“It is one of the unfortunate truisms of the human condition that there is hardly a good idea, noble impulse, or sound suggestion that can't be (and isn't eventually) adopted and bastardized by zealots… One iteration of this tendency is in the idea of “effective altruism.”

- K. Berger & R. M. Penna

In this chapter, we’ll give you time to reflect on what you think of effective altruism, and of the specific potential priorities you’ve heard about so far. 

We are dedicating a section to this because, to whatever extent we are wrong, realizing and correcting our mistakes will allow us to do more good. Honestly reckoning with strong counterarguments (from both within and outside of the EA community) can help us avoid confirmation bias and groupthink, and get us a little closer to identifying the most effective ways to do good. 

Such critiques have led to important changes in what many EAs do. For example, GiveWell received some criticisms for making moral tradeoffs on behalf of the people they were trying to help. In response, they reached out to a sample of people demographically similar to the people affected by their analysis, and asked them how they would make moral tradeoffs.

A key concept for this session is the importance of forming independent impressions. In the long run, you’re likely to gain a deeper understanding of important issues if you think through the arguments for yourself. But (since you can’t reason through everything) it can still sometimes make sense to defer to others when you’re making decisions.

We are also including pieces on Bayes’ rule and general approaches to dealing with evidence in this session because it is another tool that can be utilized for a wide range of difficult decisions. By thinking more clearly about how much we should update our views based on new evidence, we can become more calibrated and thereby better decision-makers.

 

This work is licensed under a Creative Commons Attribution 4.0 International License.

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"Such critiques have led to important changes in what many EAs do: for example, GiveWell polled a sample of people demographically similar to recipients of programs it supports on how they would make moral tradeoffs in response to criticisms that it shouldn’t make moral tradeoffs on behalf of the people its recommended charities benefit."

This is a very interesting fact! However, it is really a long and awkward sentence to parse. Friendly suggestion from a reader: maybe split this up into multiple sentences?

Thanks! I edited - does it seem clearer now?

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