Keynote Address by John Seely Brown at Pardee RAND Commencement 2018
Pardee RAND Graduate School awarded John Seely Brown an honorary degree at the 2018 Commencement ceremony. In return, he honored Pardee RAND graduates and the Commencement audience with the following wise words:
Thank you. Thank you. Heaven knows, after the prior two speeches, I'm kind of breathless myself. However, let me say something simple. Good morning.
You're graduating at amazing, amazing times. You've been exposed to some of the most important thinking of our time. You have had the opportunity to intersect with the kind of edge thinking that drives innovation in public policy. You have worked with powerful tools in the policy domain. Some of them, as we heard, were invented here at RAND. Tools that in fact help us better understand extremely complicated situations, working with data sets to make them safer, healthier and more educated by analyzing those datasets correctly. Said simply, the world needs, the world needs the skills that you have honed here ,now more than ever.
But it also needs you to be a passionate explorer to probe, to learn, to reframe, to communicate effectively, so we can collectively meet the challenges confronting us in this increasingly complex world. It's a world that is being driven by constant technological disruptions of a kind that unlike anything we have seen before, but it is also one in which diverse social systems are shifting and reframing. They are changing in kind and in operation, in dynamic and uncertain ways, both through these technologies and because of these technologies.
We've all heard about the narratives of the incredible pace of change that we're all caught up by. I'm gonna step back a bit though and to try to open up a space of possibilities that's a bit different from that classical narrative. The ability might go on what you said to begin with, and also you, Susan [Marquis]. Dave Weinberger, the co-director of the Harvard Innovation Laboratory in his book Too Big to Know characterizes it this way:
"We used to know how to know. We got our answers from books or experts. We nailed down the facts and moved on. We even had canons. But the internet age, knowledge has moved on to the networks. There's more knowledge than ever, but it's different. Topics have no boundaries and nobody agrees on anything."
The complete title of this delightful book, Too Big to Know, is Re-thinking Knowledge Now That Facts Are Not Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room. And yes, this was actually published in 2011, and written two years before that. So we have long-term problems that are immersed around us.
I also want to kind of briefly reference Joshua Cooper Ramo, the vice-chairman and co-chief executive of Kissinger Associates, and the author of The Seventh Sense. The seventh sense is the ability to look at any object and see or imagine the way in which it is changed by connection or today, he might be saying, hyperconnected, whether you are commanding an army, running a Fortune 500 company, planning a great work of art, or thinking about your child's education. The world's biggest problems are basically hyperconnected, making them complex, volatile, uncertain, contingent and highly ambiguous. A small change halfway around the world can propagate nearly instantly across our networks, affecting us in surprising ways.
Situational analysis and awareness is a lot more difficult these days. But now, all of these of us here realize that complex problems are more than just complicated problems. They are completely different, completely different class, and maybe even a different species of problems. Often categorized as wicked problems, one finds that as soon as you touch the problem, it morphs. They technically cannot be solved in any traditional sense because they resist solutions that one designs and implements based on good analysis and decision at the moment of time. The Catch-22, the Catch-22 of wicked problems is that one cannot learn about the problem without probing it or trying solutions. But every probe, every solution you try, they have lasting unintended consequences that are likely to swamp and spawn new complex problems. This is a new class of problems.
Now, add the accelerated pace of change on nearly everything around us and we have what my colleague and co-conspirator here, Ann Pendleton-Jullian, astutely refers to as you refer to it, Michael, as a white water world, a world that's rapidly changing, hyperconnected and radically contingent. Operating this white water world requires a virtuosity perhaps more akin to being a white water kayaker. Indeed, those of us who have done white water kayaking will quickly learn the importance of reading context, reading the currents and disturbances around you, interpreting the flows for what they reveal about what lies beneath the surface and leveraging the currents and disturbances and flows for amplified action. Needless to say, it's not hard to see how this applies more generally to the kinds of policy issues we now find ourselves constantly immersed in.
But what other meta skills and dispositions might now be more important than ever in this white water world? I would say there is one, a deep willingness to learn new ways, new ways to read the world and new ways to work with it. I think it is becoming an entrepreneurial learner, which is not the same as becoming an entrepreneur, but rather someone who has evolved the disposition, the disposition that is always questing, connecting, probing, is deeply curious and listening to others, is always learning with and from others, is reading context as much as content, reading context as much as content, is continuously learning from interacting with the world, almost as if in conversation with the world itself, and is finally willing to reflect on performance alone and with others such as becoming a reflective practitioner.
Yes, you need to continue to evolve your own skills, but you also need to develop skills to connect significantly with others, both inside and outside your own silos, work groups, tribes and organizations. And perhaps, just perhaps, now more than ever, you will find that it's essential to develop what Ann calls a polymathic curiosity as you heard her say yesterday. A polymath is a person whose expertise spans a significant number of different subject areas, not shallowly, but at depth. A polymathic curiosity is about having an intense curiosity of an insider in the fields that you are not of your own training.
It also helps to learn how to listen deeply, to listen deeply within, and across your own areas of expertise, across your own areas of expertise. This will be the new coin of the realm for anyone who is confronted with complex, not complicated, complex problems. But to be good at this, one must have developed not just a skill, but also the disposition of being, of being a generous listener and a generative listener, listening across multiple kinds of disciplinary and cultural boundaries, and capable of working with the constructs you hear. I will argue that cultivating such a disposition will prepare you to productively encounter radically novel and unknown situations. And to view these encounters, by the way, as adventurous. Ones that amplify your own sense of agency.
Of course, most of the above is not something one learns primarily in the classroom, but rather in the world itself. You though have already experienced some of this through your OJT. But that is just the tip of the sphere. Might there be new ways to learn what might almost be called cognition in the wild, cognition in the wild? A kind of situated learning-in-action, expanding your muscles of imagination in order to engage with contexts in a way that gets to a deeper understanding of what affects and influences them. That is, to interrogate context in a manner much like Sherlock Holmes, with deep analyses of the facts at hand, plus good deductive and inductive reasoning about those facts.
But, but where Holmes breaks new ground is insisting, is insisting that the facts never really all there and so one must engage in abductive reasoning. One must ask not only, "What do I see?" but "What am I not seeing and why am I not seeing it?" Abductive — abduction requires imagination. Not just the creative arts kind, but the kind associated with empathy, what questions one would ask if they imagine themselves in the shoes and situations of another. Or if you're not hooked on Sherlock Holmes, consider what great historians do, or perhaps consider RAND's famous Herman Kahn, Thinking the Unthinkable. But by now you must be wondering, come on John, how can I keep developing better ways of sense-making and interrogating contexts or simply picking up new skills, given that the half life of skills seems to be shrinking to five years or so, and of course, new tools are emerging almost daily?
One approach is developing broad and diverse network of colleagues that provide access, insight and learning opportunities starting obviously with the connections you have made here. But in addition to these new dispositions and meta-skills, we're also on the verge of a new era. A new era in terms of learning and working with a new class of tools, tools that can assist us with learning in action while increasing our own performance. I'm sure all here aware of new forms of artificial intelligence based on deep learning algorithms, the kinds that are capturing so much attention on the news these days. But what is getting less coverage is how these systems might be turned inside out. How do we transform AI to IA, to intelligent augmentation, systems that extend our own human capabilities? And if we get this right, these could in turn lead to a new kind of man-machine virtuosity. What? A man-machine virtuosity that actually enhances our humanness rather than just a more dystopian view of robots replacing us.
In March 2016, I, personally, had a major awakening with the AI program AlphaGo, which beat Lee Sedol, the greatest Go player in the world, four games out of five in Korea. Developed by DeepMind, the success of AlphaGo was unsettling phenomenon, perhaps unequaled in the history of computation. And by those who play Go, its gameplay was both counterintuitive — counterintuitive and surprising, even deemed to be creative by some of the major Go champions in the world. Many of us found this achievement almost beyond belief, starting with me. For me, personally, this actually marked the true beginning of the 21st century. Yes, 2016, not the year 2000. Especially as seen through my own kinds of bizarre technological lens. AlphaGo's stunning victory though, altered my very sense of what now might be possible. In fact, it raised for me an existential question, an existential question about what might man and machine be able to do together, each learning with and from each other. Was there or is there an upper bound on what might be possible here?
Now, I could get carried away and describe how amazing this machine learning system, how it works, because as you might gather it fascinates me. But that is not what I want to cover here today. We can talk about that at the reception if you want. What is interesting, I think, is what we find when we look at a more textured portrait of what actually transpired during the play of these five games between Lee and the AlphaGo machine. The story is skillfully rendered in a stunning documentary called, not surprisingly, AlphaGo. A small team followed at close range the AlphaGo development team over a six-month period. From the first game it played and lost against the 2015 European champion to the final match with the Korean world champion, Lee, who by the way, for many of us is purely a rockstar.
What is most stunning in this documentary are the testimonials and the interviews. From Lee, himself, he says, "I didn't expect it to be like this." Remember, he's just been smeared. "It was unbelievable, unbelievable. After losing three games in a row, I couldn't be happier. I've grown personally through this experience. I will make something out of it with the lessons I have learned. I feel... " And he actually said this, "I feel thankful and feel like I found the reason I play Go. It's been an unforgettable experience."
In interviews, he talks about how playing against the machine rekindled his own passion. It gave him new ideas. In the words of Fan Hui, a European grand champion that DeepMind hired to play an almost uncountable number of games leading up to this to provide some additional insights into how AlphaGo worked, he said:
"When I play with AlphaGo, it shows me something. I feel beautiful. I see the world differently. What is the real thing inside of the Go game, the real thing inside of the Go game, not the machine but the game itself? Maybe it can show humans something we have not discovered. Maybe, maybe it's beautiful."
Cade Metz from the New York Times, [an] editor who was co-present for all these matches, has said this:
"Sedol's humanness, his humanness was expanded after playing this inanimate creation and the hope is that the machine and the technology behind it can leave the same effect with us."
In the two months, by the way, following this match, Lee has won every tournament game he's played, and has not actually lost a single match since. AlphaGo led to a new kind of virtuosity, a man-plus-machine virtuosity. And for both Lee and for Fan, it created a different sense of the inner beauty of the game, probably the most complex game that ever has been in the world, played for over 2000 years. What was so stunning and eye-opening about this documentary was the way that in which the champion Go players saw AlphaGo as beautiful, as beautiful. It's showing them something even more beautiful in the game than they knew so well. This is interesting, counterintuitive and different from much of the fear that seems to pervade the public's relationship to the possibility of AI and how to play out through our futures, but that is not to say that we should not recognize the productive skepticisms. Indeed!
In fact, this month, Foreign Affairs' very interesting article by the past Secretary of State Henry Kissinger, a prior person on this stage, appeared. In this piece, Kissinger says:
"In certain field—pattern recognition, big-data analysis, gaming—AI's capabilities already exceed those of humans. If its computational power continues to compound rapidly, AI may soon be able to optimize situations in which that are at least marginally different, and probably significantly different, from how humans would optimize them. But, at that point, will AI be able to explain, in a way that humans can understand, why its solutions are optimal? Or will AI's decisionmaking surpass the explanatory powers of human language and reason?"
"Through all human history," Kissinger goes on,
"Civilizations have created ways to explain the world around them. In the Middle Ages, religion; in the Enlightenment, reason; in the 19th century, history; in the 20th century, ideology. The most difficult yet important question about the world we're headed is this: What will become of human consciousness (Kissinger asked) if its own explanatory power is surpassed by AI, and societies are no longer able to interpret the world they inhabit in terms that are meaningful to them?"
Kissinger's questions about meaning beautifully dovetail what Josh Cooper Ramo was also saying:
"Many of the technical choices we are about to make will be strikingly political. Who has access to what data? Where is the line between human choice and machine intelligence? Banal technical choices will reverberate, reverberate through the future with the same influence that the Bill of Rights and Magna Carta had. They persist long after they were written down."
So beauty or beast? Or maybe beauty and beast simultaneously. We are in a world of uncharted territory, a white water territory. One that requires virtuosity of us as individuals, and maybe, just maybe, a new kind of man-machine virtuosity. Virtuosity is an interesting word. It's about knowledge and skills, sure, but more than knowledge and skills. It's about the consummate knowledge plus the consummate skills. These provide the grounding of imaginative leaps that find fresh ways to use new techniques and the kinds of things you have learned from improvisation, from experimentation and innovation, that is necessary to work on the kinds of problems that Kissinger was referring to.
The implications of technology in our society are riding the wave of expanding our own humanness. Perhaps, perhaps, maybe now we can create an age of imagination where we can fuse, where we can fuse the arts, humanities, sciences, creating a new kind of alloy, a new kind of alloy having the properties that will differ significantly from each of their individual components. That is, of course, what an alloy does.
Anyway, thank you and please remember, we're counting on you to use skills and imagination to help unpack the complex public policy issues that surround us and possibly may even define us. Thank you.