PeterisP comments on The Best Textbooks on Every Subject - Less Wrong

167 Post author: lukeprog 16 January 2011 08:30AM

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Comment author: nykos 17 January 2011 05:42:12PM 5 points [-]

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.

Comment author: PeterisP 18 January 2011 11:25:27PM 1 point [-]

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.