Julian Birkinshaw on Strategic Agility in a World of AI | London Business School

Julian Birkinshaw on Strategic Agility in a World of AI | London Business School

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So. We're not going to be talking about technologies. So much we're. Going to take it for granted that this important. Stuff happening, behind. The scenes in terms of how artificial, intelligence. Is dramatically. Changing the way things can be done we're, going to be talking about almost the social, impact, of, that. Technology, and in. Order to help me with that I asked. Those of you who are coming tonight to. Fill in a little survey and about 80 people did so so interspersed, through my presentation, I'm, going to be sharing you with you some of the results of that survey. So. What. Is artificial intelligence here's. A definition it, is the simulation, of human intelligence. Processes. By machines especially computer. Systems as francois says what. Are they doing the people who are behind this stuff are trying to essentially figure out ways of. Taking. Our jobs away from us trying to find ways of doing the stuff that we do and, doing. It for us using, machines for, good reasons. That I'll get into. What. Did. You think the, 80 of you responded, to that survey think, about. Artificial. Intelligence as a threat, versus. An opportunity. Well. It turns out that you're. An optimistic Bunch right. 11. Percent of you said threat. 89%. Said, opportunity. And it, will not surprise you to note that tonight, I'm gonna have the next half an hour I'm, going to be talking about both sides of that, challenge there are threats there are absolutely. Risks. That the technology, is going to take us to a place we don't particularly, want to go but. There's a huge opportunity as, well and for those of us who. Follow what's happening and look a little bit further into the future I would argue that actually we can kind of get ahead of the curve and we, can use this, technology to, our advantage a. Couple. Of slides just to orient you not everyone in the room really knows that much about artificial, intelligence, I mean, you're reading about it but you're probably still scratching your heads this, image, from hands moravec is a, beautiful, way of capturing, what. Is going on he, pictures, a landscape. Which. Is gradually, where the water level is gradually, rising, and the water level is the, point at which essentially. Everything under the water is done. Better by computers, and everything above the water level is still, but done better by, humans. So you can see Jess Jeff, jeopardy, arithmetic. These, games these, are all things which basically, the computers, are now ahead. Of humans they will win every time, driving. Is a great example, drivings up there as we know autonomous, vehicles, are on the way they're not quite there. Yet but. They are certainly, going to happen within, our lifetimes, but, then you look at the high peaks you look at science, designing. Artificial intelligence writing books these, are the areas. Which we, humans, still have an undeniable. Edge, now. Will we always have that edge you know that is almost a philosophical question it really doesn't something's not something we need to worry about tonight, we do know that the technology is increasing, at exponential, rates and obviously.

That Has scary. Consequences. But. To be more prosaic when you say what is actually, happening, in terms of the world of artificial intelligence and how it's affecting. The world of business today, it. Turns out that actually there's. Not that much really, cool stuff happening, this is an article in Harvard Business Review earlier, this year by Tom Davenport, process. Automation, just making, existing processes. Work more efficiently, that, is actually, about. Half of what's happening, in terms of aai applications. Cognitive. Insights, in, other words you, know using clever, technology, to, for example, pick up on credit card fraud and. That's a big chunk and the, cognitive engagement where, we're actually engaging, with computers, to. Do almost predictive, stuff that, is a small chunk so. If you follow the literature at all you'll know that this is called artificial, narrow, intelligence. We. Figured, out ways of making computers do certain narrow things really. Well they. Can be does that go they can do all sorts of clever, things but. Artificial, general intelligence which. Is computers. Which, can replicate, human. Activities. In the breath that, we have that, is a long way off most people reckon it's a good 20 odd years away artificial. Superintelligence well, that is absolutely, the world of science fiction certainly, not in my lifetime probably, not in the lifetime of anybody here. What. Did the survey, results tell, us about your views, on how AI. Is affecting, us today. Well. I don't know if you're deluded, or whether you're just pragmatic. But the, bottom line is that, 49. Percent of you said, only, between 0, and 25 percent, of my, job could, be done by a computer and another. 44, percent of you said maybe, 25, to, 40 percent and I, think that's, probably not untrue. I mean that would be my kind, of hunch you know you, know even as a professor we all like to think we're a we're, above the fray here we all like to think that our jobs could not be. Robotized. But, of course there's little bits of everything that we do which absolutely, could be and will, be and, I'll give you a couple of examples of that later, so. I then asked you what about the future how, prepared is your organization. And the. Answer is we're. Not prepared at all so, 37. Percent of you said our, people prepared not at, all 41, percent well maybe was somewhat prepared we, don't quite know where. The world is going to go because we're a little bit scared about some other prophecies we've heard and I'll just give you this beautiful example, of a prophecy by. This, chap Ray Kurzweil, some of you've heard of him he's a he's a celebrated. Sort of visionary he, wrote this book called the singularity and the singularity is, essentially. The point in time 20 years from now he reckons, where, artificial intelligence, will have caught up with human.

Intelligence, Because. It's growing at an exponential rate he. Says that information based technologies, will encompass all human. Knowledge and proficiency. Ultimately. Including pattern recognition, powers, problem-solving, and so, on and so forth you, cannot prove that he's wrong right you absolutely cannot prove that. That is an. Incorrect statement and that is. One of the reasons I think why we have to be sanguine, about, the. Opportunity. Here we've got to see it both aspect. As well as opportunity. So. Here, are the two questions that we're, going to spend the rest of the time talking about how. Is AI, changing. The workplace, today. For us as individuals, and more important for the practice of Management I want to make this about the, world of management and leadership and, what. Therefore do we need to do to. Adapt to stay relevant how, do we become agile. Agile, enough, to succeed in this world again. I asked you a survey question and this question was about you, in terms of the, things that you need to focus on as individuals. As your core strengths, which, will enable you to do. Well in a world which, is increasingly, robotized. And automated, and I wasn't in, any way surprised by these results but I was somehow I was, actually kind of assured, in some ways because, what you're saying is that. The. Things that the computers, cannot do at, the moment make. Difficult, judgments, and decisions they. Can't be creative, they don't have empathy they, don't have the capacity to make intuitive, judgments. Those four things together are, the, things that you said actually. Are the, things that are most important, for me as an individual, now whether you are consciously, saying that's, because the computers can't do them for us I don't know but, I think that is exactly the right answer that, is the things, that we need to do as individuals and I've seen many many people. Talking about those, soft, more. Cognitive, more empathetic, skills. That. We need to continue, to accentuate. In. A world of, artificial. Intelligence, but. I want to answer a more difficult question than what, should we, do as individuals the. More difficult question, is what are the implications of, all this for, the practice of management for the, work that we do on what, is management management, is getting work done through, others that's what we all get involved in on a day to day basis. Here. Is a set. Of categories, of what, management, is what, is management about it's about coordinating, things making decisions, it's, about motivating, people it's. About setting objectives and. When I look at what is happening in, the world of artificial intelligence and, I, look at how, it, is affecting, each of those four things I come. To a slightly scary, conclusion. So. Let me just be clear well what I mean by that I'll take you each through each one of those in turn very briefly let's, think about coordinating. Activities. It. Turns out that there are huge. Improvements. In efficiency. In, terms of how coordination, happens this. Means both search costs, as well as coordination costs and even, kind of governance, and, contracting. Costs, you, take a company like an Amazon right if I say to a lexer, sitting on my kitchen table a lexer, order, more dog food I can. Be pretty confident, that 24, hours later, you. Know dog food will arrive at my home. Exactly. As planned, I have, no idea, what steps went between my, voice, command, and that arrival. I'm absolutely certain there, were many many steps involved, some of which were. Controlled, directly, by Amazon, and Amazon's employees, some, of them undoubtedly, involving, third-party. Suppliers and. If you think about the coordination. Intricacies. Of that just, that simple set of transactions. And how, quick it is and how seamless it is the, productivity, improvements, are huge and if you think about how that then plays out on the world those, of you who've ever studied transaction, cost economics will.

Know Full well that, as, soon as transaction, costs go down that. Actually means that we can use market, based relationships. Much more than, we're used to in, terms of what happens in in a firm so, we can actually use subcontracting. And third-party. Relationships, in ways that, were perhaps not as possible before. How. Do we make decisions in organizations, well, this has been much talked about I'm just going to give you one brief, example it, turns out in field after field. Experts. Medical. Experts. Experts. In you name it in the field of wine. Experts. Believe that they are genuinely. Above, the. World. Of. Prediction. And artificial, intelligence, but time after time it turns out that, when you use, the, body of data are amassed for example, in detection. Of cancer and you, put all of this data into a system and you use clever pattern, recognition, software, it. Figures, out ways. Of essentially. Codifying, years. Decades worth of expertise. And, actually, coming up with better, answers there's a beautiful old example, the, wine image here this. Is almost isn't a social, intelligence but it makes the point quite nicely there was a there, was an economist called Ollie Ashe and filter and he. Upset, the entire, wine. Growing region of Bordeaux by. Figuring, out that he could use three. Variables. Essentially. To do with rainfall and sunlight, in. A given year to, predict, the, prices of Bordeaux wines coming, forward much better than the experts could and, of course the experts poo-pooed his his, his analysis, but unfortunately, the analysis was robust. The analysis, was definitively, true because he was then able to show that the algorithm, he created, did, indeed predict. Future. Wine prices, much, better than most of the experts could so. Algorithms, will, often, beat. Heuristics, heuristics, are rules of thumb by, experts, not always and, obviously, we need a combination but in many cases they are beating the experts. Motivation. You. Remember, from, your studies, Frederick. Winslow Taylor, the. Architect. Of scientific. Management time. And motion studies, this is from the 1920s. Well. I'm, a little bit worried because artificial, intelligence, software is, in, fact enabling. A sort, of neo Taylorism. To, emerge in the workplace there are many cases now where. Clever. Software is. Keeping. Track of every. Single movement and every single statement. Made, by people, working in a call center people working, in a factory factory, in call center workers and delivery, drivers. And, uber, drivers, can be controlled, by the computer by. The machine if you like far. Better than before and. I do of course believe that you know as. A machine, is a good servant but a lousy master, but it is absolutely possible in many areas for. Them to control. The law of workers, in in kind of scary ways and then finally, what, about setting objectives our. Computer. Is going to help us in the process of setting objectives and, factories well, I don't, think they will because in fact when, you stop scratching, under, the surface of what, these computers, are doing they're, doing incredibly. Impressive. Things, but. The algorithms, and the deep learning and reinforcement learning, methodologies. They're using are all. About delivering. On, a unitary, objective, often. In a very creative way the famous case of go. Where. You know the world champion, was beaten, by alphago, which is a product. Of deep mind this london-based, AI. Company, in that case was.

Celebrated. Because the, machine came up with a with a move that no one had ever seen before so. You can argue that was a really creative solution, and, it was created but it was very much creative, within a very clear, set, of parameters, about. Winning, the game so, you give a computer or goal it will find ways of getting there but. Humans, are more complicated than that in ways that I think build become clear in a second. So. Are we entering a brave, new workplace, and I think you know what I'm getting. Out there a brave, new workplace meaning a kind of a scary one you, know if we allow. The computer. Technologies. Of today to. Dominate. The way that we think about work we. Don't end up in a very happy place, fortunately. My talk does not end there my, talk I am going to provide you some salvation. And I'm, going to provide it through a. Famous. Departed. Professor, called, Samantha, go Shaw some of you will remember Samantha. So. The question you've got to ask yourself is this what. Is it that firms exist for why do we have companies, in the first place why do we need management in, the first place you, know there's a classical, way of thinking about it I touched on it earlier, it's, called transaction, cost economics theory. Oliver. Williamson Ronald. Coase these. Guys said that a firm literally, is a, nexus. Of contracts. A firm exists, to internalize. And pull, inside one place a whole set of complex transactions, which will be too difficult to. Actually mediate. On a market, basis the. Only reason we have firms not markets, is because. Of high transaction costs and because, that's a very economic. View of the world it's not entirely wrong but it is not a satisfactory view, and I think if we allow ourselves to be seduced by that view we do indeed end up in that scary brave new workplace, that. I just talked about. So. Some months ago shall he was on the faculty here many of you will know a mess him fifteen twenty years he died I think it was thirteen years, ago he hired me he, was very much a mentor to me in terms of how I looked at the world and. He said this transaction. Cost view of the world is wrong it's not wrong it's just completely. Insufficient. Because. He was coming up with what he called him managerial. Theory, of the firm he said a theory, of the firm should actually be something that understands, what value. Managers. Individuals. Humans, create. In, order to, rise above, the. Basics, of transactions. That go on in a firm and so. That the line of thinking that he started, us on, actually. Leads. To are very important, and I think ultimately very, helpful. Conclusion, we. Need the firm and the managers in the firm to do the things markets can't that's what Samantha said and, in. Artificial, intelligence world, that we're moving into what. That means logically, is that the firm's that, succeed will be the ones that really capitalize, on those, unique. Advantages. The, things that. We, can do in firms, through management through, good management that, the markets, cannot. So. Let me just give you a few examples of what I mean by that in, a firm's I said, that computers, are good at doing unitary, goal directed, behavior, do. Firms have unitary, goals no. I mean they just don't that's a shot, that some of you will recognize the triple bottom line firms. Have. Economic. Social, and environmental, goals. Now. They they pursue them to different degrees but. All of those goals exist, you can't say the one single, thing we're going to measure a company, on or indeed lbs for that matter is is. The following there. Was a famous, london-based. Economist, John Kay he had a relationship with other business school years ago here, at this beautiful book it was called obliquity, and. He, had this notion that goals, are best pursued, indirectly. He, said that if you want to get to point a you. Should actually shoot. For point B and the point he was trying to make was, that actually the companies, that deliberately. Give himself a mission or a purpose, or some sort of meaning in terms of what they're doing in they're, trying to you know have an impact as a central impact on the work the way the business happens. In the world those, companies would. Actually, not just hit, those missions but, also be.

Financially. Profitable as an, unintended, consequence. Almost or as a byproduct of their. Mission so. John Kay called. This the oblique effects and I think it's really useful and mind-bending. Way of looking, at the world so. What are the things that firms need, to do in. Order to rise above, the, kind of the the perils, of, artificial. Intelligence you know one things that firms do is that, they deliberately, take, this long term perspective Samantha. Girl said it best he, said firms, have to take resources, out of their first best use and, deliberately. Put them somewhere where, for. A temporary, period they, are not actually, productive you. Can call this research and development you can call it leadership and development training, less. Productive in the short term but invested. Over time leads. To, better outcomes one. Step backwards, two. Steps forward Jeff. Basil said it quite nicely, you, know Amazon is the biggest, you know valley crater on the planet right now alongside, Apple, Jeff. Bezos says you, know you've got to be willing to be misunderstood, we've got to be able to do things which, actually a lot of people don't understand, because. We. Have this, long-term perspective. And we know that if we invent new stuff we, will actually, get to the future before, others. Firms. Also create value, as I touched on through. Purpose. Which enables, discretionary. Effort, discretionary. Effort meaning, getting, more out of the people that work for us and the, LDS community is a great example of trying, to create a purpose, that creates, discretionary, effort one, example would be the Tata Group which i think is fame for this but putting the, group level Tata Sons are putting, a big chunk of their, profits, into. Social, goals, within, the various different communities, that they serve. Another. Thing that firms do, is they create value by. Allowing. Unreasonable. Behavior, now. I am a little, bit cautious about sharing a picture of Elon Musk I, realized. That he's he's, not the world's favorite guy right now and. Yet, in some ways the. Fact that he's not popular almost, makes my point even, stronger because you, know love, him I hate him and a lot of people right now hate him I get I'll give you that but he, has created, huge, opportunities, he has changed, three or four industries, despite, the fact that he's a very difficult person and the. Point I'm trying to make is that you know his unreasonableness. His. Desire, to change the world according, to his point of view is actually one of those things that helps the world to move forward you've got to find a way of ultimately. Harnessing, those, peoples and energies for good but. Ultimately unreasonableness. Here, is one, of the decisive, things that firms do and of course you, know artificial. Intelligence, software. Just. Can't somehow substitute. For that I'll give you a very specific example of what I mean by that those. Of you work in the world of fund management wealth, management well, know that Robo advisors, are coming along Robo advisors, don't just advise.

You On what stocks to buy they actually execute, contracts, nowadays, they literally take your risk, preferences, in your age and so forth and they, will manage your portfolio for, you at a lower price, of course, than a human, are, these Robo advisors, taking over the world of fund management there's, this battle between man, and machine going, on my. Answer is of course there's a place for them but. We've also got to be careful because if all those Robo advisors, are, actually, working with the same algorithms, there, is a real, risk that they just copy each other and that, they end up going. To a place where by definition they're all making exactly the same return, on investment, so, I just loved this article in The Financial Times when it comes to investing, human. Stupidity. Beats. Artificial. Intelligence, and. I think you know what means he's. Saying that actually if you want to beat the market by definition you've got to be a contrarian and, a. Contrarian of course is somebody who deliberately. Intentionally. Kind of goes, in the opposite direction to. That which, the crowd have gone in now, can we imagine a world of contrarian, robots, I mean I guess we can it's. A long way off but, for moment for me at the moment that, is the human touch the, thing that allows us to spot those opportunities. And to, grab them. So. To, summarize this piece and that I've just got a few final thoughts, my. Optimistic. View of the workplace of the future the. Work of management, is the. Following what is it that us that, we rather as managers, and leaders of the, future and of today needs. Of becoming become, even better at first. Of all we've. Got to get better at managing the trade-offs, in coordination. Computers. Are very good at helping us with pieces of the puzzle only we can, make the trade-offs, between, the two in, real time, in. Terms of making decisions, the. Old word judgment, comes back judgment. Is by definition. Something. Which involves, us making, choices. Among. A set of. Incommensurable. Things, we, need to get the algorithmic, support, in terms understanding, what we might do and then, we need to be able to bring a little bit of emotional, conviction, and a bit of decisive, action to, the table to, ensure that those decisions, are the right ones for, this particular moment, in time. In. Terms of motivation, clearly, inspiring, and, generating. That extra, discretionary. Effort is a good part of the story and in. Terms of setting objectives clearly. Purpose, is a, big part so you've heard these terms before don't, get me wrong I'm not trying to say that there's some completely. New thing that we should be doing that. You haven't heard before but. All I'm saying is that these aspects, are the ones which are even more important, given. The changes, that we're seeing in terms of computer-based technologies, in the workplace so. I. Have. A couple of final thoughts just to turn, this into, something a little bit a little bit more practical for you.

Leaders. You. Know we need to play up our individual, creativity, our empathy our intuition. Those human, qualities and we need to then use, those to make the management, work that we do more, effective. What. Does that mean for our role as leaders of others, in other words if our job is to lead teams of people who. Are taking this advice, how. Can we do that job a little bit better. So. There was a study, done, gosh 15 years ago by. Richard, Laird Lord Laird of the London School of Economics and. He studies happiness and. The ask people you know who you happiest spending, time with your. Wife your kids family. Your friends well. It turns out that were happiest with our friends, and. Our parents our spouse and. We. Are the least happy, with. Our boss the, person with whom we would like to spend our time least is the, boss and, we, prefer to spend our time alone than. With our boss. So. You draw, your own conclusions. From, that survey. The. Point I want to make from this is is, the following look, it's hard to be a good boss we all want to do a good job but. The truth is that, it's actually really, difficult it's actually really difficult to, meet the, different demands. Of huge. Numbers of people who are relying on us on a day to day basis, I actually, wrote a book on this a couple of years back called becoming a better boss and. I said, look management, leadership, I mean I'm going to bracket those two terms together today, is. An unnatural. Act it does not come naturally it is something we have to consciously work on and, it's. Difficult because most. Of us you know as we go up through our organizations. You, know we are patted. On the back for delivering, good results, we, like to be seen to be in control we, get promoted when we seem to be in control and, the. Higher we get the, more we've, got to actually unlearn. Those, old tasks, control. Based behaviors, and actually. Move, to a set of behaviors which, are all about liberating. The people around us. And. All the points I made about creativity, and empathy. As a, leader today our, job, is to liberate, those, attributes in, our people, and so. For me there's, this hugely difficult, balancing. Act that we need to, work on as leaders on the one hand a big, chunk of our time has to be spent mentoring. And role modeling, the behaviors, around, creativity and empathy and intuition, that, I've been talking about spending. Time with the, people on our team individually in groups, making, sure that they feel they've got this atmosphere. Of psychological. Safety where they can try new things out things which sometimes, work things which sometimes fail those. Difficult, people that are easy. To sort of get rid of but actually are the unreasonable, ones who shape things those are the ones we have to work doubly, hard with. And. Whilst, doing that we also have. To remember that occasionally, our job is externally. Facing it's, a little bit more decisive, it's. About taking judgments, about opportunities. That we need to capitalize on, now and, actually. Championing. Those things in the external world the reason I've got a picture of Amazon, up here again is that, I know Amazon reasonably, well there may even be some Amazon employees, in the room remember. Amazon is a half a million people nowadays, and yet. Amazon still is holding. On to many of those values, of entrepreneurship. And simplicity. And customer, centricity that, made it a success ten years ago and so they're doing quite a good job of balancing the, nurturing, on the one hand and the, decisive, new business opportunities, on the, other, so. That. Is the, challenge we face as leaders is to get the, right mix between, internal. And external and, the right mix. Of skills to, make sure we get the best out of our people, the. Final, survey, question. That. You filled in was a question, about what. Are those leadership capabilities. That, you will need in the future, and I. Was again happily. Reassured, here because it turns out that when, you filled in these questions I mean I have some silly ones at the bottom what's. Silly but sort of old-fashioned, ones at the bottom about, overseeing. And monitoring, and controlling, but. You of course aimed. For, the ones which. I saw as. The. Intangible. Qualities, of leadership which, I've always been important, but are even more important, to know it now so defining. A sense of direction. Acting. Decisively in periods, of uncertainty, getting. Rid of obstacles helping. Your subordinates, to do their best work and those. Are the top three by quite a long way and, so. There is a point, I just want to finish with which. Is a link, to a famous old statement. From Warren Buffett it's only when the tide goes out that. You discover, who's been swimming naked. You. Know what what, Warren, Buffett meant, was you know in the world of fund management, right, anybody. Can make money when the markets going up at ten or twenty percent a year it's. Only when the market goes down that. You figure out which, fund managers, are actually worth, their salt there's.

Something, In. What he says which has a parallel, to, the challenges, of leadership because. If you just go back to that previous slide you, know we used to be able to hide behind. The old classical. Models. Of leadership management. Leaders. Would control, things they would monitor the behavior their subordinates, they will be the conduits, for the information flow those, are the old skills. Of management, that. In an old world where information did not flow freely we, could use those as a. Way of justifying our existence, nowadays. Of course that is not enough we've. Actually got to be good at the tough stuff the tough stuff at the top the, boss stuff at the bottom occasionally, is useful but we earn, our living as leaders in the, future by, becoming good at the top stuff and that's what Warren Buffett was talking about in the way I see it so essentially, you, know as the, artificial intelligence. Takes. Shape as computed. Technology automates. And simplifies. A lot of the things that are happening that's. When we figure out which, leaders, are as it were swimming, naked in other words which leaders are able to rise above that and do the really valuable stuff and which, leaders are somehow, succumbing, to the, threat, that I talked about earlier. Recently. In the London Business Court review there was a pretty, good article, my opinion about how you. Know implementing, technologies, like AI cetera, in the, workplace should be led from the top down from the CEO level and not necessarily just thrown to your analytics, team, however. In. Certain, cases I would argue that you know some leaders are a, bit, overeager to apply. Technology. And no matter what the cost, work. In real estate and what I see a lot is people throwing prop tech etcetera, etcetera or we're gonna apply a I - you. Know outperform. All our competitors, how. Do you, in. Your opinion. How. Does a company make, sure that you know they're actually using. This technology first. In an appropriate, way in - in a way, that actually meaningful, impact results, in the long term terrific. Question and you've probably heard this expression that you know we we we, overestimate. The short-term impact of technology we underestimate. The long-term impact and there's, this famous hype, cycle I think that gardener created, which basically says that these, new technologies, come along everybody. Grabs hold of them we, get all excited about them we go to conferences, we listen to academics. We we listen to the consultants, and then. At some point there's this inevitable. Kind of tailing off because it hasn't lived up to that short-term hype, so my advice is always look you know we have to have somebody who's keeping their eye on this stuff but. You know it is absolutely as risky, to kind of over invest in these things early as it is to under invest in them you know so blockchain, is a great example right I mean it's part of this same sphere. Of, new technologies. That we're not quite sure how to make sense of you. Know I have not yet seen any, really. Successful, practical, applications. Of blocking, I know there are other prototypes out there now, it doesn't mean that someone shouldn't take a look at them but it does mean that we should be cautious, about throwing. Our entire weight behind them you know we I almost, liken the blockchain revolution. To the the, period, in the 1990s, when the Internet had been invented but.

The World wide web had not if you see what I mean because, there's all this talk about it suddenly. The world wide web enabled. Everyday, people who had no concept, of the technology, to. Actually use this cool technology, and when. We don't understand, how, it, works and we don't need to I'm. Actually thinking the same is true of many of these emerging, technologies we we have to be, conscious of what's happening we have to have a few clever people, monitoring. It closely but. We shouldn't be all running. In that direction because, we can absolutely get distracted from. Our day jobs. So. Among. The industries, you have there on that graph I didn't see business education anywhere or the delivery of yeah, and so you talked, about Rob advisers in fund management and you, know what's, your view of where, you're interested might be going it's about you know it's. A yeah. No. Really. Detecting. Patterns and coming up with theories you know and, we we, just got a call from the Financial Times yesterday saying they, want to know what the really sexy, stuff happening in business schools are and they wanted examples, of applications. Of AI and virtual reality augmented, reality, in. The classroom, you, know and we were sorry to disappoint, because you, know just. As I said you know I I think that we've got to be on the, case but. It is possible to jump too, soon now, I happen, to have as one of my jobs is heading. Up our digital. Learning activities, and so, I've been leading a team over the last nine, months who. Have done, huge, numbers of experiments in, bringing. Digital, technology, to, our activities, you, know there's a spectrum between you. Know we're all out of business here because you're going to be taught by computers, in the future through you, know there's nothing there's nothing about the technologies, is going to help us because, you know the ancient Greeks had it right the old Socratic, method of, teaching will. Last forever you know somewhere, between those two extremes is, a reality, we, can call it blended learning if you like where, in fact the.

Classroom. Of the future is, actually, going to be partly, literally. A classroom and partly. An interactive. Virtual space, and so, I actually just gave. A little bit of encouragement to 10 of the faculty so. That they could try themselves a, bunch of experiments, in blended, learning to, see what they came up with and the other thing I is gonna make a little plug a shameless plug so I am, actually you, know one, of the creators of a course an online, course a so-called spot, a small private online course, we're, calling it innovating. In the digital world it, will launch of the first time in January we've, built this thing and we're going to be running it mostly. Online but, with occasional, workshops. And sessions led, by me and with some tutors so we, are doing stuff in this area and it's, exciting stuff, we, are deliberately, taking this really experimental, approach to say let, us try a bunch of stuff let's. Make sure it's high-quality and then a year or two from now we'll be in a position to say this is the direction of travel we want to go in and then we're going to put, a lot more money behind it so that Thank You Vera it wasn't a planted question but it was a really useful one only thing, that I've had the opportunity your opportunity, there are under threatened and. So. I miss that most clear more on the opportunity, and rather than threat right exactly. Is the glass half full is the glass half empty my colleague. Kostas marquita says you have to treat it as both you have to treat technology. As both, threat and opportunity, to get the best value management.

2018-11-02 20:41

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