Tag Archives: Prioritisation

Who is setting global priorities?

In a situation where different activities have very different benefit to cost ratios, it is important to set priorities, and finish those with the highest values first.  Any individual who didn’t set priorities would achieve much less than they could; they might end up malnourished because they are busy reading their junk mail. While it is relatively easy to set priorities for a single human’s personal life – not that we always follow them - setting priorities for humanity as a whole is very difficult and requires in-depth study.

The central limit theorem suggests that the cost effectiveness of different projects ought to have a ‘log normal’ distribution, if not an even fatter-tailed one. Furthermore, there is no reason to think that (e.g.) political reform, different environmental causes, R&D for various technologies, conflict resolution, poverty reduction and so on are ee in the same ball-park of cost effectiveness, so we should anticipate a large variance in the distribution. This would leave some causes orders of magnitude more important than others. What research on this topic has been done, by groups like J-PAL, GiveWell, the WHO, and so on, indeed finds that the value of different methods of improving the world varies dramatically, with some doing enormous amounts of good and others achieving next to nothing. Unfortunately, as far as I am aware – and I would love to be informed otherwise – there is no one who has taken on the role of picking out and promoting the most important tasks we face.

The Copenhagen Consensus set out to fill this gap in 2003, and produced reports that were of mixed quality, though excellent value for money and a substantial improvement on what existed before. Sadly, it is not currently planning another round of research because it is out of funding (though still taking donations). In the absence of a comprehensive and broad comparison of different causes, resources naturally flow to the most powerful or vocal interest groups, or the approaches that people intuitively guess are best. Given our terrible instincts for risks and magnitudes we don’t have regular direct experience with, it would be an extraordinary coincidence if these actually were the most valuable projects to be embarking on.

The natural home for a properly-funded and ongoing global prioritisation research project would be the World Bank or alternatively, the OECD, or a university. If anyone is reading this and has some influence: global prioritisation looks like a cost effective cause to hop on. Though given the lack of research on the topic, I’ll admit it is hard to be sure!

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Which biases matter most? Let’s prioritise the worst!

As part of our self-improvement program at the Centre for Effective Altruism I decided to present a lecture on cognitive biases and how to overcome them. Trying to put this together reminded me of a problem I have long had with the self-improvement literature on biases, along with those for health, safety and nutrition: they don’t prioritise. Kahneman’s book Thinking Fast and Slow represents an excellent summary of the literature on biases and heuristics, but risks overwhelming or demoralising the reader with the number of errors they need to avoid. Other sources are even less helpful at highlighting which biases are most destructive.

You might say ‘avoid them all’, but it turns out that clever and effort-consuming strategies are required to overcome most biases; mere awareness is rarely enough. As a result, it may not be worth the effort in many cases. Even if it were usually worth it, most folks will only ever put a limited effort into reducing their cognitive biases, so we should guide their attention towards the strategies which offer the biggest ‘benefit to cost ratio’ first.

There is a bias underlying this scattershot approach to overcoming bias: we are inclined to allocate equal time or value to each category or instance of something we are presented with, even if they are arbitrary, or at least not a good signal of their importance. Expressions of this bias include:

  • Allocating equal or similar migrant places or development aid funding to different countries out of ‘fairness’, even if they vary in size, need, etc.
  • Making a decision by weighing the number, or length, of ‘pro’ and ‘con’ arguments on each side.
  • Offering similar attention or research funding to different categories of cancer (breast, pancreas, lung), even though some kill ten times as many people as others.
  • Providing equal funding for a given project to every geographic district, even if the boundaries of those districts were not drawn with reference to need for the project.

Fortunately, I don’t think we need tackle most of the scores of cognitive biases out there to significantly improve our rationality. My guess is that some kind of Pareto or ’80-20′ principle applies, in which case a minority of our biases are doing most of the damage. We just have to work out which ones! Unfortunately, as far as I can tell this hasn’t yet been attempted by anyone, even the Centre for Applied Rationality, and there are a lot to sift through. So, I’d appreciate your help to produce a shortlist. You can have input through the comments below, or by voting on this Google form. I’ll gradually cut out options which don’t attract any votes.

Ultimately, we are seeking biases that have a large and harmful impact on our decisions. Some correlated characteristics I would suggest are that it:

  • potentially influences your thinking on many things
  • is likely to change your beliefs a great deal
  • doesn’t have many redeeming ‘heuristic’ features
  • disproportionately influences major choices
  • has a large effect substantiated by many studies, and so is less likely the result of publication bias.

We face the problem that more expansive categories can make a bias look like it has a larger impact (e.g. ‘cancer’ would look really bad but none of ‘pancreatic cancer’, ‘breast cancer’, etc would stand out individually). For our purposes it would be ideal to group and rate categories of biases after breaking them down by ‘which intervention would neutralise this.’ I don’t know of such a categorisation and don’t have time to make one now. I don’t expect that this problem will be too severe for a first cut.

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