Can a better understanding of human intelligence make for smarter machines?
We explored that topic this week with Rafael Reif, president of the Massachusetts Institute of Technology, following the announcement of the MIT Intelligence Quest, an effort to “discover the foundations of human intelligence” to develop better technology, especially artificial intelligence.
Reif has been MIT’s president since 2012. An electrical engineer by training, he has been outspoken in his defense of funding for basic scientific research. He was in Seattle this week to talk with alumni about MIT’s plans for the future of education, research, and innovation. We spoke about all of those topics, plus diversity in the tech industry and Boston’s bid for Amazon HQ2, on this episode of the GeekWire Podcast.
Listen to our full conversation in the player below, and continue reading for edited excerpts. Subscribe to the GeekWire Podcast on Apple Podcasts or wherever you listen.
Bishop: You’ve said the MIT Intelligence Quest will seek to better understand how human intelligence works, in engineering terms, and then take that understanding and figure out how to build wiser and more useful machines to benefit society. Why is this so important to MIT and to you?
Reif: It’s very clear that we have advanced those fields so much, that everything is moving in that direction. AI will be everywhere and will power everything. So, in talking to my colleagues at MIT, I learned not only that quite a few of them are working on understanding human intelligence — it’s the only model we have for intelligence that we can study from — and then many of my colleagues are using machine learning tools to advance their disciplines. But none of them are machine learning experts, they are electrical engineers or material scientists or climate action people. But they’re all using it because they need it to figure out all the massive information in the data they are dealing with.
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So, clearly we needed to do a couple of things: Really power the advance of human intelligence, so that we know what kind of new algorithms we can use in the future. Right now, all the machine learning algorithms we have and those tools are terrific, are very powerful, but are really based on fundamental ideas that we came up with — we collectively — decades ago. We just have to double down on that. We have to replenish the well of ideas on AI and actually replenish the well of talent on AI. So, one point was to advance human intelligence so that we learn how to come up with intelligent machines. That’s one part of the initiative I launched.
And then the other part is: Can we create an interface, a group of people who can figure out how to use those advanced tools and customize them to be used in biology, in medicine, in engineering and so forth. That’s the essence of it. I think the goal is, by doing it that way at MIT, we’re basically doing what society is going to be doing eventually sooner or later — and I think much more sooner than later — and we’re basically creating or educating the people that will power that kind of evolution.
Bishop: There’s a lot of talk about machine learning and artificial intelligence across the tech industry, those are the big buzz words. People are using Alexa and Siri on a daily basis. But how close are we to real breakthroughs in generalized AI? Because that really is the holy grail of this field.
Rafael: Absolutely. As with every kind of breakthrough, that’s hard to predict. A spark of a new idea can happen at any moment. If I were to look at the evolution of these fields, maybe we are a couple of decades away from really coming up with a breakthrough idea, but how to put it together and implement it? So, it’s not here anytime real soon. But there is a fundamental question that is also important: Do we want to build AI tools that replace us, or do we want to build AI tools that understand us and work for us? So, conceptually there is a great deal of work to be done even defining what kind of algorithm we want to put together. The way we view it is: We want to create tools that can predict our behavior, can predict human behavior so that we can play together or work together with a robot, or another machine that does and says and practices exactly what we need them to do. That’s a kind of thinking of AI. So there are different branches of what AI means and how to use it. Of course, generalized AI’s the ultimate goal, but again, to what purpose? That part is a very important question.
Bishop: In a lot of ways, this leverages an interdisciplinary approach, like you can have at MIT, with life sciences and computer science, engineering, all coming together. If the MIT Intelligence Quest succeeds, what will that look like? What will be the outcomes? What are you driving for here ultimately?
Rafael: Well, let me just say, to answer your question … it will succeed. But let me make a point: It’s a new way of thinking. So, take science right now, whether it’s biology or physics or chemistry. The way we think today, we do one experiment at a time in which we work on a particular cell and understand that cell tremendously, or a molecule and understand it tremendously, or an atom. Machine learning tools allow us to do many experiments because we don’t have to worry about a very precise control of how a particular cell behaves and then do the next experiment because we learned something new. We can do a massive number of experiments with a massive number of variables, because we have the tools that can give us the information extracted. But how to design an experiment like that? That is basically a revolutionary way of thinking, of changing the way we think. What I’m trying to accomplish is just basically a paradigm shift in the pace of advancement of science by empowering them using this kind of new tool.
Bishop: Let’s talk a little bit about the political landscape. You’ve been very outspoken on the immigration changes and the threats to scientific funding at the national level. How much of this is bluster from the Trump administration and how much of this is a real issue? Because sometimes it’s hard to know what’s real and what’s not, these days.
Rafael: Well, I don’t know what’s real or not, outside the confines of MIT, but I can tell you what’s real for us and what’s really serious. I think, in a global sphere, everybody understands sports. Everybody understands — what’s the local team, for basketball, the SuperSonics?
Bishop: No, that’s a sore subject, not anymore.
Rafael: OK. But my point is, everyone understands a competition between two great teams.
Rafael: And you have two basketball teams that are great and you put the best five players on the court. Well, we have a major competition worldwide right now. It’s between Team US and Team China, and we just have to prepare our best players for that competition. China is not the enemy, China is a competitor — and in many ways, hopefully they’re be also our collaborator. But, we want to compete and we want to beat them. So, we have to think about putting our best 5 players [on the court]. So what do we do? Well, we need to prepare them. We need to educate them. We need to advance science with them. We need to fund them properly, and we need to have our players compete with the best.
So we need to prepare our domestic players as best we can, and if we have players from other countries who want to play in our team, we want to bring them here and compete with our best teams so we can put the best players on the court. That’s what China is doing. And that’s why I think the issue of immigration is important, the issue of science funding is important. It’s not so much that MIT is needing that. Yes of course we need it, but not for MIT, we need it for the country.
Bishop: Based on what you’ve seen in budgets so far for the National Science Foundation, etc., how real is this threat right now?
Rafael: Well, the threat is real. The threat that we are not going to be able to put our best players on the court — the threat is very high. All the talk about immigration is affecting the ability to attract the best talent. And the best talent is having second thoughts on whether to come to the US. When it comes to science funding — quite frankly, the good news, in my view, is that Congress by and large understands that. At least, they understand the [National Institutes of Health] is important, perhaps NSF as well. I would like them to understand a little broader than that but at least they understand that much.
I think to some extent it looks like people in the White House — some of them have that understanding, some of them do not, so there are internal debates. So, this is an issue that I think is going to affect us in the future if we don’t realize that is the issue. I had a conversation with some high-level members of Congress, and I asked them point blank, “Does Congress see the impact of science funding on the economy?” And the answer was, “No, because there isn’t any.” So, if people in Congress at the level of leadership think that way, then we just have to do our hard work to convince them it’s just the other way around.
Bishop: Gender diversity and ethnic diversity in the engineering field are very important, and I know in particular MIT’s School of Engineering has been making a big push along with other universities out there. What’s the key to getting more women and minorities involved in engineering and technology? This is a huge holy grail problem.
Rafael: It’s a huge issue but frankly, all you need to do is seek them and recruit them. MIT has a reputation of being a place for males. Well, almost half of our undergraduates are women. So, if MIT can attract 46 or 48 percent of undergraduates to be women, everybody can. So it’s just a matter of going out there, looking for them and recruiting them.
Bishop: It’s got to be more complicated than that. How have you done that?
Rafael: Well, the bottom line is to try some things and see how they work. I remember when MIT started —when the numbers started to increase, the perception was, “Look, the MIT males are very focused and the MIT females are broader. So, by bringing in women, we’re gonna just lose the focus and perhaps we’re gonna lose the edge that we have educating our students.” Well, guess what? As women started coming in, what do you think, Todd, who has the higher GPA at MIT, the women or the men?
Bishop: Oh gosh. The women.
Rafael: This is your podcast.
Bishop: The women.
Rafael: The women! Right answer. My point is, when you are not used to it and you just go and accept words of wisdom that come from decades ago, of ignorance, and then you actually try new things, you realize, “Goodness, it’s actually working better.”
Bishop: What about racial diversity? Where are you on that and how can you make strides there?
Rafael: Well, that’s another challenge. We’re doing reasonably well there, as well. If I remember correctly, and maybe I’m off by a little bit, about a quarter of our undergraduates or so are under-represented minorities. In fact, MIT is a place in which a few years ago, the majority became a minority. So, about 25 percent are Hispanics or African Americans, and about 26-27 percent are from Asia, India, or China. So less than 50 percent are what you consider the majority. That line was crossed years ago.
Bishop: Okay. You’re here in Seattle meeting with MIT alums and others to talk about your vision, but this is an interesting spot in part because you’ve got the University of Washington, you’ve got the Allen Institutes of Brain Science and Artificial Intelligence here, founded by the Microsoft co-founder, Paul Allen. To what extent are you collaborating with folks here in the Seattle region on any of these initiatives that you have, whether it’s diversity or science funding or artificial intelligence?
Rafael: Not enough. Not enough. Of course, we’re aware of the Allen Institute and our scientists do work and collaborate and participate in advisory activities, and so forth, and of course, I’m aware of the university here, and the computer science program here is terrific.
Bishop: And it’s a competitor to MIT.
Rafael: It’s a competitor, yeah. Competition makes sense. They want students, we want students. They want the best faculty, we want the best faculty. That’s a fair game. But when we come to looking at something like intelligence and how human intelligence works, that’s a big project and collaboration there is for the best. I applaud efforts like the Allen Institute, I applaud those kinds of activities, but in my view, those activities would work much, much better — and I’m sure the Allen Institute does locally — collaborating with universities.
I think one important point to make, and I’ve been saying this for about 20 years, to everybody who wants to establish their own thing. I haven’t made any progress changing anybody’s mind, but I say the same thing anyway. A university is the only entity that changes its personal 25 percent every year. A quarter of our people graduate and a quarter of our people come in new every year. People that are teaching them are forever young, the institution is forever young. There is no other institution in America — companies, whatever — in which the average age doesn’t go up. It always goes up. Universities’ average age stays the same. And that makes for a very refreshing environment in which new ideas are always there and old ideas are always challenged. So, that’s why universities are great to collaborate with not just with each other but with established institutions like the Allen Institute.
I think what’s happening in the country right now, in many universities also, is that the big tech companies are investing so much money there — and they should — and then the sense is, “Well why should we also play a role there, it’s already done?” And that’s a huge mistake. These tech companies are investing heavily, focusing on products. And they have to do that, and in doing so, they advance the whole field. But the key ideas that will create new kinds of applications and new kinds of ways of thinking, and how to apply it more broadly — not just to a product but to a whole society — I want that concept to be implemented in our campus to show that is going to happen anyway.
Bishop: There’s another interesting institution here in Seattle: Amazon. And of course, they are considering a variety of cities around the country for their second headquarters, including Boston. What role did MIT play in Boston’s Amazon HQ2 bid?
Rafael: Well, I wrote a letter to support that, and we contacted the people on the proposal saying that we are strongly in favor of that. So, Amazon will do what’s best for Amazon. In my humble opinion, it’s great for Amazon to come to Boston. But they will make their own decision.
Bishop: What makes Boston the right fit?
Rafael: Talent. It’s like Seattle. Let’s go back to this basketball game. It’s about players, it’s about talent. And goodness gracious, Boston has a lot of talent graduating every single year, tens of thousands. Some of the best universities in America are there. So, if you want talent to compete, there is plenty there every year.
Bishop: When a lot of people look at robotics and AI and the combination of the two, they worry about jobs. As you look at the initiative you’re working on, how do you address that issue?
Rafael: Well, that’s another great role for universities. We clearly want to advance the science and the technology, in this case. But we also want to advance the understanding of the impact of science and technology on society. In the case of automation, the impact is real, it has happened and will continue to happen. There is lots of talk about the future of work and I slightly disagree with that way of thinking. The future of work makes it sound like, “Will there be any work in the future? We’re gonna be replaced by machines and they think the way we do,” and so forth. I look at it somewhat differently. I look at it more like: “The work of the future,” meaning there will be work, it just will look very different from today. And we need to prepare for that transition. We’re going be announcing a companion study to IQ, which is gonna focus on exactly this topic, the work of the future. It’s important for us to understand the different scenarios for the future and how to prepare our society and the new members of society to handle that transition.
Bishop: Rafael Reif is the president of MIT, he’s here in Seattle this week and he spoke with us at the GeekWire offices in the Fremont neighborhood. Thank you very much for being here.
Rafael: Thank you for having me. I enjoyed it, thank you.
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