Research in Academia vs. Industry
The meaning given to the word [computer-related] “research” is not the same in universities (i.e. academia) and in industrial research labs. (Research has yet other meanings, that I won’t touch, for example, “market research.”) The fact that “research” has two meanings is quite subtle, because these two meanings do overlap substantially.
The duality of meanings is most apparent when you see how people from the two environments regard the same piece of work. While I saw people from academia regard a paper as a masterpiece, at the same time people in industry declared it useless. And each party had perfectly valid arguments to their side. How could that be possible?
To reconcile these seemingly contradictory points of view, one has to understand that people in these two camps play two different games, and thus optimize for two different criteria. In academia the reward is tenure, and (perhaps surprisingly) the respect of peers, and the main measure of success seems to be the number of publications (and various awards). In industrial research labs the main reward is having your work translated into a product, and the measures of success are more varied, but include mainly technology transfer (hard to quantify) and patents. What blurs this picture is the fact that there are quite a few people who cross the lines: academics who create companies (i.e., start-ups) or consult for industry, people in labs who publish papers. But in the end, there are two different games that are played here, with the same name, “research”, but with different rewards, and different rules.
There is this famous quote:
Life is a game. Money is how we keep score.
— Ted Turner
I believe that this is pushing the “game” framework a little too far, as I will explain in a minute. But the “game” framework has become really useful for me. Let me give you one more example.
Let’s take software developers. I have met some absolutely brilliant software developers, who can craft some amazing pieces of software, and who have proven that they have a very deep understanding of computers, perhaps much deeper than many people who have stayed much more time in school and gotten a Ph.D. exactly to study the behavior of the machine.
I can imagine how a guy with a Ph.D. can snicker about these developers being just “code monkeys,” who can’t put a paper together, and who don’t know the “related work.” I can also imagine how the coder can snicker about the Ph.D. guy having never produced a piece of code which doesn’t break any time the wind blows. So, who is better?
This is the wrong question. You have to understand that the developer and the graduate student are playing different games. One of them is optimizing for producing software, and the other is optimizing for producing papers. Both of these are really hard and intellectually deep activities. Both of them, when done well, can be very useful for society, and society can pay top dollar for them. You can’t ask one of them to play the other’s game. It would be like asking Tiger Woods to write equations and Einsten to play golf. These are just different games.
That’s why I think that Ted Turner’s quote is not always appropriate: not all people want to play together at the same table.
But I have drifted from my original subject.
Once you understand that academia and industry are different, you can adjust your career accordingly. This has important consequences for the interview style – which should be different in academia and industry, and for managing your career, and even for networking with people from these environments. But I hope to write about some of this stuff in another post.