Source: Ed Boyden, Oct 2019
Huffington Post, Sep 2016
Synthesize new ideas constantly.
Never read passively. Annotate, model, think, and synthesize while you read, even when you’re reading what you conceive to be introductory stuff.
That way, you will always aim towards understanding things at a resolution fine enough for you to be creative
we don’t actually have theories — detailed knowledge — enough to make predictive, interesting models, for example, of how we form emotions, of how we make decisions.
… questions about attention-focusing drugs like Ritalin or Adderall. Maybe they make people more focused, but are you sacrificing some of the wandering and creativity that might exist in the brain and be very important for not only personal productivity but the future of humanity?
I think one of the things that I really love about the space of ecological diversity is, if you think of brains as computing things, then ecological diversity might provide many ways of computing the same thing but in different ways that actually yield interesting computational insights or aesthetic outcomes.
I think architecture is very important. I find architecture to be very inspiring for scientific ideas.
My group started at the MIT Media Lab, and now we have half our group over here in the MIT McGovern Institute, but I used to wander the halls of campus late at night to just look at stuff, the posters in the hallway. I get inspiration by trying to connect dots from different fields or disciplines or even entirely separate, unconnected topics. I find a lot of productivity from inspirational environments and connecting dots between random things.
COWEN: Now, you were first hired here by the Media Lab, is that correct?
BOYDEN: I was.
COWEN: They were a different ecosystem, and they saw some reason to hire you, where other groups didn’t see the same reason.
BOYDEN: Yeah. I was writing up these faculty applications to propose to set up a full-time neurotechnology group — let’s control the brain, let’s map the brain. At the time, the majority of the places that I applied to for faculty jobs actually turned me down.
So I went to the Media Lab to talk to people there. I’d been an undergrad researcher there. That’s when I was doing work on quantum computing, for example. It was just sheer dumb luck. They had a job opening that they couldn’t fill, and they said, “Why don’t you apply?”
COWEN: A job opening for what?
BOYDEN: I can’t recall the details. It might have been a professor of education or something. I forget what it was. But they said, “You know what? We’re the Media Lab. Maybe our new mission is to hire misfits.”
It’s a great place for people between one field and another where there’s sort of some space. But you know what? It could be an entire new discipline. Now, flash forward 12 years later, we actually started a center for neuroengineering here at MIT that I co-direct.
I think I learn more from individuals and their variability than from categories of people. For example, in our group at MIT, I have two PhD students. Neither finished college, actually. I can’t think of any other neuroscience groups on Earth where that’s true.
COWEN: And you hired them.
BOYDEN: I did, yeah.
COWEN: Knowing they didn’t finish college. And that was a plus? Or, “I’ll hire them in spite of this”?
BOYDEN: Well, one of them had been a Thiel fellow and then decided that it could be good to have an ecosystem in academia to support a long-term biotechnology play, and it’s hard to do biotechnology all by yourself. The other was a college dropout who was working as a computer tech support person next door, and both of them are now leading very independent projects.
Again, I try to look more at the individual, and I try to get to know people over a long period of time to learn what they’re good at and how they can maybe make a contribution based upon their unique experience. That’s different from what people have done traditionally.
BOYDEN: I think there’s so much crosstalk nowadays. I read a statistic that 40 percent of the professors at MIT trained at one point in their career at Stanford, Harvard, or MIT. So there’s a lot of crosstalk that goes back and forth. I think one of the themes in science is that you end up learning different things and bringing multiple things to bear.
COWEN: How should we improve the funding of science in this country?
BOYDEN: I like to look at the history of science to learn about its future, and one thing I’ve learned a lot over the last couple years — and it’s even happened to me — is that it’s really hard to fund pioneering ideas.
The third thing I would do is I would go looking for trouble. I would go looking for serendipity.
One idea is, how do we find the diamonds in the rough, the big ideas but they’re kind of hidden in plain sight? I think we see this a lot. Machine learning, deep learning, is one of the hot topics of our time, but a lot of the math was worked out decades ago — backpropagation, for example, in the 1980s and 1990s. What has changed since then is, no doubt, some improvements in the mathematics, but largely, I think we’d all agree, better compute power and a lot more data.
So how could we find the treasure that’s hiding in plain sight? One of the ideas is to have sort of a SWAT team of people who go around looking for how to connect the dots all day long in these serendipitous ways.
COWEN: Does that mean fewer committees and more individuals?
BOYDEN: Or maybe individuals that can dynamically bring together committees. “Hey, you’re a yogurt scientist that’s curious about this weird CRISPR molecule you just found. Here’s some bioinformaticists who are looking to find patterns. Here’s some protein engineers who love — ”
COWEN: But should the evaluators be fewer committees and more individuals? The people doing the work will always be groups, but committees, arguably, are more conservative. Should we have people with more dukedoms and fiefdoms? They just hand out money based on what they think?
BOYDEN: A committee of people who have multiple non-overlapping domains of knowledge can be quite productive.
But in economics and in other fields, it also seems like people are trying to make better maps of things and how they interact.
BOYDEN: One way to think of it is that, if a scientific topic is really popular and everybody’s doing it, then I don’t need to be part of that. What’s the benefit of being the 100,000th person working on something?
So I read a lot of old papers. I read a lot of things that might be forgotten because I think that there’s a lot of treasure hiding in plain sight. As we discussed earlier, optogenetics and expansion microscopy both begin from papers from other fields, some of which are quite old and which mostly had been ignored by other people.
I sometimes practice what I call failure rebooting. We tried something, or somebody else tried something, and it didn’t work. But you know what?
Something happened that made the world different. Maybe somebody found a new gene. Maybe computers are faster. Maybe some other discovery from left field has changed how we think about things. And you know what? That old failed idea might be ready for prime time.
With optogenetics, people were trying to control brain cells with light going back to 1971. I was actually reading some earlier papers. There were people playing around with controlling brain cells with light going back to the 1940s. What is different? Well, this class of molecules that we put into neurons hadn’t been discovered yet.
COWEN: The same is true in economics, I think. Most of behavioral economics you find in Adam Smith and Pigou, who are centuries old.
BOYDEN: Wow. I almost think search engines like Google often are trying to look at the most popular things, and to advance science, what we almost need is a search engine for the most important unpopular things.
COWEN: Last question. As a researcher, what could and would you do with more money?
BOYDEN: Well, I’m always looking for new serendipitous things, connecting the dots between different fields. These ideas always seem a bit crazy and are hard to get funded. I see that both in my group but also in many other groups.
I think if I was given a pile of money right now, what I would like to do is to find a way — not just in our group but across many groups — to try to find those unfundable projects where, number one, if we think about the logic of it, “Hey, there’s a non-zero chance it could be revolutionary.”
Number two, we can really, in a finite amount of time, test the idea. And if it works, we can dynamically allocate more money to it. But if it doesn’t work, then we can de-allocate money to it.
I would like to go out and treasure hunt. Let’s look at the old literature. Let’s look at people who might be on the fringes of science, but they don’t have the right connections, like the people who I talked about earlier. They’re not quite in the right place to achieve the rapid scale-up of the project. But by connecting the dots between people and topics, you know what? We could design an amazing project together.