I think that it pays to be rationally ignorant. It is an economic fact that the more people specialize, the more they get paid and the chance of making a significant contribution in their particular field increases. You can’t achieve your best in being a doctor if you spend valuable time reading textbooks about Western philosophy or quantum computing instead of reading textbooks about diseases. There is a saying capturing this thought: “jack of all trades and master of none”. Sure, there are some fields such as AI at the intersection of many sciences—however, I doubt that most people on this blog (including me) are capable of handling that much information while producing new results in the field in a reasonable amount of time.
So, instead of reading the intro textbook of each field/science (I bet there are more such fields than anyone can handle in a normal, no-singularity lifespan), the best approach for me is to learn a little about each field in my free time—just enough so that I will not be ignorant to the point of making serious mistakes about the nature of reality, and sufficiently easy on the mind so that I maintain the processing power for the main work: digging as deep as possible into the field of my choice.
So, I disagree with the author and think that Teaching Company courses are more useful than textbooks… except for the textbooks pertaining to your chosen specialty.
There is a real danger in becoming more absorbed with the exploration of rationality and science than with focusing on, and excelling in, your own field. I myself am guilty of this.
I have a gut feeling that there are lots of low-hanging fruit that could be picked by people reading more widely and applying the tools of one discipline into another. For instance, Aubrey de Grey claims that because he had a computer science background, he was able to start contributing new content to biology after studying for the field for only a very short time. There might be simple, obvious ways of expanding a field by bringing in new tools of analysis from another field, but none of this happens because most people only specialize in their own field.
But some years back, reading an interesting article by Akerlof and Yellin on why changes that should have reduced the number of children born to unmarried mothers had been accompanied instead by a sharp increase, I was struck by the fact that they had used game theory to make an argument that could have been presented equally well, perhaps more clearly, with supply and demand curves. Their analysis was simply an application of the theory of joint products—sexual pleasure and babies in a world without reliable contraception or readily available abortion. Add in those technologies, making the products no longer joint, and the outcome changes, making some women who want babies unable to find husbands to help support them.
Assume, for the moment, that I am right, that both economics in the journals and economics in the classroom emphasize mathematics well past the point where it no longer contributes much to the economics. Why?
The answer, I suspect, takes us back to Ricardo’s distinction between the intensive and extensive margins of cultivation. Expanding production on the intensive margin means getting more grain out of land already cultivated, expanding it on the extensive margin means getting more grain by bringing new land into cultivation.
In economics, the intensive margin means writing new articles on subjects that smart people have been writing articles about for most of the past century—new enough, at least, to get published. One way of doing it, assuming you don’t have some new and interesting economic idea, is to apply a new tool, some recently developed mathematical approach,. It has not been done before, that tool not having existed before, so with luck you can get published.
The extensive margin is the application of the existing tools of economics, and mathematics where needed, to new subjects. Examples include public choice theory, law and economics, and, somewhat more recently, behavioral economics. The same thing can be done on a smaller scale if you happen to think of something new that is relevant to more conventional topics. I have considerable disagreements with Robert Frank, some exposed in exchanges between us on this blog a while back. But when, in Choosing the Right Pond, he showed how the fact that relative as well as absolute outcomes matter to people could be incorporated into conventional price theory, he really was working new ground and, in the process, teaching the rest of us something interesting.
My conclusion is that, if you want to do interesting economics, your best bet is probably to work on the extensive margin—better yet, if sufficiently clever and lucky, to extend it.
Working on the intensive margin seems to me to be what happens if you specialize too deeply in just one field or two (economics and math in this example), while work on the extensive margin requires you to read widely or otherwise become familiar of new areas to which your standard tools to be applied to.
The saying actually goes ‘jack of all trades and a master of none, though oft better than a master of one’.
There are quite a few insights and improvements that are obvious with cross-domain expertise, and much of the new developments nowadays pretty much are merging of two or more knowledge domains—bioinformatics as a single, but not nearly only example. Computational linguistics, for example—there are quite a few treatises on semantics written by linguists that would be insightful and new for computer science guys handling also non-linguistic knowledge/semantics projects.
I think that it pays to be rationally ignorant. It is an economic fact that the more people specialize, the more they get paid and the chance of making a significant contribution in their particular field increases. You can’t achieve your best in being a doctor if you spend valuable time reading textbooks about Western philosophy or quantum computing instead of reading textbooks about diseases. There is a saying capturing this thought: “jack of all trades and master of none”. Sure, there are some fields such as AI at the intersection of many sciences—however, I doubt that most people on this blog (including me) are capable of handling that much information while producing new results in the field in a reasonable amount of time.
So, instead of reading the intro textbook of each field/science (I bet there are more such fields than anyone can handle in a normal, no-singularity lifespan), the best approach for me is to learn a little about each field in my free time—just enough so that I will not be ignorant to the point of making serious mistakes about the nature of reality, and sufficiently easy on the mind so that I maintain the processing power for the main work: digging as deep as possible into the field of my choice.
So, I disagree with the author and think that Teaching Company courses are more useful than textbooks… except for the textbooks pertaining to your chosen specialty.
There is a real danger in becoming more absorbed with the exploration of rationality and science than with focusing on, and excelling in, your own field. I myself am guilty of this.
I have a gut feeling that there are lots of low-hanging fruit that could be picked by people reading more widely and applying the tools of one discipline into another. For instance, Aubrey de Grey claims that because he had a computer science background, he was able to start contributing new content to biology after studying for the field for only a very short time. There might be simple, obvious ways of expanding a field by bringing in new tools of analysis from another field, but none of this happens because most people only specialize in their own field.
I’m also reminded of this discussion:
Working on the intensive margin seems to me to be what happens if you specialize too deeply in just one field or two (economics and math in this example), while work on the extensive margin requires you to read widely or otherwise become familiar of new areas to which your standard tools to be applied to.
The saying actually goes ‘jack of all trades and a master of none, though oft better than a master of one’.
There are quite a few insights and improvements that are obvious with cross-domain expertise, and much of the new developments nowadays pretty much are merging of two or more knowledge domains—bioinformatics as a single, but not nearly only example. Computational linguistics, for example—there are quite a few treatises on semantics written by linguists that would be insightful and new for computer science guys handling also non-linguistic knowledge/semantics projects.