Roll the Bones! #15: Replicator
In the which I argue with myself about academia despite not being an academic
Greetings from Roll the Bones! Here we muse about complexity, learning, epistemology, accomplishing goals in complex environments, and whatever else I might be in the mood to discuss.
One thing I want to drive home is that life is not a game. The only simple, widely-understandable rules it follows are given by God Himself. In all other aspects, things are often more complex than they appear.
This Week’s Links
This week I’ve been thinking some more about research, academia, and independence. I invite you to discuss it with me.
There are no affiliate links here, just things I’ve been reading. None of the authors have any idea their work is about to be featured and they haven’t paid me a cent.
Science as Amateur Software Development
I like Richard McElreath. He’s a thoughtful guy. In this talk addressed to Max Planck scientists, he talks about the reproducibility of experiments. He does so out of a love for figuring out how much we can infer from things we observe (he is a statistician at heart) and with an eye critical of poor experimental practice.
My thoughts:
It’s true that software engineering figured out how to merge the contributions of multiple participants into complex projects a while ago. It’s also true that software engineering figured out how to track changes, versions, and sources for things a while ago - it’s necessary if you want to re-build, re-deploy, or re-use code. Thus, the premise (that Software Development is “professional” in this regard) is fair.
Those who are playing around with ideas, experimenting, and investigating often do so in an ad-hoc way. They are exploring, after all, not producing. Unfortunately, this means many scientists 1) don’t have their code/data anymore 2) can’t remember which versions of code/data they used for their studies 3) are ashamed to share their code/data with others because it would reflect poorly on them.
From what I can tell, becoming a researcher involves a lot of skills beyond writing papers, asking interesting questions, and being an expert in a given subject matter. However, much of that seems to be woefully neglected by the processes that mint new researchers. We have poor (and often unwilling) teachers, sloppy and meaningless statistics, and an almost complete inability to perform an experiment more than once.
The good news is that there is a ton of low hanging fruit for those willing to put in the effort. The other good news is that you don’t need to be in academia to do research if you have other means.
On The Use of a Life
There are some who believe the “greatest” minds should all be sent to the academy to work on the “hardest problems” for society. Colin Percival, a computer scientist and the creator of TarSnap, feels differently. In this post, he describes one example of how one can make meaningful contributions to society without taking the scientific or business world by storm.
My thoughts:
“Is our society structured in a way which encourages people to make less than the greatest contribution they could?” I’m not sure I see the point of such a question. “Is the potential of every member of our society optimized?” Of course not. We live in a world of finite resources and imperfect people. Do what you can with what you have and try to help others. Reaching an “optimum” doesn’t enter into it so long as there is free will.
“Academia is a lousy place to do novel research. […] My supervisor cautioned me of the risks of doing work which was overly novel as a young academic: Committees don't know what to make of you, and they don't have any reputational prior to fall back upon.” This is a sentiment I’ve seen crop up repeatedly; one that my limited experience in academic research agrees with. The risks necessary for serendipity are not hedged. Consistent mediocrity is preferred over long-term success. It’s easier to manage predictable things and people, after all.
How would you encourage novel research? How would you do so without involving a university? It’s been done before. Can we bring that back en masse?
Robotic Manipulation
If you wanted to start learning about robotic manipulation without shelling out time and money at a university, you could do worse than these notes from a MIT course. Take a look at the preface to get a sense for what is offered.
My thoughts:
I’ve heard people say you can replace a PhD “for the price of a library card”. While that’s obviously an aphorism, resources like this are absolutely necessary to make such an approach work.
Robots are one of the places where theory meets reality. Your ideas don’t work unless they work in physical space. I think it’s an especially good field for challenging the effectiveness of learning algorithms - can they handle the noise and generalization demanded by robotics applications?
“Finally, it feels that the time is ripe for robotic manipulation to have a real and dramatic impact in the world, in fields from logistics to home robots”. Experts often think this about their work whether it’s true or not. In this case, I feel the author may be right.
What will blindside roboticists, if they do not already think in terms of systems, is 1) the need for adaptability in the face of uncertain and changing environments and 2) the need to cope with much higher complexity than traditional applications.
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