WEBVTT 00:00:00.000 --> 00:00:03.800 Hi, in this set of lectures we are going to talk about problem solving. 00:00:03.800 --> 00:00:07.538 We’re going to talk about individuals and teams go about solving problems. 00:00:07.538 --> 00:00:09.146 and we’re going to focus on a couple of things — 00:00:09.146 --> 00:00:12.050 We're going to talk about the role that diversity plays in problem solving, 00:00:12.050 --> 00:00:15.856 and we’re also going to talk about how ideas can get recombined, 00:00:15.856 --> 00:00:17.923 and how a lot of innovation actually comes from 00:00:17.923 --> 00:00:21.200 somebody having an idea in one place and it being applied someplace else. 00:00:21.200 --> 00:00:26.800 So, those are going to be the two main themes: The role of diversity, and the power of recombination. 00:00:26.800 --> 00:00:30.962 So to get there, think about how we model problem solving: We got to start off by making it more formal, 00:00:30.962 --> 00:00:32.962 constructing a somewhat formal model. 00:00:32.962 --> 00:00:37.046 So here is how we are going to do it: We are going to assume that you take some sort of action (a), 00:00:37.046 --> 00:00:40.038 where you have some sort of solution we’ll represent by (a), 00:00:40.038 --> 00:00:43.662 and there's a payout function (F), that gives you the value of that particular action. 00:00:43.662 --> 00:00:47.769 So that action could be a particular string of code if you are writing computer code, 00:00:47.769 --> 00:00:50.800 and (F) might be how fast that code runs. 00:00:50.800 --> 00:00:57.408 Alternatively, (a) could be a health care policy and (F) would be how efficient that health care policy is. 00:00:57.408 --> 00:01:03.015 So, (a) is the solution that you propose and F(a) (F of a) is how good the solution is. 00:01:03.015 --> 00:01:05.638 What we want to do is to have some kind of an understanding [of] 00:01:05.638 --> 00:01:09.577 how people come up with better solutions — where innovation comes from. 00:01:09.577 --> 00:01:11.869 So to do that we are going to invoke a metaphor. 00:01:11.869 --> 00:01:18.215 And we are going to use this 'metaphor of a landscape' as a lens through which to interpret our models. 00:01:18.215 --> 00:01:20.800 Okay, so, think about it in the following way: 00:01:20.800 --> 00:01:24.108 You are trying to come up with some solution to a problem, and each solution has a value. 00:01:24.108 --> 00:01:27.762 So the altitude here is the value of it. 00:01:27.762 --> 00:01:31.062 So, B is the best possible solution. 00:01:31.062 --> 00:01:35.146 Now, along here on the X-axis, these are all the different solutions. 00:01:35.146 --> 00:01:37.523 So I might start out by having some Idea (I) 00:01:37.523 --> 00:01:39.912 (Let’s just put it right here, and here’s my idea.) 00:01:39.912 --> 00:01:43.367 And it's an okay idea; but we’d like to think about “How do we find better ideas?” 00:01:43.377 --> 00:01:46.977 So one think we might do is [we] might “try things to the left and the right,” 00:01:46.977 --> 00:01:51.269 and realize that “climb uphill” here and we get to some point (C); 00:01:51.269 --> 00:01:55.569 and (C) might be where I get stuck, because if I go to the left I’m lower, and if I go to the right I’m lower, 00:01:55.569 --> 00:01:58.831 so I could say “Wait, (C) is the best thing I can come up with.” 00:01:58.831 --> 00:02:01.623 What we want to see is how people come up with these ideas, 00:02:01.623 --> 00:02:03.800 how teams of people come up with better ideas, 00:02:03.800 --> 00:02:06.638 and how we can avoid getting stuck on (C), 00:02:06.638 --> 00:02:08.823 and possibly getting ourselve[s] up to (B). 00:02:09.715 --> 00:02:12.523 How are we going to do it? Well, here’s what the model is going to look like: 00:02:12.523 --> 00:02:16.885 We are going to start out by talking about something I am going to call ‘perspectives’. 00:02:16.885 --> 00:02:21.108 What is a perspective? Perspective is how you represent a problem. 00:02:21.108 --> 00:02:23.215 So if someone poses some problem to you— 00:02:23.215 --> 00:02:25.654 again, whether it is code, health care policy, 00:02:25.654 --> 00:02:29.631 designing a bycicle, or designing an addition to you house— 00:02:29.631 --> 00:02:32.469 you have some way of representing that problem in your head. 00:02:32.469 --> 00:02:37.392 That's going to be a perspective — it’s literally how you encode the problem. 00:02:37.400 --> 00:02:43.392 Once you have encoded the problem, what you do is you create—again, this is metaphorically—a ‘landscape’. 00:02:43.400 --> 00:02:46.962 as if you can think of your encoding is like that horizontal axis, 00:02:46.962 --> 00:02:49.500 and that there is a value for each possible solution, 00:02:49.500 --> 00:02:51.433 and that creates a landscape. 00:02:51.433 --> 00:02:56.338 So we are going to talk about how different perspectives give different landscapes. 00:02:56.338 --> 00:02:57.531 That is the first part. 00:02:57.531 --> 00:02:59.977 [The] second part is something I’m going to call ‘heuristics’. 00:02:59.977 --> 00:03:02.415 Heuristics are how you move on the landscape. 00:03:02.415 --> 00:03:04.062 So, remember when I drew that landscape, 00:03:04.062 --> 00:03:06.062 I talked about climbing up the 'hill'. 00:03:06.062 --> 00:03:08.208 Well, 'Hill Climbing' is one heuristic. 00:03:08.208 --> 00:03:11.831 'Random Search' would be another heuristic — if you just randomly pick some points 00:03:11.831 --> 00:03:15.131 and then find which one is where the highest value is, that is another heuristic. 00:03:15.131 --> 00:03:18.592 So we will talk about how different perspectives and different heruistics 00:03:18.592 --> 00:03:22.392 allow people to find a better or improving solutions to problems. 00:03:22.392 --> 00:03:24.762 So that is going to be the focus of our model of problem solving: 00:03:24.762 --> 00:03:28.623 People have perspectives, and people have heuristics. 00:03:28.623 --> 00:03:32.000 Once we finish talking about individuals, then we will talk about teams. 00:03:32.000 --> 00:03:36.023 One of the interesting things here is if you have groups of people or [a] team of people solving a problem. 00:03:36.023 --> 00:03:38.946 You actually can show that they will be better than the individuals in it. 00:03:38.946 --> 00:03:42.654 And the reason why is because they have more tools, and those tools tend to be diverse. 00:03:42.654 --> 00:03:46.669 So they have different perspectives and different heuristics, and all that diversity makes them better 00:03:46.669 --> 00:03:50.108 coming up with new solutions and better solutions to problems. 00:03:50.831 --> 00:03:52.685 So, teams are going to be important. 00:03:52.685 --> 00:03:54.738 After we have talked about teams, 00:03:54.738 --> 00:04:00.108 and after we have talked about the role of how one person can improve upon the solution of another, 00:04:00.115 --> 00:04:03.869 we are going to extend our model a little bit and talk about recombination. 00:04:03.869 --> 00:04:06.123 So here is sort of the big idea. The big idea is this: 00:04:06.123 --> 00:04:10.023 I have some solution from one problem, you have a solution from a different problem, 00:04:10.023 --> 00:04:13.100 and sometimes I can take your solution and combine it with my solution, 00:04:13.100 --> 00:04:15.200 and come up with something even better. 00:04:15.200 --> 00:04:17.269 So, the thing about sophisticated products— 00:04:17.269 --> 00:04:20.800 like a house, an automobile, or even a computer— 00:04:20.800 --> 00:04:24.115 that consists of all sorts of solutions to sub-problems. 00:04:24.115 --> 00:04:27.554 And we are going to see how by recombining solutions to sub-problems 00:04:27.554 --> 00:04:31.992 we get ever better solutions, and that is really a big driver of innovation. 00:04:31.992 --> 00:04:33.808 So let us think back for a second — Remember in our previous lecture, 00:04:33.808 --> 00:04:38.138 we talked about how without sustained innovation we no longer get growth, 00:04:38.138 --> 00:04:40.400 that growth depends on sustained innovation. 00:04:40.400 --> 00:04:44.323 What we’re going to talk about here is how diversity leads to innovations, 00:04:44.323 --> 00:04:48.231 and how recombinations of innovations can lead to even more Innovations. 00:04:48.231 --> 00:04:50.938 So that is the big theme — So that is where we are headed: 00:04:50.938 --> 00:04:54.831 We are going to start by talking about perspectives. Then we will talk about heuristics. 00:04:54.831 --> 00:04:59.454 Then we will talk about how teams of people can leverage their diverse perspectives in heuristics. 00:04:59.454 --> 00:05:04.362 And then we’ll talk about recombining ideas can really drive a lot of growth. 00:05:04.362 --> 00:05:09.284 All right, let’s get started. Thank you!