Abstract: "Using reasoning and evidence to do the most good"; the fundamental idea of Effective Altruism. But how does one accomplish that? In this article I'll discuss why I believe the focus of EA so far has been largely misplaced, and how we can tackle the subject better.
Disclaimer: My knowledge of how things actually get done by the people who read this forum is rather limited. The points made in this article were based on reading what the site recommends, and skimming the forum.
Let's call the point in time we're at - point A. From point A. spreads a tree of possibilities that leads to many potential different outcomes. To simplify matters, we can imagine each outcome, each potential world, as a giant white wall plagued by black spots. The spots diverse in size (i.e the amount of people affected), and intensity (i.e. the expected value - which holds within it both the present and near future ramifications, and the deterioration function if left unattended). Our chosen path is the one that leads to the outcome with the least black surface with the least intensity. Of course, the model has several problems – the main one being not defining the deterioration function, and unifying it with the near-future ramification – but there are others. While one can't denounce them insignificant, to the matter of separating consequential paths from non-effective paths those aren't of importance
Notice the wording: Consequential paths. Not consequential problems.
EA has mostly solved the almost hidden problem of philanthropy. But it did not do so by learning and prioritizing black spots. The achievement came from learning and prioritizing erasers. So why do we focus on problems so much, when considering a life course?
Perhaps the best analogy to explain the point would be in the game of chess. Asking what is the most important problem, or how many people work on it, is almost like trying to determine whether you should attack the kingside, or the queenside, by calculating how every single line you can theoretically choose (good, interesting and bad ones) will enact, averaging all of them for each choice, and comparing the results. Preposterous! I do not care for every single line of attack! I care for the best one, and on the case it isn't clear, the very few best ones.
Whether you plan to change the world, or in search of the career that achieves the most good among the selected group you will also enjoy, clearly you should not ask what is the 'biggest' problem in the world; (Which, I am still not convinced our parameters help to determine, but that's for a different article), you should ask a simply put question: among the options I hold, which one has the besterasing expected value?
Now assuming you're from the former group, I'll go even further than that. A year ago, we were at point Ap. From Ap to A, the black dot symbolizing global warming had become slightly easier to erase; which is remarkably surprising, since it is the second time in over ten years someone can even consider making such a claim. The obvious following question - would be what, or who, is the cause for that statement. Since we're discussing a problem of such a scale, we would expect it to be a major powerhouse – the last time, for example, it was the Paris Agreement signed in UNFCCC by 186 countries. One could hypothesize, that Perhaps a miscalculation in the models leading to a disaster large enough to change the public's mind; or maybe, the mid-term elections in the US, had changed the political landscape in the largest country in the world enough to cause it. Numerous still-theorized scientific discoveries may come to mind as well.
If you didn't know who I spoke of, it's doubtful a sixteen-year-old girl came to your mind.
On the case of Ms. Thunberg, I will not lengthen in words; it is irrelevant to the point. But this is a fact: Of the many, many people who give their life to serve good, few ever reach the realm of global change. Most of the few seemed a mere few years prior, non-impactful. That they rose so high is not due to luck or perhaps, it shouldn't be.
In any given moment there are invisible points of impacts, buttons hidden within reality that if pressed, incredible achievements for good will follow – only we don't know where. But we don't need an all-knowing entity to tell us we will achieve more 'good' if we take part in larger efforts. So instead of choosing a problem based on an algorithm trys to distinguish between immense problems, all of which need tot be corrected, what will happen, if we choose according to an algorithm more similar to this:
1. Identifying the relevant problems.
2. Analyzing them.
3. Acknowledging the potential points of impact
4. Devising a path that leads to that point.
5. Estimating and comparing the important factors: timeframe, odds both the point of impact is there and as large as you think it is, and that the point will be reached
And then, imagine those people will sit together, and choose which paths have the best value, and each group that agrees on one of them will start walking the path. Little is beyond the reach of power will and careful reasoning. We could be looking on a completely different world in a just a few decades if we start thinking of the problems of the world as a whole, choosing in-between paths and not problems, and useng our biggest strength – that there are others who also aspire for effective altruism, and understand the concept of the Litany of Gendlin(1).
On Paths and Problems
Abstract: "Using reasoning and evidence to do the most good"; the fundamental idea of Effective Altruism. But how does one accomplish that? In this article I'll discuss why I believe the focus of EA so far has been largely misplaced, and how we can tackle the subject better.
Disclaimer: My knowledge of how things actually get done by the people who read this forum is rather limited. The points made in this article were based on reading what the site recommends, and skimming the forum.
Let's call the point in time we're at - point A. From point A. spreads a tree of possibilities that leads to many potential different outcomes. To simplify matters, we can imagine each outcome, each potential world, as a giant white wall plagued by black spots. The spots diverse in size (i.e the amount of people affected), and intensity (i.e. the expected value - which holds within it both the present and near future ramifications, and the deterioration function if left unattended). Our chosen path is the one that leads to the outcome with the least black surface with the least intensity. Of course, the model has several problems – the main one being not defining the deterioration function, and unifying it with the near-future ramification – but there are others. While one can't denounce them insignificant, to the matter of separating consequential paths from non-effective paths those aren't of importance
Notice the wording: Consequential paths. Not consequential problems.
EA has mostly solved the almost hidden problem of philanthropy. But it did not do so by learning and prioritizing black spots. The achievement came from learning and prioritizing erasers. So why do we focus on problems so much, when considering a life course?
Perhaps the best analogy to explain the point would be in the game of chess. Asking what is the most important problem, or how many people work on it, is almost like trying to determine whether you should attack the kingside, or the queenside, by calculating how every single line you can theoretically choose (good, interesting and bad ones) will enact, averaging all of them for each choice, and comparing the results. Preposterous! I do not care for every single line of attack! I care for the best one, and on the case it isn't clear, the very few best ones.
Whether you plan to change the world, or in search of the career that achieves the most good among the selected group you will also enjoy, clearly you should not ask what is the 'biggest' problem in the world; (Which, I am still not convinced our parameters help to determine, but that's for a different article), you should ask a simply put question: among the options I hold, which one has the best erasing expected value?
Now assuming you're from the former group, I'll go even further than that. A year ago, we were at point Ap. From Ap to A, the black dot symbolizing global warming had become slightly easier to erase; which is remarkably surprising, since it is the second time in over ten years someone can even consider making such a claim. The obvious following question - would be what, or who, is the cause for that statement. Since we're discussing a problem of such a scale, we would expect it to be a major powerhouse – the last time, for example, it was the Paris Agreement signed in UNFCCC by 186 countries. One could hypothesize, that Perhaps a miscalculation in the models leading to a disaster large enough to change the public's mind; or maybe, the mid-term elections in the US, had changed the political landscape in the largest country in the world enough to cause it. Numerous still-theorized scientific discoveries may come to mind as well.
If you didn't know who I spoke of, it's doubtful a sixteen-year-old girl came to your mind.
On the case of Ms. Thunberg, I will not lengthen in words; it is irrelevant to the point. But this is a fact: Of the many, many people who give their life to serve good, few ever reach the realm of global change. Most of the few seemed a mere few years prior, non-impactful. That they rose so high is not due to luck or perhaps, it shouldn't be.
In any given moment there are invisible points of impacts, buttons hidden within reality that if pressed, incredible achievements for good will follow – only we don't know where. But we don't need an all-knowing entity to tell us we will achieve more 'good' if we take part in larger efforts. So instead of choosing a problem based on an algorithm trys to distinguish between immense problems, all of which need tot be corrected, what will happen, if we choose according to an algorithm more similar to this:
1. Identifying the relevant problems.
2. Analyzing them.
3. Acknowledging the potential points of impact
4. Devising a path that leads to that point.
5. Estimating and comparing the important factors: timeframe, odds both the point of impact is there and as large as you think it is, and that the point will be reached
And then, imagine those people will sit together, and choose which paths have the best value, and each group that agrees on one of them will start walking the path. Little is beyond the reach of power will and careful reasoning. We could be looking on a completely different world in a just a few decades if we start thinking of the problems of the world as a whole, choosing in-between paths and not problems, and useng our biggest strength – that there are others who also aspire for effective altruism, and understand the concept of the Litany of Gendlin(1).
Thoughts?
(1) https://wiki.lesswrong.com/wiki/Litany_of_Gendlin