A guided cause prioritisation flowchart

By JackM @ 2022-01-03T20:32 (+44)

Overview

I have previously written about the importance of making it as easy as possible for EAs to make a fully-informed decision on preferred cause area, given the potentially astronomical differences in value between cause areas. Whilst one piece of feedback was sceptical about the claim that these vast expected value differences exist, generally feedback agreed that the idea of making cause prioritisation easier, for example by highlighting key considerations that have the biggest effect on choice of preferred cause area, could be high impact.

In light of this I have decided to progress this idea by putting together a first draft cause prioritisation flowchart designed to guide people through the process of cause prioritisation. The flowchart would ideally be accompanied by guidance assisting making informed decisions throughout the flowchart. I haven’t finalised this guidance, although present a sample for one particular decision in the flowchart. At this point I am attempting a proof of concept rather than delivering a final product, and so would welcome feedback on both the idea and the preliminary attempt.

Introducing the flowchart

In the following section you can see my draft flowchart. The flowchart asks individuals ethical and empirical questions that I view as most important in determining which cause area they should focus on. Only cause areas that are accepted as important by a non-negligible proportion of the EA community are included in the flowchart. In addition, some foundational assumptions common to EA are made, including a consequentialist view of ethics in which wellbeing is what has intrinsic value.

A key component of a final flowchart would be accompanying guidance to help individuals make informed decisions as they progress through the flowchart. I have not put together all of this guidance at this stage, however as part of the proof of concept I have attempted to illustrate what this might look like for the “Can we influence the future?” question. My vision for a final flowchart would be being able to click on each box to be guided to easily-digestible reading enabling an informed choice on how to proceed.

In my view, some strengths of this flowchart compared to the main previous attempt include:

• It includes an up-to-date set of cause areas: the previous attempt that I have come across is, in my opinion, slightly out of date in that it excludes options that have fairly recently entered the mainstream of EA, such as investing for the future. The previous attempt also includes some cause areas that aren’t typically considered high impact by EAs today, such as education or human rights.
• It includes more nuances relevant to longtermist cause areas: my flowchart considers nuances such as the consideration of whether or not one thinks that the future is likely to be good. It has been suggested/hinted that not believing that the future is likely to be good may lead one away from longtermism as one would not want to prolong a bad future. However, there is a class of cause areas that could be said to broadly sit under “Improving quality of the future” that would remain robust to this view, and indeed other views that some people think invalidate longtermism such as a person-affecting view of population ethics.
• It includes (very incomplete) guidance that assists with making decisions along the flowchart: my vision for a final flowchart is one that is accompanied by guidance helping one make an informed decision throughout the flowchart. This feels like an essential part of any flowchart - without it one is just making gut judgements on very complex questions for which much discussion has already taken place. This is my main bone to pick with the previous attempt.

I would like to note that I don’t see my flowchart as clearly better than the previous attempt and I certainly don’t see it as final or even close to final. I think it is likely that substantial improvements can be made on my attempt.

The (draft) flowchart

Sample Guidance

Can we influence the future?

Is it possible to improve the future (beyond 100 years) in expectation?

Key reading:

• The case for strong longtermism (June 2021) by MacAskill and Greaves (Section 4)

Whilst it might at first seem unrealistic that we can positively influence the far future (say more than 100 years from now) in expectation, many EAs believe that there are a variety of ways in which we can do so.

One class of interventions that aims to influence the far future in a positive way are those that involve trying to ensure we stay or end up in “persistent states” of the world that are better than others. A persistent state is a state of the world which is likely to last for a very long time (even millions of years) if entered. If we can do things to increase the probability that we end up in a better persistent state than a worse one, we will then have influenced the far future for the better in expectation on account of how long the world is likely to stay in that better state.

There are a number of real world examples of attempting to steer into better rather than worse persistent states:

• Mitigating risks of premature human extinction: Human extinction is a persistent state as it would be very unlikely for humanity to re-evolve once extinct. The existence of humanity is also a persistent state: while we face risks of premature extinction, humanity’s expected persistence is vast. If we expect future lives to be net positive and adopt a total utilitarian view of population ethics in which the goodness of a state of the world depends on the total sum of welfare, then extinction would be a vastly worse persistent state. In this case, doing things to reduce the chance of premature human extinction would have high expected value. This could include the detection and potential deflection of asteroids, or reducing the risks of extinction-level pandemics.
• Influencing the choice among non-extinction persistent states: There are also potential persistent states of the world that do not rely on extinction. Many EAs are concerned about risks of artificial superintelligence (ASI). ASI could be developed once we have built human-level AI which could then recursively self-improve, designing ever-better versions of itself, quickly becoming superintelligent. From there, in order to better achieve its aims, it could try to gain resources, and try to prevent threats to its survival. It could therefore be incentivised to take over the world and eliminate or permanently suppress human beings. Alternatively, if an authoritarian country were the first to develop ASI, with a sufficient lead, they could use this technological advantage to achieve world domination and quash any competition. In either of these scenarios, once power over civilisation is in the hands of an ASI, this could persist as long as civilisation does. Different versions of the ASI-controlled futures are therefore persistent states with significantly differing expected value, and working to ensure ASI is aligned to our interests could therefore improve the far future in expectation.

Outside of the class of interventions that involve steering between persistent states, one can look to speed up progress to improve every time period in the future:

• Speeding up sustainable progress: Provided value per unit time doesn’t plateau at a modest level, bringing forward the march of progress could have long-lasting beneficial effects compared to status quo, as each time period would be better off than it would have been otherwise. Therefore boosting economic growth or speeding up technological progress could have very large positive effects. Under this scenario, one would want to ensure that such progress is sustainable i.e. that it can reliably continue for a long time period. This can be achieved by tackling climate change and ensuring that we can progress in a way that doesn’t negatively impact the environment or biodiversity on which our progress relies.

There are also a number of “meta” options to improve the far future:

• Global priorities research: It may be the case that further research can uncover interventions that would significantly improve the far future, that we aren’t aware of at the moment. Provided that subsequent governments or philanthropists would take due note of the results, this ‘meta-option’ could easily have much greater far-future expected benefits than the best available near-future expected benefits, since it could dramatically increase the expected effectiveness of future governmental and philanthropic action.
• Investing for the future: It might be that we are not living at the most influential time now as we may have a better idea about how to do good in the future, including on how to improve the very far future. In this case we may want to invest for these more influential periods, for example by movement building now, or investing financially. Investing financially may also be high impact on the far future due to investment returns meaning the pot of money grows over time, even in real terms.

There are therefore a number of potential ways to impact the far future that have been put forward by EAs. If you think any of the above have serious potential to impact the far future in a positive way, you should answer “Yes” at this point.

Next steps

At this point I would welcome feedback on:

• The general idea of having a cause prioritisation flowchart with guidance: my (ambitious) vision would be for such a flowchart to be used widely by new EAs to help them make an informed decision on cause area, ultimately improving the allocation of EAs to cause areas.
• The flowchart itself: are there any key considerations that have been missed? Are there any other cause areas that should be included? It is very difficult if not impossible to put together a flowchart including all relevant nuances but a final flowchart should include all key considerations.
• The sample guidance: Is this roughly the right length, detail and difficulty to guide someone through the flowchart?

I would also be interested to hear if anyone else would be interested in collaborating on such a flowchart given that there is more work to be done. I should say however that I may abandon this project if feedback is lukewarm/negative and it doesn’t look like pursuing with it would be high impact.