To improve the ability to avoid cognitive biases, I recommend [Charlie Munger’s multiple mental models which are discussed somewhat here. My own approach (without studies to back it up of course) is heavy on looking at things in multiple different ways, and sort of keeping in mind salient points of each. The idea here is that the map is not the territory, some maps may be very good at showing you some things about the real territory, and having multiple different maps of the same territory at least gives you some good diversity of interesting features to consider.
In some sense, the multiple maps approach is opposite to the list of biases approach. Multiple maps adds to the list of things you may know about something. A list of biases serves to remove things from the list of things you may know as you identify some of them with some of the biases on your list.
Of course doing both (multiple maps AND checking things against a list of biases) is a multiple maps kind of approach: the list of biases is just another map.
My own approach (without studies to back it up of course) is heavy on looking at things in multiple different ways, and sort of keeping in mind salient points of each
Multiple maps adds to the list of things you may know about something
Why do you want to have a list of things that you know about something? Seems to me like collecting facts (“things you know”) about just about any topic is easy and that the tricky part is integrating into a decision or probability estimate them.
Why do you want to have a list of things that you know about something? Seems to me like collecting facts (“things you know”) about just about any topic is easy and that the tricky part is integrating into a decision or probability estimate them.
Because the “truth” of the things I “know” about something is graded on a curve. If I look at a company purely as a physicist I may notice that their chief scientist is smart and their technological ideas are sound. As a physicist I would think this company a good investment.
But to be good investment, the physics has to be right AND the management has to be able to hire the right people and get them to do useful things, AND the product they are building has to be something of interest to customers AND the product has to be marketed in such a way that potential customers see it as something they want AND the company has to bring all this to fruition before they run out of money.
If I look at it ONLY as a physicist I am very likely to estimate probabilities incorrectly. With only the brilliance of their ideas and scientists in my mind, I am likely to “anchor” on these, implicitly assuming every other factor somehow doesn’t matter as much as the one I bother to study.
If I look at it in multiple ways, if there is something that really is more important I am much more likely to discover it, than if I stopped trying to learn more about the something once I had three or four facts and a physicsts model of it. You never want to invest in anything where the pitch starts with “Assume a spherical chicken.”
To improve the ability to avoid cognitive biases, I recommend [Charlie Munger’s multiple mental models which are discussed somewhat here. My own approach (without studies to back it up of course) is heavy on looking at things in multiple different ways, and sort of keeping in mind salient points of each. The idea here is that the map is not the territory, some maps may be very good at showing you some things about the real territory, and having multiple different maps of the same territory at least gives you some good diversity of interesting features to consider.
In some sense, the multiple maps approach is opposite to the list of biases approach. Multiple maps adds to the list of things you may know about something. A list of biases serves to remove things from the list of things you may know as you identify some of them with some of the biases on your list.
Of course doing both (multiple maps AND checking things against a list of biases) is a multiple maps kind of approach: the list of biases is just another map.
Do you adjust for anchoring when you do this?
Why do you want to have a list of things that you know about something? Seems to me like collecting facts (“things you know”) about just about any topic is easy and that the tricky part is integrating into a decision or probability estimate them.
Because the “truth” of the things I “know” about something is graded on a curve. If I look at a company purely as a physicist I may notice that their chief scientist is smart and their technological ideas are sound. As a physicist I would think this company a good investment.
But to be good investment, the physics has to be right AND the management has to be able to hire the right people and get them to do useful things, AND the product they are building has to be something of interest to customers AND the product has to be marketed in such a way that potential customers see it as something they want AND the company has to bring all this to fruition before they run out of money.
If I look at it ONLY as a physicist I am very likely to estimate probabilities incorrectly. With only the brilliance of their ideas and scientists in my mind, I am likely to “anchor” on these, implicitly assuming every other factor somehow doesn’t matter as much as the one I bother to study.
If I look at it in multiple ways, if there is something that really is more important I am much more likely to discover it, than if I stopped trying to learn more about the something once I had three or four facts and a physicsts model of it. You never want to invest in anything where the pitch starts with “Assume a spherical chicken.”
This appears to finish early, or have a stray word at the end. [Now fixed—thanks!]
thanks I edited it.
Thanks for the explanation. I now understand what you were saying and agree that this approach is complementary to the study of cognitive biases.