people in the future, since the impact of both is likely to be higher, the more people there are in future.

Future consequences of benefits

        The preceding section highlighted the importance of knowing whether interventions that are beneficial in the short term are likely to be beneficial in the long term. For the kinds of interventions we tend to consider – ones that improve global health or increase education or income – it seems plausible that this is the case. After all, if people are healthier or more educated they typically become richer, and which allows them to invest in more education and research in the future, and so on.

However, we might want to question that assumption. We might think that it is not generally the case that current benefits increase the chance/quantity of future benefits, but that that is only the case in times of peace. If you’re a nation at war with another nation, you are likely to want to the other nation to be less developed and poorer. However, overall wars seem less likely to happen if nations are more prosperous and resources are not scarce.

A second reason for questioning the idea that current benefits will lead to future benefits is the fact that in nature populations tend to experience cycles. A population of rabbits might increase until the point where it was overstretching the food supply, at which point many would starve and the population would decrease. Or the increase in rabbits would be followed by foxes proliferating, which would shrink the rabbit population. If humans are relevantly similar to other species, perhaps we should expect that short term benefits to humanity will simply hasten a time when there is a lack of resources. One reason to think that humans are not relevantly similar to other species, however, is our capacity for adaptation. Far more than other animals, we are able to change which resources we use. Therefore it doesn’t seem necessary that current benefits speed-up harm coming to us – it seems more likely that (very broadly speaking) benefiting people today improves their future. An exception might be harm coming from advancing technology, which could be sped up if current benefits increase the rate of technological progress.

How uncertainty about interventions might affect our choices

        Say that we thought that we could save more lives in 300 years than we can now, because we think there will be more people in 300 years. In that case, even if we think that treating TB now will have a positive effect in 300 years time, it seems likely that we would still want to opt for directly tackling climate change. After all, an intervention that is directly aiming at improving the state of the world in 300 years time seems more likely to do that than one which is aiming at helping people this year.

        On the other hand, it seems very difficult to know how good interventions which aim to minimise the harm of climate change in 300 years time are. For one thing, we can’t test their relative efficacies. On the other hand, we know quite a lot about health interventions and we certainly can test and compare them. Since that’s the case, even if the average current health intervention was worse than the average future-oriented intervention, it might be that we would be better off supporting current health interventions. The reason is that we can tell which the best health interventions are, and we might expect those to be better than the average future-oriented interventions.