Good Taste as a Feedback Mechanism

Ira Glass talks about how beginning artists have standards much higher than their actual ability, and how the process of getting good at art is a long, painful period of bridging the gap between your taste and your ability:

All of us who do creative work, we get into it because we have good taste. But there is this gap. For the first couple years you make stuff, it’s just not that good. It’s trying to be good, it has potential, but it’s not. But your taste, the thing that got you into the game, is still killer. And your taste is why your work disappoints you…It is only by going through a volume of work that you will close that gap, and your work will be as good as your ambitions. And I took longer to figure out how to do this than anyone I’ve ever met. It’s gonna take awhile. It’s normal to take awhile. You’ve just gotta fight your way through.

Implicit in this is that good taste helps you eventually become a good artist: by recognizing what good work looks like, you’re able to practice and gradually improve your work until it meets your own standards. On the other hand, if your taste is poor then you’re subject to a much slower feedback loop: at best, you can ask others to look at your work, which is still useful but introduces a substantial amount of delay. And the gap between practice and feedback has an enormous impact on how fast you learn. So poor taste = slow feedback loop = slow learning, while good taste = tight feedback loop = fast learning. This suggests that one of the most important things you can do is continuously cultivate better taste.

This applies to many domains, not just art. Beginning programmers benefit a lot from having a compiler which tells you whether your code will work at all, and more advanced programmers benefit from a sense of elegant code and architectures. Good Mathematicians benefit from the ability to recognize whether their work is correct. Analysts benefit from a host of heuristics that tell them whether a dataset seems plausible, and where to look next. Cooking benefits from literal good taste.

So if you’re new to a domain, one of the best things you can do is develop a sense of what really good work looks like. To teach complex Machine Learning concepts in a simple way, look at Andrew Ng’s videos and Hillary Mason’s presentations. To become a good programmer, read code that’s widely considered elegant–and figure out what makes it good. To become a better public speaker, spend a lot of time watching speakers you admire. Ultimately you need the ability to recognize and critique work that’s substantially better than your own, so you can continuously move towards that standard.

 

Categories: Intelligence, Learning

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