Sometimes you think you understand something, and when you try to explain it to somebody else, you realize that maybe you gained some new insight that you didn't have before. Maybe you realize you didn't understand it as well as you thought you did. What I think is interesting about this process is that it’s a process of learning by thinking. When you're explaining to yourself or to somebody else without them providing feedback, insofar as you gain new insight or understanding, it isn't driven by that new information that they've provided. In some way, you've rearranged what was already in your head in order to get new insight.

The process of trying to explain to yourself is a lot like a thought experiment in science. For the most part, the way that science progresses is by going out, conducting experiments, getting new empirical data, and so on. But occasionally in the history of science, there've been these important episodes—Galileo, Einstein, and so on—where somebody will get some genuinely new insight from engaging in a thought experiment. 

TANIA LOMBROZO is a professor of psychology at the University of California, Berkeley, as well as an affiliate of the Department of Philosophy and a member of the Institute for Cognitive and Brain Sciences. She is a contributor to Psychology Today and the NPR blog 13.7: Cosmos and Culture. Tania Lombrozo's Edge Bio page

20 years: Online platform Edge.org
Where Avant-Garde Thinking Reflects The Present
By Tobias Sedlmaier 6.30.2017

The online platform Edge has been looking for the big questions for twenty years - and for the even bigger answers of life. A critical appraisal.

Internet Presence of Edge (photo: screenshot)

In the beginning is the question. Born out of restless nights and ingenious inspirations, it is examined in cold daylight, perhaps focused more precisely, and sent out by its ingenious creators into the ignorant world.

What sounds like a diffusely romantic myth of origin is in fact the recurrent practice of finding Edge’s Annual Question. On this online platform, major contemporary (mostly American) scientists and a selection of trendsetters have been formulating answers to more or less urgent questions of our time for twenty years.

How does the world work?

These can be very vague, for example: What Now? Or they can be leading questions: What Scientific Idea Is Ready for Retirement? Almost always the notion of big ideas—either brilliant or dangerous ones—resonates here; and of course, life, the internet, and all the other themes come in.

The answers, which are first published on the website, later in book form, can be long essays with examples and formulas that run five print pages. Or they are as aphoristic as Brian Eno's response about the value of the Internet:  "The great promise of the Internet was that more information would automatically yield better decisions. The great disappointment is that more information actually yields more possibilities to confirm what you already believed anyway.“

Master of Ceremonies of this sophisticated debate forum is John Brockman, author and literary agent, who is called a giant by some. The industrious intellectual impresario has himself written a handful of books, edited around fifty more and performed in an inter-disciplinary  program of avant-garde events with John Cage and Jorge Luis Borges in New York. He was also a Godfather for the think tanks "Reality Club" as well as Edge.

At a moment in history when borders are erected more quickly than torn down, you can imagine the larger than life Brockman with his characteristic wide-brimmed hat as an iconoclastic breaker of barriers. He is equally at home in the role of the business-minded entrepreneur as in the role of the theorist well aware of the sensitive changes in the Zeitgeist, oscillating between Andy Warhol and Norbert Wiener, at the intersection of art and cybernetics.

We're now accumulating data at an incredible rate. I mentioned electron microscopy to study the ribosome—each experiment generates several terabytes of data, which is then massaged, analyzed, and reduced, and finally you get a structure. At least in this data analysis, we believe we know what's happening. We know what the programs are doing, we know what the algorithms are, we know how they come up with the result, and so we feel that intellectually we understand the result. What is now happening in a lot of fields is that you have machine learning, where computers are essentially taught to recognize patterns with deep neural networks. They're formulating rules based on patterns. There are are statistical algorithms that allow them to give weights to various things, and eventually they come up with conclusions.

When they come up with these conclusions, we have no idea how; we just know the general process. If there's a relationship, we don't understand that relationship in the same way that we would if we came up with it ourselves or came up with it based on an intellectual algorithm. So we're in a situation where we're asking, how do we understand results that come from this analysis? This is going to happen more and more as datasets get bigger, as we have genome-wide studies, population studies, and all sorts of things.

We're at the threshold of a new age of structural biology, where these things that everybody thought were too difficult and would take decades and decades, are all cracking. Now we're coming to pieces of the cell. The real advance is that you're going to be able to look at all these machines and large molecular complexes inside the cell. It will tell you detailed molecular organization of the cell. That's going to be a big leap, to go from molecules to cells and how cells work.

In almost every disease, there's a fundamental process that's causing the disease, either a breakdown of a process, or a hijacking of a process, or a deregulation of a process. Understanding these processes in the cell in molecular terms will give us all kinds of ways to treat disease. They'll give us new targets for drugs. They'll give us genetic understanding. The impact on medicine is going to be quite profound over the long-term.

VENKATRAMAN "VENKI" RAMAKRISHNAN is a Nobel Prize-winning biologist whose many scientific contributions include his work on the atomic structure of the ribosome. He is Group Leader and Former Deputy Director of the MRC Laboratory of Molecular Biology in Cambridge, and the current President of the Royal Society. Venki Ramakrishnan's Edge Bio Page