"If we're going to get science policy right, it's really important for us to study the economic benefit of open access and not accept the arguments of incumbents. Existing media companies claim that they need ever stronger and longer copyright protection and new, draconian laws to protect them, and meanwhile, new free ecosystems, like the Web, have actually led to enormous wealth creation and enormous new opportunities for social value. And yes, they did in fact lead in some cases to the destruction of incumbents, but that's the kind of creative destruction that we should celebrate in the economy. We have to accept that, particularly in the area of science, there's an incredible opportunity for open access to enable new business models."
"One question that fascinated me in the last two years is, can we ever use data to control systems? Could we go as far as, not only describe and quantify and mathematically formulate and perhaps predict the behavior of a system, but could you use this knowledge to be able to control a complex system, to control a social system, to control an economic system?"
"The issue is that when you look at the world from these sorts of institutional lenses, identifying problems becomes relatively easy. Solving them becomes very hard. It's no mystery how you get economic growth. You need to provide opportunities and incentives. But how do you make that political equilibrium? How do you make it so that everybody in society actually agrees and abides by a system that provides those incentives and opportunities even if it's not in their short-term interests? Those are the real challenges and that's exactly the sorts of issues we're seeing in Europe, it's the sorts of issues we're seeing in the United States, it's the sorts of issues we're seeing in Turkey."
"Part of my program of research is to convince people that they should stop distinguishing cultural and biological evolution as separate in that way. We want to think of it all as biological evolution."
"With Big Data we can now begin to actually look at the details of social interaction and how those play out, and are no longer limited to averages like market indices or election results. This is an astounding change. The ability to see the details of the market, of political revolutions, and to be able to predict and control them is definitely a case of Promethean fire—it could be used for good or for ill, and so Big data brings us to interesting times. We're going to end up reinventing what it means to have a human society."
"We have always had this tension of understanding the world, at small spatial scales or individual scales, and large macro scales. In the past when we looked at macro scales, at least when it comes to many social phenomena, we aggregated everything. Our idea of macro is, by an accident of history, a synonym of aggregate, a mass in which everything is added up and in which individuality is lost. What data at high spatial resolution, temporal resolution and typological resolution is allowing us to do, is to see the big picture without losing the individuality inside it."
"One of the fundamental questions here is, is extinction a good thing? Is it "nature's way?" And if it's nature's way, who in the world says anyone should go about changing nature's way? If something was meant to go extinct, then who are we to screw around with it and bring it back? I don't think it's really nature's way. I think that the extinction that we've seen since man is 99.9 percent caused by man."
Think about it this way: previously we thought that our universe was like a spherical balloon. In the new picture, it's like a balloon producing balloons, producing balloons. This is a big fractal. The Greeks were thinking about our universe as an ideal sphere, because this was the best image they had at their disposal. The 20th century idea is a fractal, the beauty of a fractal. Now, you have these fractals. We ask, how many different types of these elements of fractals are there, which are irreducible to each other? And the number will be exponentially large, and in the simplest models it is about 10 to the degree 10, to the degree 10, to the degree 7. It actually may be much more than that, even though nobody can see all of these universes at once.
"These three things—a biological hurricane, computational social science, and the rediscovery of experimentation—are going to change the social sciences in the 21st century. With that change will come, in my judgment, a variety of discoveries and opportunities that offer tremendous prospect for improving the human condition.
It's one thing to say that the way in which we study our object of inquiry, namely humans, is undergoing profound change, as I think it is. The social sciences are indeed changing. But the next question is: is the object of inquiry also undergoing profound change? It's not just how we study it that's changing, which it is. The question is: is the thing itself, our humanity, also changing?"
"A lot of people assume that Semantic Web consists only of the metadata, the data at the top of an article that indicates who it was written by. But no, it's the data. It's the government spending data. It's where the potholes are and where space ships are. It's where cars are. It's where taxis are and it is all the data that makes a map. It's the data that makes all the charts, and it's the data that makes industry run. It's the data that makes governments run. It's not just metadata, and it's not data just sucked from the Web."