WEBVTT 00:00:00.000 --> 00:00:01.292 align:middle line:90% SARAH HANSEN: I'm Sarah Hansen. 00:00:01.292 --> 00:00:03.800 align:middle line:84% And today, I'm talking with financial economist Andrew 00:00:03.800 --> 00:00:06.110 align:middle line:84% Lo, whose videos have been viewed millions of times 00:00:06.110 --> 00:00:06.840 align:middle line:90% on our channel. 00:00:06.840 --> 00:00:09.260 align:middle line:84% I asked Andrew how he makes a topic like finance 00:00:09.260 --> 00:00:10.620 align:middle line:90% accessible to everyone. 00:00:10.620 --> 00:00:15.410 align:middle line:84% ANDREW LO: It's amazing how bad we are as Homo sapiens 00:00:15.410 --> 00:00:16.843 align:middle line:90% in managing our finances. 00:00:16.843 --> 00:00:18.260 align:middle line:84% SARAH HANSEN: We also get personal 00:00:18.260 --> 00:00:19.710 align:middle line:90% about his own learning journey. 00:00:19.710 --> 00:00:22.230 align:middle line:84% ANDREW LO: I have a learning issue. 00:00:22.230 --> 00:00:25.470 align:middle line:84% It's the mathematical equivalent of dyslexia, dyscalculia. 00:00:25.470 --> 00:00:26.455 align:middle line:90% SARAH HANSEN: You do? 00:00:26.455 --> 00:00:28.110 align:middle line:84% And I get his answer to the question, 00:00:28.110 --> 00:00:31.170 align:middle line:84% should I use ChatGPT to plan my retirement? 00:00:31.170 --> 00:00:33.740 align:middle line:90% [DRUM ROLL] 00:00:33.740 --> 00:00:36.650 align:middle line:84% All this and more on "Chalk Radio." 00:00:36.650 --> 00:00:39.097 align:middle line:84% Andrew, thank you so much for being with us today. 00:00:39.097 --> 00:00:39.930 align:middle line:90% ANDREW LO: Pleasure. 00:00:39.930 --> 00:00:40.930 align:middle line:90% Thank you for having me. 00:00:40.930 --> 00:00:42.530 align:middle line:84% SARAH HANSEN: For a long time, I've 00:00:42.530 --> 00:00:45.780 align:middle line:84% thought that if I don't have an advanced degree in mathematics, 00:00:45.780 --> 00:00:48.140 align:middle line:84% that I probably don't have a place in finance 00:00:48.140 --> 00:00:50.700 align:middle line:84% and probably shouldn't be thinking about it much. 00:00:50.700 --> 00:00:54.470 align:middle line:84% But I'm wondering if you might prompt me to think differently. 00:00:54.470 --> 00:00:55.970 align:middle line:84% ANDREW LO: Well, not surprisingly, I 00:00:55.970 --> 00:00:57.440 align:middle line:84% have a very different perspective 00:00:57.440 --> 00:00:59.700 align:middle line:90% as a financial economist. 00:00:59.700 --> 00:01:02.372 align:middle line:84% Someone once said that, to a person that has a hammer, 00:01:02.372 --> 00:01:03.580 align:middle line:90% everything looks like a nail. 00:01:03.580 --> 00:01:05.500 align:middle line:90% And I'm guilty as charged. 00:01:05.500 --> 00:01:09.610 align:middle line:84% I learned early on in life that virtually everything, 00:01:09.610 --> 00:01:13.260 align:middle line:84% at some point or another, ends up being about money. 00:01:13.260 --> 00:01:17.430 align:middle line:84% Particularly with regard to any kind of innovative pursuits 00:01:17.430 --> 00:01:20.767 align:middle line:84% for entrepreneurship or career-wise, 00:01:20.767 --> 00:01:22.350 align:middle line:84% at some point or another, you're going 00:01:22.350 --> 00:01:23.500 align:middle line:90% to have to deal with money. 00:01:23.500 --> 00:01:26.010 align:middle line:84% And then you need to speak the language of finance. 00:01:26.010 --> 00:01:27.600 align:middle line:84% So that's what really motivated me 00:01:27.600 --> 00:01:30.450 align:middle line:84% to learn how to speak that and then ultimately, be 00:01:30.450 --> 00:01:33.838 align:middle line:84% able to develop new words and sentences in that language. 00:01:33.838 --> 00:01:34.630 align:middle line:90% SARAH HANSEN: Yeah. 00:01:34.630 --> 00:01:35.680 align:middle line:90% It is a new language. 00:01:35.680 --> 00:01:38.190 align:middle line:84% And it seems like it's something that everybody 00:01:38.190 --> 00:01:40.363 align:middle line:84% can learn, no matter where they're starting from. 00:01:40.363 --> 00:01:41.280 align:middle line:90% ANDREW LO: Absolutely. 00:01:41.280 --> 00:01:43.750 align:middle line:84% SARAH HANSEN: You've contributed to OpenCourseWare. 00:01:43.750 --> 00:01:46.570 align:middle line:84% Your videos have been watched millions of times. 00:01:46.570 --> 00:01:49.110 align:middle line:84% And you seem really good at making 00:01:49.110 --> 00:01:51.360 align:middle line:84% finance accessible to people, no matter 00:01:51.360 --> 00:01:52.710 align:middle line:90% where they're starting from. 00:01:52.710 --> 00:01:56.340 align:middle line:84% I'm wondering what it is that you 00:01:56.340 --> 00:01:58.010 align:middle line:90% do that allows that to happen. 00:01:58.010 --> 00:02:00.380 align:middle line:84% Have you done any reflecting on that over the years? 00:02:00.380 --> 00:02:01.570 align:middle line:84% ANDREW LO: Well, first of all, it's a great honor 00:02:01.570 --> 00:02:02.890 align:middle line:90% to be part of OpenCourseWare. 00:02:02.890 --> 00:02:05.350 align:middle line:84% And the fact that it does reach people 00:02:05.350 --> 00:02:09.370 align:middle line:84% all around the world, regardless of cost or access, 00:02:09.370 --> 00:02:11.170 align:middle line:90% is really wonderful. 00:02:11.170 --> 00:02:14.290 align:middle line:84% And the reason that I was so pleased and honored 00:02:14.290 --> 00:02:16.637 align:middle line:84% to participate in that is because I really 00:02:16.637 --> 00:02:18.220 align:middle line:84% feel like everybody should have access 00:02:18.220 --> 00:02:21.370 align:middle line:84% to this knowledge, at different levels, of course. 00:02:21.370 --> 00:02:24.692 align:middle line:84% But we all need to know a little bit of finance. 00:02:24.692 --> 00:02:28.120 align:middle line:84% And I think that early on, I was really 00:02:28.120 --> 00:02:31.990 align:middle line:84% drawn to this field because of how impenetrable it was, 00:02:31.990 --> 00:02:34.610 align:middle line:84% and at the same time, how important it is. 00:02:34.610 --> 00:02:37.450 align:middle line:84% Growing up, I just remember always 00:02:37.450 --> 00:02:39.640 align:middle line:84% hearing my mother talk about finances 00:02:39.640 --> 00:02:42.200 align:middle line:84% and some of the challenges that we were facing. 00:02:42.200 --> 00:02:46.480 align:middle line:84% And I think that really made me hyperaware of the fact 00:02:46.480 --> 00:02:49.910 align:middle line:84% that it's really a necessary part of life-- sometimes, 00:02:49.910 --> 00:02:51.800 align:middle line:84% unfortunately, too much a part of life. 00:02:51.800 --> 00:02:54.220 align:middle line:84% And if we don't understand it, it's 00:02:54.220 --> 00:02:57.950 align:middle line:84% very easy to end up being taken advantage of 00:02:57.950 --> 00:03:00.800 align:middle line:84% or not being well prepared for the kind of things 00:03:00.800 --> 00:03:02.405 align:middle line:84% that finance helps you deal with. 00:03:02.405 --> 00:03:04.280 align:middle line:84% SARAH HANSEN: Yeah, I think about this a lot, 00:03:04.280 --> 00:03:07.370 align:middle line:84% when I go to the grocery store and see cereals 00:03:07.370 --> 00:03:12.990 align:middle line:84% for over $6 and eggs sometimes up to $8. 00:03:12.990 --> 00:03:17.810 align:middle line:84% What are some theories of modern finance that everyday people 00:03:17.810 --> 00:03:20.330 align:middle line:84% like me could apply or think about 00:03:20.330 --> 00:03:22.910 align:middle line:84% when I'm faced with those situations? 00:03:22.910 --> 00:03:23.640 align:middle line:90% ANDREW LO: Wow. 00:03:23.640 --> 00:03:27.740 align:middle line:84% Well, there's a whole bunch of ideas and important notions 00:03:27.740 --> 00:03:30.560 align:middle line:84% that we can use in our everyday lives. 00:03:30.560 --> 00:03:33.470 align:middle line:84% One of the key notions is that there's 00:03:33.470 --> 00:03:36.620 align:middle line:84% a trade-off among everything that we do 00:03:36.620 --> 00:03:38.580 align:middle line:90% and everything that we purchase. 00:03:38.580 --> 00:03:41.610 align:middle line:84% Far too often, we tend to compartmentalize. 00:03:41.610 --> 00:03:45.420 align:middle line:84% And we have a mental budget for certain activities, 00:03:45.420 --> 00:03:47.730 align:middle line:84% as well as other budgets for other activities. 00:03:47.730 --> 00:03:49.590 align:middle line:90% And we don't allow them to mix. 00:03:49.590 --> 00:03:52.250 align:middle line:84% But sometimes, if you can think a little bit more 00:03:52.250 --> 00:03:57.450 align:middle line:84% broadly about the fact that we have a given set of resources, 00:03:57.450 --> 00:03:59.340 align:middle line:84% and we have to allocate them across lots 00:03:59.340 --> 00:04:01.260 align:middle line:84% of different activities, and there 00:04:01.260 --> 00:04:05.020 align:middle line:84% are interesting financial ways of making those decisions, 00:04:05.020 --> 00:04:07.288 align:middle line:84% we can actually come up with better outcomes. 00:04:07.288 --> 00:04:09.330 align:middle line:84% One example that I think most people are aware of 00:04:09.330 --> 00:04:13.030 align:middle line:84% is borrowing money to buy a home or buy a car. 00:04:13.030 --> 00:04:17.459 align:middle line:84% That is basically moving money from the future, our futures, 00:04:17.459 --> 00:04:18.833 align:middle line:90% to our present. 00:04:18.833 --> 00:04:19.500 align:middle line:90% We're borrowing. 00:04:19.500 --> 00:04:23.460 align:middle line:84% And sometimes we need to put money today aside 00:04:23.460 --> 00:04:27.520 align:middle line:84% for our kids' college fund or purchasing a car in the future. 00:04:27.520 --> 00:04:31.440 align:middle line:84% That's an example of moving money from today to ourselves 00:04:31.440 --> 00:04:33.520 align:middle line:84% two years from now or three years from now. 00:04:33.520 --> 00:04:36.420 align:middle line:84% So this notion of being able to move money around 00:04:36.420 --> 00:04:40.380 align:middle line:84% and making sure that you don't lose a lot of it in the process 00:04:40.380 --> 00:04:42.580 align:middle line:84% is part of the language of finance. 00:04:42.580 --> 00:04:45.168 align:middle line:84% And that's something that all of us can benefit from. 00:04:45.168 --> 00:04:45.960 align:middle line:90% SARAH HANSEN: Yeah. 00:04:45.960 --> 00:04:48.930 align:middle line:84% It's so interesting, the idea of having 00:04:48.930 --> 00:04:53.050 align:middle line:84% more flexible understanding of your resources 00:04:53.050 --> 00:04:55.992 align:middle line:84% and how they might move across categories. 00:04:55.992 --> 00:04:57.950 align:middle line:84% ANDREW LO: I mean, I think, at the heart of it, 00:04:57.950 --> 00:04:59.720 align:middle line:90% it's really all about control. 00:04:59.720 --> 00:05:02.200 align:middle line:84% But I think not enough people understand 00:05:02.200 --> 00:05:05.740 align:middle line:84% how finance works so that ultimately, it ends up 00:05:05.740 --> 00:05:09.580 align:middle line:84% ruling their lives, as opposed to allowing them to use finance 00:05:09.580 --> 00:05:12.500 align:middle line:84% to achieve the kind of goals that they really want. 00:05:12.500 --> 00:05:15.620 align:middle line:84% SARAH HANSEN: So, Andrew, before the show, 00:05:15.620 --> 00:05:18.850 align:middle line:84% we asked you to respond to a question, which we will now 00:05:18.850 --> 00:05:20.060 align:middle line:90% reveal the answer to. 00:05:20.060 --> 00:05:23.870 align:middle line:84% So the question was, should I, Sarah Hansen, 00:05:23.870 --> 00:05:27.410 align:middle line:84% use ChatGPT right now to plan my retirement? 00:05:27.410 --> 00:05:30.280 align:middle line:90% What's our answer? 00:05:30.280 --> 00:05:31.400 align:middle line:90% Not yet. 00:05:31.400 --> 00:05:31.990 align:middle line:90% OK. 00:05:31.990 --> 00:05:32.638 align:middle line:90% Please explain. 00:05:32.638 --> 00:05:33.430 align:middle line:90% ANDREW LO: Not yet. 00:05:33.430 --> 00:05:36.340 align:middle line:84% Not yet, because large language models 00:05:36.340 --> 00:05:39.550 align:middle line:84% are not yet ready to be able to do 00:05:39.550 --> 00:05:42.310 align:middle line:84% delegated financial decision making for us. 00:05:42.310 --> 00:05:44.230 align:middle line:84% Turns out that saving for retirement 00:05:44.230 --> 00:05:45.860 align:middle line:90% is one set of activities. 00:05:45.860 --> 00:05:47.878 align:middle line:84% But then spending while in retirement, 00:05:47.878 --> 00:05:49.670 align:middle line:84% that's a whole different set of activities. 00:05:49.670 --> 00:05:52.090 align:middle line:84% And many of us have become good at saving. 00:05:52.090 --> 00:05:55.620 align:middle line:84% But we've been such good savers that we 00:05:55.620 --> 00:05:58.320 align:middle line:84% forget that at some point, we need to spend. 00:05:58.320 --> 00:06:01.170 align:middle line:84% And we have to spend at the right rate, 00:06:01.170 --> 00:06:03.760 align:middle line:84% for the right things, at the right times. 00:06:03.760 --> 00:06:07.110 align:middle line:84% So what my colleagues and I are trying to understand now 00:06:07.110 --> 00:06:10.690 align:middle line:84% is not only what those optimal decisions are-- 00:06:10.690 --> 00:06:12.880 align:middle line:84% I think we now have a lot of information about that. 00:06:12.880 --> 00:06:14.290 align:middle line:84% There's been a lot of research done on that. 00:06:14.290 --> 00:06:17.220 align:middle line:84% But the more challenging issue is, how do we communicate that 00:06:17.220 --> 00:06:19.470 align:middle line:84% to people who don't have any finance background, 00:06:19.470 --> 00:06:22.980 align:middle line:84% and moreover, can't afford to hire the financial advisors 00:06:22.980 --> 00:06:25.050 align:middle line:84% that some of the higher-net-worth individuals 00:06:25.050 --> 00:06:26.110 align:middle line:90% have access to? 00:06:26.110 --> 00:06:30.120 align:middle line:84% So we're working on an AI solution, an AI 00:06:30.120 --> 00:06:33.090 align:middle line:84% financial advisor, that can satisfy 00:06:33.090 --> 00:06:36.480 align:middle line:84% the most important criterion of financial advice 00:06:36.480 --> 00:06:39.640 align:middle line:84% that regulators impose, which is something called fiduciary duty. 00:06:39.640 --> 00:06:42.390 align:middle line:84% A fiduciary is somebody who is appointed 00:06:42.390 --> 00:06:45.090 align:middle line:84% to help you further your goals, will look out 00:06:45.090 --> 00:06:48.980 align:middle line:84% for your best interests, above and beyond their own. 00:06:48.980 --> 00:06:50.800 align:middle line:84% And so, very often, people get a little bit 00:06:50.800 --> 00:06:53.017 align:middle line:84% concerned about financial planners and other people 00:06:53.017 --> 00:06:54.850 align:middle line:84% in the financial industry because they don't 00:06:54.850 --> 00:06:56.360 align:middle line:90% want to be taken advantage of. 00:06:56.360 --> 00:06:59.060 align:middle line:84% And there are many good financial planners out there. 00:06:59.060 --> 00:07:00.860 align:middle line:84% But not everybody can afford one. 00:07:00.860 --> 00:07:03.730 align:middle line:84% So the question is, can you-- for those people who 00:07:03.730 --> 00:07:06.370 align:middle line:84% can't afford financial planning and for the financial 00:07:06.370 --> 00:07:09.100 align:middle line:84% institutions that don't want to spend their resources 00:07:09.100 --> 00:07:12.280 align:middle line:84% on financial advice to those who aren't going to generate enough 00:07:12.280 --> 00:07:13.460 align:middle line:90% commissions for them-- 00:07:13.460 --> 00:07:18.370 align:middle line:84% for these people, can we come up with financial advice from an AI 00:07:18.370 --> 00:07:22.370 align:middle line:84% platform that satisfies the definition of a fiduciary, 00:07:22.370 --> 00:07:25.342 align:middle line:84% some program that you can trust to look out 00:07:25.342 --> 00:07:26.300 align:middle line:90% for your best interest? 00:07:26.300 --> 00:07:27.200 align:middle line:90% We're not there yet. 00:07:27.200 --> 00:07:29.530 align:middle line:84% However, I believe that everybody 00:07:29.530 --> 00:07:31.510 align:middle line:84% should use large language models to help 00:07:31.510 --> 00:07:34.730 align:middle line:84% them think through retirement issues more seriously. 00:07:34.730 --> 00:07:38.020 align:middle line:84% For example, ask ChatGPT, what are the biggest issues 00:07:38.020 --> 00:07:39.830 align:middle line:84% that I need to focus on for my retirement? 00:07:39.830 --> 00:07:41.030 align:middle line:90% How much time do I have? 00:07:41.030 --> 00:07:43.780 align:middle line:84% What kind of ideas, and products, and services 00:07:43.780 --> 00:07:44.720 align:middle line:90% should I make use of? 00:07:44.720 --> 00:07:46.690 align:middle line:84% How do I get better financial information? 00:07:46.690 --> 00:07:48.520 align:middle line:84% How do I learn more about these problems? 00:07:48.520 --> 00:07:50.430 align:middle line:84% All of those things, I think ChatGPT 00:07:50.430 --> 00:07:51.790 align:middle line:90% can do a pretty good job at. 00:07:51.790 --> 00:07:54.490 align:middle line:84% But I wouldn't let it make your decisions for you. 00:07:54.490 --> 00:07:55.990 align:middle line:84% SARAH HANSEN: Real question for you. 00:07:55.990 --> 00:07:59.370 align:middle line:84% I know, a lot of times, when I put in a prompt that's 00:07:59.370 --> 00:08:03.490 align:middle line:84% within my domain of expertise, some of it will be good, 00:08:03.490 --> 00:08:06.160 align:middle line:84% but some it's kind of garbage and not all that accurate. 00:08:06.160 --> 00:08:08.410 align:middle line:84% So as a person who doesn't know finance, 00:08:08.410 --> 00:08:11.020 align:middle line:84% how do I know I can trust the answers that are coming back, 00:08:11.020 --> 00:08:13.300 align:middle line:84% even about those general type of questions? 00:08:13.300 --> 00:08:14.700 align:middle line:84% ANDREW LO: Well, so that's really 00:08:14.700 --> 00:08:17.100 align:middle line:84% why you need to have additional time 00:08:17.100 --> 00:08:20.230 align:middle line:84% and effort employed in thinking through these issues, 00:08:20.230 --> 00:08:23.100 align:middle line:84% not just by yourself, but with friends and family. 00:08:23.100 --> 00:08:25.710 align:middle line:84% So we need human support for thinking 00:08:25.710 --> 00:08:28.260 align:middle line:84% about how large language models can work, either well, 00:08:28.260 --> 00:08:30.070 align:middle line:90% or in some cases, not so well. 00:08:30.070 --> 00:08:32.947 align:middle line:84% And in any case, if you are planning for your retirement, 00:08:32.947 --> 00:08:34.530 align:middle line:84% at some point or another, you're going 00:08:34.530 --> 00:08:37.650 align:middle line:84% to have to engage with people from the financial institutions. 00:08:37.650 --> 00:08:39.360 align:middle line:84% They will be able to help deal with some 00:08:39.360 --> 00:08:41.370 align:middle line:84% of the so-called hallucination problems 00:08:41.370 --> 00:08:43.270 align:middle line:84% with these large language models. 00:08:43.270 --> 00:08:45.582 align:middle line:84% But the answer is like anything else that we do. 00:08:45.582 --> 00:08:47.790 align:middle line:84% How do you know that your doctor is always giving you 00:08:47.790 --> 00:08:48.852 align:middle line:90% the best information? 00:08:48.852 --> 00:08:51.310 align:middle line:84% Doctors are very highly trained, but they do make mistakes. 00:08:51.310 --> 00:08:52.870 align:middle line:90% So get a second opinion. 00:08:52.870 --> 00:08:53.860 align:middle line:90% Get a third opinion. 00:08:53.860 --> 00:08:55.070 align:middle line:90% Talk to your family members. 00:08:55.070 --> 00:08:56.820 align:middle line:84% Ultimately, you're going to be responsible 00:08:56.820 --> 00:08:57.910 align:middle line:90% for your own decisions. 00:08:57.910 --> 00:08:59.800 align:middle line:84% But the more informed you can be, 00:08:59.800 --> 00:09:03.130 align:middle line:84% and the more you can check the accuracy of the information-- 00:09:03.130 --> 00:09:06.480 align:middle line:84% and that information can come from humans or from chatbots-- 00:09:06.480 --> 00:09:09.750 align:middle line:84% I think those are the ways that we've developed for making sure 00:09:09.750 --> 00:09:12.150 align:middle line:84% that we make the best decisions possible to get a better 00:09:12.150 --> 00:09:12.792 align:middle line:90% handle on this. 00:09:12.792 --> 00:09:13.625 align:middle line:90% SARAH HANSEN: Right. 00:09:13.625 --> 00:09:18.180 align:middle line:84% And I assume part of the idea would be to start this 00:09:18.180 --> 00:09:19.950 align:middle line:90% in your 20s, if you can. 00:09:19.950 --> 00:09:22.800 align:middle line:84% Start learning and start using these applications 00:09:22.800 --> 00:09:24.258 align:middle line:90% to really begin to save. 00:09:24.258 --> 00:09:25.050 align:middle line:90% ANDREW LO: Exactly. 00:09:25.050 --> 00:09:28.110 align:middle line:84% Many people don't realize that the decisions that they 00:09:28.110 --> 00:09:32.370 align:middle line:84% make early on can have just tremendous consequences 30, 40 00:09:32.370 --> 00:09:33.220 align:middle line:90% years from now. 00:09:33.220 --> 00:09:34.480 align:middle line:90% We now know that about health. 00:09:34.480 --> 00:09:37.210 align:middle line:84% We know that if we don't eat right, even as a teenager, 00:09:37.210 --> 00:09:39.670 align:middle line:84% we can affect our health when we get to middle age. 00:09:39.670 --> 00:09:41.830 align:middle line:84% The same thing is true about our finances. 00:09:41.830 --> 00:09:44.370 align:middle line:84% If we make bad financial decisions early on, 00:09:44.370 --> 00:09:47.660 align:middle line:84% it could end up having repercussions far beyond what we 00:09:47.660 --> 00:09:49.500 align:middle line:90% typically are able to measure. 00:09:49.500 --> 00:09:52.710 align:middle line:84% And so that's really the purpose of having some kind of support, 00:09:52.710 --> 00:09:55.620 align:middle line:84% some kind of advice that can actually look 40, 00:09:55.620 --> 00:09:58.560 align:middle line:90% 50 years ahead of a teenager. 00:09:58.560 --> 00:10:01.130 align:middle line:84% SARAH HANSEN: It's kind of interesting, because at least 00:10:01.130 --> 00:10:04.430 align:middle line:84% in the US, or at least in the cultural circles 00:10:04.430 --> 00:10:07.650 align:middle line:84% in which I grew up, it was sort of taboo to talk about money-- 00:10:07.650 --> 00:10:10.860 align:middle line:84% how much you make, how much other people make, 00:10:10.860 --> 00:10:12.030 align:middle line:90% how you're budgeting. 00:10:12.030 --> 00:10:13.713 align:middle line:84% Have you found that in this context? 00:10:13.713 --> 00:10:14.630 align:middle line:90% ANDREW LO: Absolutely. 00:10:14.630 --> 00:10:16.213 align:middle line:84% And that's actually one of the reasons 00:10:16.213 --> 00:10:18.000 align:middle line:84% why you want to have a fiduciary. 00:10:18.000 --> 00:10:19.760 align:middle line:84% You want to have somebody you can 00:10:19.760 --> 00:10:24.870 align:middle line:84% talk to about your deepest secrets, your financial goals, 00:10:24.870 --> 00:10:27.620 align:middle line:84% your constraints, the concerns that you have about losing 00:10:27.620 --> 00:10:29.840 align:middle line:84% your job or not being able to find a job, 00:10:29.840 --> 00:10:32.850 align:middle line:84% and be able to get honest advice about what to do about it. 00:10:32.850 --> 00:10:35.563 align:middle line:84% Many of us have good friends that we can rely on for that. 00:10:35.563 --> 00:10:36.980 align:middle line:84% But if you don't have a friend who 00:10:36.980 --> 00:10:39.080 align:middle line:84% has financial expertise, what do you do? 00:10:39.080 --> 00:10:43.610 align:middle line:84% So the hope is that maybe a platform, a reliable AI 00:10:43.610 --> 00:10:47.090 align:middle line:84% platform that is able to serve as a fiduciary, 00:10:47.090 --> 00:10:50.448 align:middle line:84% can really help individuals with all of their concerns. 00:10:50.448 --> 00:10:51.240 align:middle line:90% SARAH HANSEN: Yeah. 00:10:51.240 --> 00:10:53.670 align:middle line:84% That's going to be a game changer for sure. 00:10:53.670 --> 00:10:57.530 align:middle line:84% What are some of the dangers, pitfalls, or challenges 00:10:57.530 --> 00:11:00.890 align:middle line:84% that might come with leveraging AI 00:11:00.890 --> 00:11:03.380 align:middle line:84% to give financial advice to people who do not 00:11:03.380 --> 00:11:07.350 align:middle line:90% have financial expertise? 00:11:07.350 --> 00:11:10.500 align:middle line:84% ANDREW LO: Well, any great tool can easily be abused. 00:11:10.500 --> 00:11:12.740 align:middle line:84% And I think we have to worry about the fact 00:11:12.740 --> 00:11:17.220 align:middle line:84% that if we have a financial planning tool that is AI driven, 00:11:17.220 --> 00:11:18.780 align:middle line:90% can that be abused? 00:11:18.780 --> 00:11:23.240 align:middle line:84% What if we were to ask this AI to engage in illicit activities 00:11:23.240 --> 00:11:25.620 align:middle line:90% for our financial betterment? 00:11:25.620 --> 00:11:28.770 align:middle line:84% Is that something that we should be able to do? 00:11:28.770 --> 00:11:32.077 align:middle line:84% Or is it something that the AIs should guard against? 00:11:32.077 --> 00:11:34.160 align:middle line:84% You get into all sorts of tricky ethical questions 00:11:34.160 --> 00:11:36.090 align:middle line:90% about how these tools are used. 00:11:36.090 --> 00:11:38.180 align:middle line:84% And so I think that those of us who 00:11:38.180 --> 00:11:40.770 align:middle line:84% are developing the technologies really 00:11:40.770 --> 00:11:42.990 align:middle line:84% require spending more time thinking 00:11:42.990 --> 00:11:44.245 align:middle line:90% about the ethical dimensions. 00:11:44.245 --> 00:11:45.870 align:middle line:84% That's not something that you typically 00:11:45.870 --> 00:11:47.530 align:middle line:90% focus on in your research. 00:11:47.530 --> 00:11:52.090 align:middle line:84% But for us now, given how far AI has come and what it can do, 00:11:52.090 --> 00:11:54.420 align:middle line:84% we have to be much more proactive 00:11:54.420 --> 00:11:56.958 align:middle line:84% about thinking about these unintended consequences. 00:11:56.958 --> 00:11:59.500 align:middle line:84% SARAH HANSEN: Yeah, and just how fast everything is changing. 00:11:59.500 --> 00:12:02.890 align:middle line:84% The technology is so fluid and so fast, and honestly, 00:12:02.890 --> 00:12:04.960 align:middle line:84% not all that transparent most of the time. 00:12:04.960 --> 00:12:05.627 align:middle line:90% ANDREW LO: Yeah. 00:12:05.627 --> 00:12:07.980 align:middle line:84% That's a concern that I think most people don't really 00:12:07.980 --> 00:12:08.950 align:middle line:90% appreciate yet. 00:12:08.950 --> 00:12:11.370 align:middle line:84% It's true that there's always been technology 00:12:11.370 --> 00:12:13.800 align:middle line:84% that has made advances, and as a result, 00:12:13.800 --> 00:12:15.790 align:middle line:90% has created winners and losers. 00:12:15.790 --> 00:12:19.350 align:middle line:84% When the horse-drawn buggy gave way to railroads and then 00:12:19.350 --> 00:12:22.380 align:middle line:84% eventually to automobiles, people lost their jobs. 00:12:22.380 --> 00:12:24.390 align:middle line:90% And people had to be retrained. 00:12:24.390 --> 00:12:27.180 align:middle line:84% But there is a big difference between that technology 00:12:27.180 --> 00:12:29.408 align:middle line:84% and the current set of technologies. 00:12:29.408 --> 00:12:30.700 align:middle line:90% And it's exactly what you said. 00:12:30.700 --> 00:12:32.040 align:middle line:90% It's about speed. 00:12:32.040 --> 00:12:36.510 align:middle line:84% The fact is that right now, AI is moving at such breakneck pace 00:12:36.510 --> 00:12:39.560 align:middle line:84% that within a very short period of time, 00:12:39.560 --> 00:12:44.380 align:middle line:84% we can actually have large parts of our population unemployed. 00:12:44.380 --> 00:12:47.320 align:middle line:84% And the hope of retraining them in time for them 00:12:47.320 --> 00:12:49.360 align:middle line:84% to make a difference for their lives 00:12:49.360 --> 00:12:52.640 align:middle line:84% can be very challenging, given how quickly things are moving. 00:12:52.640 --> 00:12:56.110 align:middle line:84% So I think that's the one concern that AI researchers are 00:12:56.110 --> 00:12:57.340 align:middle line:90% thinking about. 00:12:57.340 --> 00:12:59.060 align:middle line:84% We don't have any good answers yet. 00:12:59.060 --> 00:13:01.160 align:middle line:84% And one of the answers that's been proposed, 00:13:01.160 --> 00:13:03.370 align:middle line:84% which is to slow down the rate of progress-- 00:13:03.370 --> 00:13:05.360 align:middle line:90% that's almost never possible. 00:13:05.360 --> 00:13:08.120 align:middle line:84% Even if you want to do it, even if you have legislation, 00:13:08.120 --> 00:13:09.670 align:middle line:84% there'll be people that will refuse 00:13:09.670 --> 00:13:13.720 align:middle line:84% to abide by that, because legislation is not going to stop 00:13:13.720 --> 00:13:14.960 align:middle line:90% that kind of innovation. 00:13:14.960 --> 00:13:17.418 align:middle line:84% It's not going to stop people from having ideas and wanting 00:13:17.418 --> 00:13:18.230 align:middle line:90% to implement them. 00:13:18.230 --> 00:13:19.022 align:middle line:90% SARAH HANSEN: Yeah. 00:13:19.022 --> 00:13:22.720 align:middle line:84% The idea of people being put out of work with the advancement 00:13:22.720 --> 00:13:24.920 align:middle line:84% of these technologies is hugely concerning, 00:13:24.920 --> 00:13:27.370 align:middle line:84% and I know one that you're concerned about, because it 00:13:27.370 --> 00:13:29.240 align:middle line:84% seems like, in everything you do, 00:13:29.240 --> 00:13:34.270 align:middle line:84% it all comes back to people and the impact on people. 00:13:34.270 --> 00:13:37.880 align:middle line:84% I'm wondering where that drive comes from. 00:13:37.880 --> 00:13:41.120 align:middle line:84% Where did your interest in leveraging finance 00:13:41.120 --> 00:13:44.340 align:middle line:84% to positively impact people's lives come from? 00:13:44.340 --> 00:13:45.780 align:middle line:90% Because it didn't have to. 00:13:45.780 --> 00:13:47.360 align:middle line:84% There's a lot you can do with money 00:13:47.360 --> 00:13:50.190 align:middle line:84% and not worry about positively impacting people. 00:13:50.190 --> 00:13:52.303 align:middle line:84% So tell us a little bit about that. 00:13:52.303 --> 00:13:53.220 align:middle line:90% ANDREW LO: Well, yeah. 00:13:53.220 --> 00:13:55.730 align:middle line:84% I have to say that that was really not something 00:13:55.730 --> 00:13:56.790 align:middle line:90% that I had planned. 00:13:56.790 --> 00:13:58.940 align:middle line:84% Much of my early career was focused 00:13:58.940 --> 00:14:01.760 align:middle line:84% on applying mathematical and statistical models to investment 00:14:01.760 --> 00:14:04.800 align:middle line:84% problems, developing trading strategies, 00:14:04.800 --> 00:14:08.570 align:middle line:84% risk management policies, various kinds of systemic risk 00:14:08.570 --> 00:14:09.420 align:middle line:90% measures. 00:14:09.420 --> 00:14:12.770 align:middle line:84% It was really all geared around the amazing impact 00:14:12.770 --> 00:14:15.990 align:middle line:84% that this technology could have on the field itself, 00:14:15.990 --> 00:14:18.480 align:middle line:84% on finance, making finance better. 00:14:18.480 --> 00:14:21.260 align:middle line:84% And in some of the things that I did in practice 00:14:21.260 --> 00:14:22.730 align:middle line:90% on the commercial side-- 00:14:22.730 --> 00:14:24.830 align:middle line:84% started up my own asset management company 00:14:24.830 --> 00:14:27.380 align:middle line:84% and ultimately implemented some of these strategies 00:14:27.380 --> 00:14:30.950 align:middle line:84% for various kinds of hedge funds and investors. 00:14:30.950 --> 00:14:32.648 align:middle line:90% And at some point-- 00:14:32.648 --> 00:14:33.940 align:middle line:90% I mean, it was very satisfying. 00:14:33.940 --> 00:14:36.930 align:middle line:84% But at some point, I started to wonder whether or not 00:14:36.930 --> 00:14:42.400 align:middle line:84% this was it, this was what I was meant to do. 00:14:42.400 --> 00:14:44.890 align:middle line:84% And around that time-- it was about 20 years ago-- 00:14:44.890 --> 00:14:48.390 align:middle line:84% a number of friends and family all developed cancer 00:14:48.390 --> 00:14:49.180 align:middle line:90% at the same time. 00:14:49.180 --> 00:14:51.510 align:middle line:84% Within seven years, six people close to me 00:14:51.510 --> 00:14:53.220 align:middle line:90% all died, including my mother. 00:14:53.220 --> 00:14:56.850 align:middle line:84% I'd really never dealt with death up close 00:14:56.850 --> 00:14:58.470 align:middle line:90% and personal before that. 00:14:58.470 --> 00:15:01.960 align:middle line:84% And so it was a big wake up call, and through that process, 00:15:01.960 --> 00:15:06.300 align:middle line:84% realized that finance plays a pretty big role in cancer drug 00:15:06.300 --> 00:15:07.150 align:middle line:90% development. 00:15:07.150 --> 00:15:08.735 align:middle line:90% I was pretty naive at the time. 00:15:08.735 --> 00:15:10.860 align:middle line:84% I just thought that if there was a patient in need, 00:15:10.860 --> 00:15:12.480 align:middle line:84% and there was some great technology that 00:15:12.480 --> 00:15:14.522 align:middle line:84% could help that patient, that somehow, magically, 00:15:14.522 --> 00:15:17.700 align:middle line:84% money would just come sprinkling down and develop the drug. 00:15:17.700 --> 00:15:20.340 align:middle line:84% But when I looked into it and talked to my colleagues 00:15:20.340 --> 00:15:23.580 align:middle line:84% here in Cambridge, it became very obvious to me 00:15:23.580 --> 00:15:25.920 align:middle line:84% that that was not the case, that there 00:15:25.920 --> 00:15:29.820 align:middle line:84% were many examples of good drugs that could help lots of patients 00:15:29.820 --> 00:15:32.810 align:middle line:84% that will never, ever see it to market because there 00:15:32.810 --> 00:15:36.090 align:middle line:84% was not enough financing to bring that to the patients. 00:15:36.090 --> 00:15:39.170 align:middle line:84% So that's when I started thinking about how finance 00:15:39.170 --> 00:15:40.560 align:middle line:90% could play a role in that. 00:15:40.560 --> 00:15:42.087 align:middle line:84% And it was actually totally selfish. 00:15:42.087 --> 00:15:44.420 align:middle line:84% I wanted to figure out how to help my friends and family 00:15:44.420 --> 00:15:46.730 align:middle line:84% and how to get better drugs to them. 00:15:46.730 --> 00:15:50.090 align:middle line:84% But in doing so, it just made me realize the power of finance 00:15:50.090 --> 00:15:53.360 align:middle line:84% and the responsibility that we have, 00:15:53.360 --> 00:15:56.030 align:middle line:84% given that we understand the kind of things 00:15:56.030 --> 00:15:57.680 align:middle line:84% that other people don't about how 00:15:57.680 --> 00:15:59.850 align:middle line:84% to finance certain kinds of projects, 00:15:59.850 --> 00:16:02.600 align:middle line:84% about how to bring money to a particular area 00:16:02.600 --> 00:16:07.308 align:middle line:84% and really make it go faster, that we also 00:16:07.308 --> 00:16:09.350 align:middle line:84% have a responsibility to take some of these ideas 00:16:09.350 --> 00:16:11.540 align:middle line:84% and implement them for those really 00:16:11.540 --> 00:16:14.060 align:middle line:84% high-impact, high-societal-impact kinds 00:16:14.060 --> 00:16:16.370 align:middle line:90% of pursuits. 00:16:16.370 --> 00:16:17.483 align:middle line:90% So I started with that. 00:16:17.483 --> 00:16:18.900 align:middle line:84% And then one thing led to another. 00:16:18.900 --> 00:16:22.070 align:middle line:84% And I began thinking more broadly about how finance 00:16:22.070 --> 00:16:24.883 align:middle line:84% impacts society in general, and realizing 00:16:24.883 --> 00:16:26.300 align:middle line:84% that there are many things that we 00:16:26.300 --> 00:16:29.460 align:middle line:84% can do to further all sorts of different goals-- 00:16:29.460 --> 00:16:32.500 align:middle line:84% climate change, energy transition. 00:16:32.500 --> 00:16:34.080 align:middle line:84% There are so many different issues 00:16:34.080 --> 00:16:36.390 align:middle line:84% that really are crying out for new business models 00:16:36.390 --> 00:16:37.810 align:middle line:90% and financing strategies. 00:16:37.810 --> 00:16:41.180 align:middle line:84% And these are well-known tools that all financial economists 00:16:41.180 --> 00:16:41.680 align:middle line:90% know. 00:16:41.680 --> 00:16:44.590 align:middle line:84% But we haven't really spent time thinking about the applications. 00:16:44.590 --> 00:16:46.410 align:middle line:84% So that's been a really rewarding aspect 00:16:46.410 --> 00:16:47.388 align:middle line:90% of my current focus. 00:16:47.388 --> 00:16:48.180 align:middle line:90% SARAH HANSEN: Yeah. 00:16:48.180 --> 00:16:51.480 align:middle line:84% Could you give an example of how a different business 00:16:51.480 --> 00:16:54.930 align:middle line:84% model might radically change the climate trajectory 00:16:54.930 --> 00:16:55.643 align:middle line:90% that we're on? 00:16:55.643 --> 00:16:56.310 align:middle line:90% ANDREW LO: Sure. 00:16:56.310 --> 00:16:58.480 align:middle line:84% Let's talk about energy transition, 00:16:58.480 --> 00:17:01.350 align:middle line:84% because clearly, we are not in the process 00:17:01.350 --> 00:17:03.130 align:middle line:90% of transitioning very quickly. 00:17:03.130 --> 00:17:04.255 align:middle line:90% SARAH HANSEN: That's right. 00:17:04.255 --> 00:17:06.930 align:middle line:84% ANDREW LO: In fact, right now, about 82% 00:17:06.930 --> 00:17:10.240 align:middle line:84% of the world's energy usage is in the form of fossil fuels. 00:17:10.240 --> 00:17:15.880 align:middle line:84% I think that might be down from 83% or 84% 10 years ago. 00:17:15.880 --> 00:17:16.960 align:middle line:90% It's not enough. 00:17:16.960 --> 00:17:19.869 align:middle line:84% And we're not making a difference fast enough. 00:17:19.869 --> 00:17:22.260 align:middle line:84% A number of people who know a lot more about the issues 00:17:22.260 --> 00:17:25.200 align:middle line:84% than I do have said that we're not really, 00:17:25.200 --> 00:17:27.520 align:middle line:84% right now, in the business of transitioning, 00:17:27.520 --> 00:17:30.590 align:middle line:84% because it's not as if we're declining our usage of energy. 00:17:30.590 --> 00:17:31.730 align:middle line:90% If anything, it's growing. 00:17:31.730 --> 00:17:33.370 align:middle line:84% So what we need to do is to come up 00:17:33.370 --> 00:17:36.307 align:middle line:84% with new sources of energy, energy addition, 00:17:36.307 --> 00:17:37.640 align:middle line:90% as opposed to energy transition. 00:17:37.640 --> 00:17:38.690 align:middle line:84% SARAH HANSEN: Oh, that's interesting. 00:17:38.690 --> 00:17:40.490 align:middle line:84% ANDREW LO: And so what do you do with that? 00:17:40.490 --> 00:17:41.330 align:middle line:90% Where do you go? 00:17:41.330 --> 00:17:44.920 align:middle line:84% There are three totally green sources of energy 00:17:44.920 --> 00:17:47.410 align:middle line:84% that my colleagues tell me right now that 00:17:47.410 --> 00:17:50.120 align:middle line:90% are not in the renewable space. 00:17:50.120 --> 00:17:53.270 align:middle line:84% Obviously, solar, wind, hydro is important. 00:17:53.270 --> 00:17:55.340 align:middle line:84% But they're not always there when we need it. 00:17:55.340 --> 00:17:57.430 align:middle line:84% We need to develop better battery technologies. 00:17:57.430 --> 00:17:58.640 align:middle line:90% And that's all happening. 00:17:58.640 --> 00:18:01.250 align:middle line:84% That's good, but again, not enough. 00:18:01.250 --> 00:18:04.190 align:middle line:84% So if we want to speed up the process of energy addition, 00:18:04.190 --> 00:18:05.697 align:middle line:84% we need new sources of green energy. 00:18:05.697 --> 00:18:06.530 align:middle line:90% And there are three. 00:18:06.530 --> 00:18:11.140 align:middle line:84% There's nuclear fission, nuclear fusion, and geothermal. 00:18:11.140 --> 00:18:15.440 align:middle line:84% And all of these should be areas that we pursue. 00:18:15.440 --> 00:18:18.010 align:middle line:84% And so imagine if we could support 00:18:18.010 --> 00:18:20.140 align:middle line:84% all sorts of different investment projects 00:18:20.140 --> 00:18:24.160 align:middle line:84% in all three areas and really make a concerted effort 00:18:24.160 --> 00:18:26.880 align:middle line:84% to develop these new sources of green energy. 00:18:26.880 --> 00:18:29.790 align:middle line:84% That's an example of what finance can do. 00:18:29.790 --> 00:18:32.930 align:middle line:84% But we need to develop the political will 00:18:32.930 --> 00:18:34.170 align:middle line:90% to be able to do that. 00:18:34.170 --> 00:18:37.460 align:middle line:84% And even part of that can be hastened by finance, 00:18:37.460 --> 00:18:40.250 align:middle line:84% because if you can show that governments can actually 00:18:40.250 --> 00:18:43.010 align:middle line:84% save money in the long run by investing in these, if they can 00:18:43.010 --> 00:18:45.365 align:middle line:84% get a good rate of return on these investments, 00:18:45.365 --> 00:18:47.990 align:middle line:84% they're much more likely to be able to write the checks that we 00:18:47.990 --> 00:18:48.588 align:middle line:90% need now. 00:18:48.588 --> 00:18:49.380 align:middle line:90% SARAH HANSEN: Yeah. 00:18:49.380 --> 00:18:51.360 align:middle line:84% It really does all come down to money. 00:18:51.360 --> 00:18:54.020 align:middle line:84% ANDREW LO: Unfortunately, in most cases, 00:18:54.020 --> 00:18:55.730 align:middle line:90% that seems to be true. 00:18:55.730 --> 00:18:59.070 align:middle line:84% But fortunately, the world has become wealthier. 00:18:59.070 --> 00:19:02.300 align:middle line:84% And largely, that's happened because of industrialization 00:19:02.300 --> 00:19:04.370 align:middle line:84% and the innovations in technology 00:19:04.370 --> 00:19:06.410 align:middle line:90% that we have pioneered. 00:19:06.410 --> 00:19:08.990 align:middle line:84% But the wealth is not equally spread. 00:19:08.990 --> 00:19:10.740 align:middle line:84% There's definitely winners and losers. 00:19:10.740 --> 00:19:13.370 align:middle line:84% And I would argue that the wealth is not necessarily 00:19:13.370 --> 00:19:16.730 align:middle line:84% being allocated in the most efficient way. 00:19:16.730 --> 00:19:19.050 align:middle line:84% If we were to change some of that allocation, 00:19:19.050 --> 00:19:21.450 align:middle line:84% we could actually get better outcomes for everybody. 00:19:21.450 --> 00:19:22.770 align:middle line:90% Nobody has to lose. 00:19:22.770 --> 00:19:26.100 align:middle line:84% SARAH HANSEN: So it all sounds so logical when you explain it. 00:19:26.100 --> 00:19:29.340 align:middle line:90% But then you introduce humans. 00:19:29.340 --> 00:19:31.350 align:middle line:90% Talk to me about humans. 00:19:31.350 --> 00:19:35.730 align:middle line:84% ANDREW LO: Human behavior is one of the most interesting and most 00:19:35.730 --> 00:19:40.740 align:middle line:84% confounding aspects of what I do in finance, because we can write 00:19:40.740 --> 00:19:43.080 align:middle line:84% down all these wonderful equations that 00:19:43.080 --> 00:19:45.450 align:middle line:84% predict various kinds of opportunities 00:19:45.450 --> 00:19:47.320 align:middle line:90% for financial investments. 00:19:47.320 --> 00:19:50.790 align:middle line:84% But at the end of the day, you're talking about people. 00:19:50.790 --> 00:19:52.210 align:middle line:90% And people can react. 00:19:52.210 --> 00:19:53.760 align:middle line:90% Sometimes they can overreact. 00:19:53.760 --> 00:19:56.170 align:middle line:84% For example, during the pandemic, 00:19:56.170 --> 00:19:59.700 align:middle line:84% the stock market lost something like 30% 00:19:59.700 --> 00:20:01.890 align:middle line:90% in a matter of a few days. 00:20:01.890 --> 00:20:05.560 align:middle line:84% And if most of your retirement is tied up in the stock market, 00:20:05.560 --> 00:20:07.410 align:middle line:90% that was a really big hit. 00:20:07.410 --> 00:20:10.810 align:middle line:84% So a number of people responded by what? 00:20:10.810 --> 00:20:13.060 align:middle line:84% By pulling out their money from the stock market, 00:20:13.060 --> 00:20:14.820 align:middle line:90% putting it in cash. 00:20:14.820 --> 00:20:18.070 align:middle line:84% That, in and of itself, is not necessarily a bad decision. 00:20:18.070 --> 00:20:20.410 align:middle line:84% The problem is that many of these individuals, 00:20:20.410 --> 00:20:22.170 align:middle line:84% they took too long to put the money back 00:20:22.170 --> 00:20:23.240 align:middle line:90% into the stock market. 00:20:23.240 --> 00:20:25.180 align:middle line:84% And they missed the rebound, which 00:20:25.180 --> 00:20:28.970 align:middle line:84% actually happened just a few weeks after that 30% decline. 00:20:28.970 --> 00:20:30.470 align:middle line:90% The market went right back up. 00:20:30.470 --> 00:20:34.840 align:middle line:84% And if you had taken a vacation between middle of March 2020 00:20:34.840 --> 00:20:37.840 align:middle line:84% and middle of June 2020-- if you had taken a vacation 00:20:37.840 --> 00:20:39.760 align:middle line:84% and done nothing, you would not even 00:20:39.760 --> 00:20:41.720 align:middle line:84% have noticed that the stock market moved. 00:20:41.720 --> 00:20:43.780 align:middle line:84% It just went down and then back up. 00:20:43.780 --> 00:20:47.680 align:middle line:84% So I think that understanding these kind of dynamics 00:20:47.680 --> 00:20:51.880 align:middle line:84% is important, because we often allow ourselves 00:20:51.880 --> 00:20:54.800 align:middle line:84% to engage in behaviors that can be really counterproductive. 00:20:54.800 --> 00:20:57.890 align:middle line:84% And that's part of what I do as a finance professional, 00:20:57.890 --> 00:21:01.340 align:middle line:84% is to understand how human behavior factors into this. 00:21:01.340 --> 00:21:06.790 align:middle line:84% And it's amazing how bad we are as Homo sapiens 00:21:06.790 --> 00:21:08.388 align:middle line:90% in managing our finances. 00:21:08.388 --> 00:21:10.430 align:middle line:84% And that's one of the reasons why I do what I do. 00:21:10.430 --> 00:21:11.690 align:middle line:90% And I'm really excited about it. 00:21:11.690 --> 00:21:12.482 align:middle line:90% SARAH HANSEN: Yeah. 00:21:12.482 --> 00:21:14.090 align:middle line:90% You have a hypothesis. 00:21:14.090 --> 00:21:15.670 align:middle line:90% What is it called? 00:21:15.670 --> 00:21:19.700 align:middle line:84% ANDREW LO: So my hypothesis is the Adaptive Markets Hypothesis. 00:21:19.700 --> 00:21:22.700 align:middle line:84% And it was developed in contrast to one 00:21:22.700 --> 00:21:24.470 align:middle line:84% of the most popular theories in my field, 00:21:24.470 --> 00:21:26.810 align:middle line:84% called the Efficient Market Hypothesis. 00:21:26.810 --> 00:21:30.200 align:middle line:84% That's a theory that says that markets, always and everywhere, 00:21:30.200 --> 00:21:32.190 align:middle line:84% reflect all available information. 00:21:32.190 --> 00:21:35.000 align:middle line:84% And that means that the prices that you see 00:21:35.000 --> 00:21:37.220 align:middle line:90% are generally correct. 00:21:37.220 --> 00:21:39.920 align:middle line:84% And it turns out that the efficient market hypothesis 00:21:39.920 --> 00:21:41.190 align:middle line:90% is not wrong. 00:21:41.190 --> 00:21:43.520 align:middle line:84% It actually works most of the time. 00:21:43.520 --> 00:21:45.300 align:middle line:90% But it's not complete. 00:21:45.300 --> 00:21:47.010 align:middle line:90% It doesn't work all the time. 00:21:47.010 --> 00:21:48.500 align:middle line:84% And for the times when it doesn't 00:21:48.500 --> 00:21:51.680 align:middle line:84% work, where human behavior overwhelms the rationality 00:21:51.680 --> 00:21:53.460 align:middle line:84% that you typically see in the markets, 00:21:53.460 --> 00:21:55.430 align:middle line:84% that's where you need to understand 00:21:55.430 --> 00:21:57.710 align:middle line:84% how the mechanics of human behavior 00:21:57.710 --> 00:22:01.020 align:middle line:84% interacts with the beautiful logic of financial markets. 00:22:01.020 --> 00:22:02.850 align:middle line:84% That's the adaptive markets hypothesis. 00:22:02.850 --> 00:22:03.642 align:middle line:90% SARAH HANSEN: Yeah. 00:22:03.642 --> 00:22:05.960 align:middle line:84% So as a fellow human, what can I do 00:22:05.960 --> 00:22:09.900 align:middle line:84% to counteract my own irrational tendencies? 00:22:09.900 --> 00:22:11.510 align:middle line:84% ANDREW LO: Well, the first step is 00:22:11.510 --> 00:22:13.650 align:middle line:84% to recognize that this is an issue. 00:22:13.650 --> 00:22:17.820 align:middle line:84% So if you recognize that we all have this problem, 00:22:17.820 --> 00:22:19.950 align:middle line:84% that's the first step in recovery, 00:22:19.950 --> 00:22:22.090 align:middle line:84% in trying to understand how to deal with it. 00:22:22.090 --> 00:22:27.400 align:middle line:84% The second step is to do scenario analyses in our brain. 00:22:27.400 --> 00:22:30.970 align:middle line:84% One of the most magnificent gifts of human evolution 00:22:30.970 --> 00:22:34.140 align:middle line:84% is the ability to engage in abstract thought, 00:22:34.140 --> 00:22:35.370 align:middle line:90% in hypotheticals. 00:22:35.370 --> 00:22:38.250 align:middle line:84% We can hold in our mind all sorts of "what ifs." 00:22:38.250 --> 00:22:40.690 align:middle line:84% Of what if I decided not to go to work today? 00:22:40.690 --> 00:22:41.710 align:middle line:90% What would happen then? 00:22:41.710 --> 00:22:44.560 align:middle line:84% What if I decided to become a doctor, a lawyer? 00:22:44.560 --> 00:22:47.490 align:middle line:84% What if I decided to save money so 00:22:47.490 --> 00:22:48.850 align:middle line:90% that my kids can go to college? 00:22:48.850 --> 00:22:53.580 align:middle line:84% Those kinds of "what ifs," we can often work out in reasonable 00:22:53.580 --> 00:22:57.060 align:middle line:84% detail in our heads and then pick the "what if" that is 00:22:57.060 --> 00:22:58.260 align:middle line:90% the most attractive. 00:22:58.260 --> 00:23:01.440 align:middle line:84% So right now, if we're not in the middle of a financial 00:23:01.440 --> 00:23:04.180 align:middle line:84% crisis, we can do "what if" and say, 00:23:04.180 --> 00:23:08.070 align:middle line:84% what if it turns out that the stock market crashes by 20%? 00:23:08.070 --> 00:23:10.268 align:middle line:84% Given my age, given the likelihood 00:23:10.268 --> 00:23:12.060 align:middle line:84% that it's going to come back, because based 00:23:12.060 --> 00:23:14.170 align:middle line:84% on the last hundred years of history, 00:23:14.170 --> 00:23:17.050 align:middle line:84% when the markets go down, eventually they go back up-- 00:23:17.050 --> 00:23:17.930 align:middle line:90% it takes a while. 00:23:17.930 --> 00:23:20.420 align:middle line:84% But we can actually see when things are recovering. 00:23:20.420 --> 00:23:23.600 align:middle line:84% What if I decided not to sell out everything? 00:23:23.600 --> 00:23:26.420 align:middle line:84% What if I decided to wait and see how things go? 00:23:26.420 --> 00:23:29.480 align:middle line:84% What if I were to wait two years, three years, five years? 00:23:29.480 --> 00:23:30.770 align:middle line:90% Can I afford to wait? 00:23:30.770 --> 00:23:33.710 align:middle line:84% By doing those kinds of "what if" analyses, 00:23:33.710 --> 00:23:36.460 align:middle line:84% we can go a long way towards preparing for these kinds 00:23:36.460 --> 00:23:37.300 align:middle line:90% of events. 00:23:37.300 --> 00:23:40.130 align:middle line:84% And this is where financial planners are really helpful. 00:23:40.130 --> 00:23:42.280 align:middle line:84% They have a lot more sophisticated "what ifs" 00:23:42.280 --> 00:23:45.020 align:middle line:84% than you and I might be able to come up on our own. 00:23:45.020 --> 00:23:48.850 align:middle line:84% And there, I think, we can get AI to play a role, 00:23:48.850 --> 00:23:51.770 align:middle line:84% because AI now, with large language models, 00:23:51.770 --> 00:23:54.880 align:middle line:84% are remarkably good at coming up with all sorts of interesting 00:23:54.880 --> 00:23:55.760 align:middle line:90% "what ifs." 00:23:55.760 --> 00:24:00.190 align:middle line:84% And so to be forearmed is to be-- to be forewarned 00:24:00.190 --> 00:24:01.550 align:middle line:90% is to be forearmed. 00:24:01.550 --> 00:24:04.540 align:middle line:84% SARAH HANSEN: We have a lot of YouTube comments pointing out 00:24:04.540 --> 00:24:09.010 align:middle line:84% that you tend to make finance very accessible 00:24:09.010 --> 00:24:10.670 align:middle line:90% through your lectures. 00:24:10.670 --> 00:24:13.510 align:middle line:84% And I'm wondering if you could articulate 00:24:13.510 --> 00:24:17.210 align:middle line:84% what it is you think you do that opens the door for students 00:24:17.210 --> 00:24:19.400 align:middle line:84% in your classes and around the world when they watch 00:24:19.400 --> 00:24:21.357 align:middle line:90% your OpenCourseWare videos. 00:24:21.357 --> 00:24:23.940 align:middle line:84% ANDREW LO: Well, first of all, thank you for that observation. 00:24:23.940 --> 00:24:27.780 align:middle line:84% I'm really humbled and grateful for that. 00:24:27.780 --> 00:24:31.220 align:middle line:84% If that's true, it's because I often 00:24:31.220 --> 00:24:35.670 align:middle line:84% develop my lectures with an eye towards being a student myself. 00:24:35.670 --> 00:24:38.740 align:middle line:84% I was a high school student in New York City at the Bronx High 00:24:38.740 --> 00:24:39.490 align:middle line:90% School of Science. 00:24:39.490 --> 00:24:42.530 align:middle line:84% It's a school that specializes in STEM, 00:24:42.530 --> 00:24:45.380 align:middle line:84% and a wonderful education that money 00:24:45.380 --> 00:24:47.430 align:middle line:84% didn't need to buy because it's public school. 00:24:47.430 --> 00:24:51.110 align:middle line:84% And I learned more from my classmates in Bronx Science 00:24:51.110 --> 00:24:53.690 align:middle line:84% than I think I did from any other time 00:24:53.690 --> 00:24:54.780 align:middle line:90% in my educational career. 00:24:54.780 --> 00:24:56.070 align:middle line:90% It's a phenomenal school. 00:24:56.070 --> 00:24:57.980 align:middle line:84% But one of the things that I learned from Bronx Science that 00:24:57.980 --> 00:25:00.230 align:middle line:84% wasn't quite right-- and this is my own fault-- 00:25:00.230 --> 00:25:04.250 align:middle line:84% I identified intelligence with STEM. 00:25:04.250 --> 00:25:07.650 align:middle line:84% So if you were smart at Bronx Science, 00:25:07.650 --> 00:25:09.660 align:middle line:84% that meant you were good at science and math. 00:25:09.660 --> 00:25:12.210 align:middle line:84% I mean, we had history, English, social studies, 00:25:12.210 --> 00:25:13.480 align:middle line:90% all of those other fields. 00:25:13.480 --> 00:25:17.830 align:middle line:84% But those weren't the real focus of the kids that went there. 00:25:17.830 --> 00:25:20.620 align:middle line:84% You went there because you wanted to study science, math, 00:25:20.620 --> 00:25:21.410 align:middle line:90% and engineering. 00:25:21.410 --> 00:25:25.390 align:middle line:84% And it wasn't until I got to college that I was completely 00:25:25.390 --> 00:25:27.280 align:middle line:90% disabused of that notion. 00:25:27.280 --> 00:25:29.950 align:middle line:84% And it happened because I met somebody 00:25:29.950 --> 00:25:32.990 align:middle line:90% who was completely innumerate. 00:25:32.990 --> 00:25:36.520 align:middle line:84% I mean, he wasn't even able to take the introductory math 00:25:36.520 --> 00:25:40.760 align:middle line:84% class in college and needed my help to get through it. 00:25:40.760 --> 00:25:43.070 align:middle line:84% And so I would tutor him every once in a while. 00:25:43.070 --> 00:25:45.290 align:middle line:90% And he would eventually learn. 00:25:45.290 --> 00:25:46.480 align:middle line:90% But it took him a while. 00:25:46.480 --> 00:25:47.690 align:middle line:90% And it was never easy. 00:25:47.690 --> 00:25:49.840 align:middle line:84% He really sweated it out, and ultimately, I 00:25:49.840 --> 00:25:52.982 align:middle line:84% think, passed with a C or something. 00:25:52.982 --> 00:25:55.190 align:middle line:84% SARAH HANSEN: I may or may not have been that person, 00:25:55.190 --> 00:25:56.380 align:middle line:90% but go ahead. 00:25:56.380 --> 00:25:59.680 align:middle line:84% ANDREW LO: Well, the thing about that person 00:25:59.680 --> 00:26:02.410 align:middle line:84% is that he was one of the smartest people I ever 00:26:02.410 --> 00:26:03.820 align:middle line:90% met in college. 00:26:03.820 --> 00:26:05.620 align:middle line:90% And I didn't expect that. 00:26:05.620 --> 00:26:07.340 align:middle line:84% And let me explain what I mean by that. 00:26:07.340 --> 00:26:08.720 align:middle line:90% We'd be sitting at dinner. 00:26:08.720 --> 00:26:13.020 align:middle line:84% And no matter what the topic of conversation was-- 00:26:13.020 --> 00:26:16.880 align:middle line:84% politics, religion, music-- anything 00:26:16.880 --> 00:26:20.360 align:middle line:84% that you would talk about other than mathematics, 00:26:20.360 --> 00:26:24.470 align:middle line:84% he was just incredibly well informed, articulate, 00:26:24.470 --> 00:26:27.295 align:middle line:90% and extraordinarily analytical. 00:26:27.295 --> 00:26:29.480 align:middle line:84% And so that really threw me for a loop, 00:26:29.480 --> 00:26:33.800 align:middle line:84% because again, analytical, math, but not in his brain. 00:26:33.800 --> 00:26:35.790 align:middle line:84% So he ultimately went to law school, 00:26:35.790 --> 00:26:39.060 align:middle line:84% became a very, very well-respected attorney. 00:26:39.060 --> 00:26:43.310 align:middle line:84% And he could argue anybody into the ground 00:26:43.310 --> 00:26:47.090 align:middle line:84% because he had a mind sharp as a razor blade. 00:26:47.090 --> 00:26:49.490 align:middle line:84% How is it possible that somebody could 00:26:49.490 --> 00:26:51.732 align:middle line:90% be so smart and yet innumerate? 00:26:51.732 --> 00:26:53.190 align:middle line:84% That was a big wake-up call for me. 00:26:53.190 --> 00:26:55.910 align:middle line:84% And it pointed out the fact that there are different kinds 00:26:55.910 --> 00:26:57.210 align:middle line:90% of intelligence. 00:26:57.210 --> 00:27:00.290 align:middle line:84% So up until recently, when we think 00:27:00.290 --> 00:27:03.300 align:middle line:84% about artificial intelligence and computation, 00:27:03.300 --> 00:27:06.080 align:middle line:84% it's all computational, quantitative. 00:27:06.080 --> 00:27:07.128 align:middle line:90% For the very first time-- 00:27:07.128 --> 00:27:09.170 align:middle line:84% and this is why I think large language models are 00:27:09.170 --> 00:27:11.430 align:middle line:84% such a breakthrough-- we are now confronted 00:27:11.430 --> 00:27:15.010 align:middle line:84% with a very different kind of artificial intelligence. 00:27:15.010 --> 00:27:18.640 align:middle line:84% This is intelligence that is like my friend in college. 00:27:18.640 --> 00:27:23.310 align:middle line:84% It becomes analytical, but in a way that uses language, not 00:27:23.310 --> 00:27:24.850 align:middle line:90% numbers and equations. 00:27:24.850 --> 00:27:27.540 align:middle line:84% And so I think that large language models 00:27:27.540 --> 00:27:30.640 align:middle line:84% is a different type of AI than what we're used to. 00:27:30.640 --> 00:27:32.440 align:middle line:84% That's what makes it so powerful. 00:27:32.440 --> 00:27:34.290 align:middle line:84% But it does have some weaknesses, just 00:27:34.290 --> 00:27:36.210 align:middle line:84% like my friend, who, if you asked 00:27:36.210 --> 00:27:38.800 align:middle line:84% him to prove a very simple theorem in calculus, 00:27:38.800 --> 00:27:40.830 align:middle line:90% he'd sweat bullets doing it. 00:27:40.830 --> 00:27:44.440 align:middle line:84% But he was incredibly intelligent in other ways. 00:27:44.440 --> 00:27:47.520 align:middle line:84% And so I think that opens up all sorts of new insights for me 00:27:47.520 --> 00:27:50.590 align:middle line:84% in terms of my own students and myself, 00:27:50.590 --> 00:27:52.200 align:middle line:84% and how we think about intelligence, 00:27:52.200 --> 00:27:55.690 align:middle line:84% and sometimes how limited we are in thinking about intelligence. 00:27:55.690 --> 00:27:59.140 align:middle line:84% We measure intelligence with tests, reading comprehension, 00:27:59.140 --> 00:28:02.950 align:middle line:84% vocabulary, and mathematical problems. 00:28:02.950 --> 00:28:06.348 align:middle line:84% But I wonder if there's many forms of intelligence 00:28:06.348 --> 00:28:08.140 align:middle line:84% that we are not capturing with those tests, 00:28:08.140 --> 00:28:09.880 align:middle line:84% and there are whole swaths of society 00:28:09.880 --> 00:28:13.100 align:middle line:84% that we have somehow neglected and underappreciated 00:28:13.100 --> 00:28:15.370 align:middle line:84% because they have an intelligence that we don't 00:28:15.370 --> 00:28:17.290 align:middle line:84% know about, we can't measure, but we really 00:28:17.290 --> 00:28:18.490 align:middle line:90% could benefit from. 00:28:18.490 --> 00:28:20.615 align:middle line:84% SARAH HANSEN: Well, I couldn't agree with you more. 00:28:20.615 --> 00:28:22.640 align:middle line:84% I used to be an elementary school teacher. 00:28:22.640 --> 00:28:26.290 align:middle line:84% So I saw the ways in which schools pinpoint intelligence, 00:28:26.290 --> 00:28:29.560 align:middle line:84% and measure it, and leave out large groups of people. 00:28:29.560 --> 00:28:31.250 align:middle line:90% So we're on the same page there. 00:28:31.250 --> 00:28:33.208 align:middle line:84% ANDREW LO: Well, speaking of elementary school, 00:28:33.208 --> 00:28:36.310 align:middle line:84% that was one of the important and formative experiences 00:28:36.310 --> 00:28:37.310 align:middle line:90% of my life. 00:28:37.310 --> 00:28:42.430 align:middle line:84% It turns out that, in retrospect, I 00:28:42.430 --> 00:28:44.560 align:middle line:90% have a learning issue. 00:28:44.560 --> 00:28:48.033 align:middle line:84% It's the mathematical equivalent of dyslexia, dyscalculia. 00:28:48.033 --> 00:28:48.950 align:middle line:90% SARAH HANSEN: You do?! 00:28:48.950 --> 00:28:49.690 align:middle line:90% ANDREW LO: Yes. 00:28:49.690 --> 00:28:50.660 align:middle line:90% SARAH HANSEN: Wow. 00:28:50.660 --> 00:28:52.850 align:middle line:90% That is so surprising. 00:28:52.850 --> 00:28:55.340 align:middle line:84% ANDREW LO: Well, people say that because of what I do now. 00:28:55.340 --> 00:28:55.840 align:middle line:90% Yeah. 00:28:55.840 --> 00:28:59.840 align:middle line:84% But it was definitely the case that math was my worst subject. 00:28:59.840 --> 00:29:03.890 align:middle line:84% And for an Asian growing up in New York City in the 1970s, 00:29:03.890 --> 00:29:05.090 align:middle line:90% that was not easy. 00:29:05.090 --> 00:29:05.840 align:middle line:90% SARAH HANSEN: Wow. 00:29:05.840 --> 00:29:10.640 align:middle line:84% ANDREW LO: So it wasn't until I went to the third grade 00:29:10.640 --> 00:29:16.230 align:middle line:84% that I finally found a teacher that recognized something in me, 00:29:16.230 --> 00:29:20.340 align:middle line:84% Mrs. Barbara Ficalora, third grade, PS 13 in Queens. 00:29:20.340 --> 00:29:24.470 align:middle line:84% And she knew that I was struggling with math. 00:29:24.470 --> 00:29:27.600 align:middle line:84% But yet, she also saw that I was really curious. 00:29:27.600 --> 00:29:30.510 align:middle line:84% I would always enjoy going to the library. 00:29:30.510 --> 00:29:32.900 align:middle line:84% Once a week, I would take out a stack of science books, 00:29:32.900 --> 00:29:35.730 align:middle line:84% and read them, and be really interested in that. 00:29:35.730 --> 00:29:40.220 align:middle line:84% And so she tried to boost my confidence by making 00:29:40.220 --> 00:29:42.243 align:middle line:90% me the class scientist. 00:29:42.243 --> 00:29:44.160 align:middle line:84% Now, I didn't know that that position existed. 00:29:44.160 --> 00:29:45.690 align:middle line:90% I certainly didn't apply for it. 00:29:45.690 --> 00:29:48.530 align:middle line:84% But what it meant was that I got to demonstrate 00:29:48.530 --> 00:29:50.900 align:middle line:84% one of these science experiments that I was concocting 00:29:50.900 --> 00:29:54.290 align:middle line:84% at the back of the room every free period I could get, 00:29:54.290 --> 00:29:59.480 align:middle line:84% and just talk to the whole class about how to make a battery out 00:29:59.480 --> 00:30:02.730 align:middle line:90% of lemons and magnets. 00:30:02.730 --> 00:30:04.540 align:middle line:84% And I think it was that experience that 00:30:04.540 --> 00:30:07.910 align:middle line:84% allowed me to get through my elementary years, 00:30:07.910 --> 00:30:09.700 align:middle line:84% despite the fact that other teachers 00:30:09.700 --> 00:30:12.640 align:middle line:84% that I had who were not so supportive-- 00:30:12.640 --> 00:30:16.670 align:middle line:84% were pretty discouraging to me and to my mother. 00:30:16.670 --> 00:30:18.070 align:middle line:84% Back then, there was no diagnosis 00:30:18.070 --> 00:30:21.640 align:middle line:90% of ADHD or dyscalculia. 00:30:21.640 --> 00:30:26.410 align:middle line:84% So, I basically soldiered on until I went to high school 00:30:26.410 --> 00:30:28.990 align:middle line:84% at that Bronx High School of Science I mentioned. 00:30:28.990 --> 00:30:32.350 align:middle line:84% That was in the 1970s, when New York City was undergoing this 00:30:32.350 --> 00:30:34.383 align:middle line:84% radical experiment called the New Math. 00:30:34.383 --> 00:30:36.050 align:middle line:84% I don't know if you've heard about that. 00:30:36.050 --> 00:30:39.580 align:middle line:84% But it was a widely renowned failure, 00:30:39.580 --> 00:30:44.360 align:middle line:84% because it was replacing the basic concepts of algebra, 00:30:44.360 --> 00:30:48.160 align:middle line:84% geometry, and trigonometry with all these mathematical concepts 00:30:48.160 --> 00:30:50.540 align:middle line:84% of groups, rings, fields, isomorphisms, 00:30:50.540 --> 00:30:52.030 align:middle line:90% and other transformations. 00:30:52.030 --> 00:30:55.480 align:middle line:84% And while, mathematically, it was more rigorous 00:30:55.480 --> 00:30:57.830 align:middle line:84% and intellectually more pleasing, 00:30:57.830 --> 00:31:00.130 align:middle line:84% most of the New York City school teachers 00:31:00.130 --> 00:31:02.750 align:middle line:84% were not prepared to teach in this way. 00:31:02.750 --> 00:31:06.890 align:middle line:84% And so, for most schools, it was really a failure. 00:31:06.890 --> 00:31:10.250 align:middle line:84% But for me, it was night and day. 00:31:10.250 --> 00:31:14.658 align:middle line:84% I came from being a C student in math to an A student overnight. 00:31:14.658 --> 00:31:17.200 align:middle line:84% SARAH HANSEN: Because it was more analytical and less focused 00:31:17.200 --> 00:31:17.710 align:middle line:90% on-- 00:31:17.710 --> 00:31:18.580 align:middle line:90% ANDREW LO: Numbers. 00:31:18.580 --> 00:31:19.930 align:middle line:90% No numbers. 00:31:19.930 --> 00:31:22.490 align:middle line:84% To this day, I have a hard time memorizing numbers. 00:31:22.490 --> 00:31:25.090 align:middle line:84% I never memorized the multiplication tables. 00:31:25.090 --> 00:31:26.840 align:middle line:84% I still have trouble with 6 times 7. 00:31:26.840 --> 00:31:29.030 align:middle line:84% I have to actually do the calculation in my head. 00:31:29.030 --> 00:31:31.810 align:middle line:84% And it takes me a little bit longer than most people. 00:31:31.810 --> 00:31:34.520 align:middle line:84% But when you replace numbers with equations, 00:31:34.520 --> 00:31:37.040 align:middle line:90% that was like a huge relief. 00:31:37.040 --> 00:31:39.832 align:middle line:84% It's like wearing shoes that are two sizes too small. 00:31:39.832 --> 00:31:41.290 align:middle line:84% And then you take them off, and you 00:31:41.290 --> 00:31:43.700 align:middle line:84% put on shoes that are just exactly the right size. 00:31:43.700 --> 00:31:44.780 align:middle line:90% It felt wonderful. 00:31:44.780 --> 00:31:46.300 align:middle line:84% And because I struggled as a student 00:31:46.300 --> 00:31:48.130 align:middle line:84% with my own learning issues, I could 00:31:48.130 --> 00:31:52.000 align:middle line:84% tell the difference between good teaching and bad teaching. 00:31:52.000 --> 00:31:55.760 align:middle line:84% And of course, for a while, I blamed it on myself. 00:31:55.760 --> 00:31:58.630 align:middle line:84% But then, once I learned a bit more about my own learning 00:31:58.630 --> 00:32:02.900 align:middle line:84% issues, I began to understand what certain things would 00:32:02.900 --> 00:32:06.230 align:middle line:84% allow me to see a concept versus other things 00:32:06.230 --> 00:32:07.590 align:middle line:90% that would confuse me. 00:32:07.590 --> 00:32:11.210 align:middle line:84% Now, when I write my lectures, I often 00:32:11.210 --> 00:32:14.270 align:middle line:84% have to step into the student's role and ask myself, 00:32:14.270 --> 00:32:17.840 align:middle line:84% if I didn't know anything about this, what would be the fastest 00:32:17.840 --> 00:32:21.320 align:middle line:84% way to get me to have some kind of a grasp of what 00:32:21.320 --> 00:32:23.430 align:middle line:90% it is that I'm trying to teach? 00:32:23.430 --> 00:32:25.710 align:middle line:84% And again, looking at it from my own lens. 00:32:25.710 --> 00:32:28.250 align:middle line:84% The other part is that I've had the great gift 00:32:28.250 --> 00:32:31.170 align:middle line:84% of having a number of really incredible teachers. 00:32:31.170 --> 00:32:32.670 align:middle line:84% When I was a high school student, 00:32:32.670 --> 00:32:36.590 align:middle line:84% my calculus teacher, Mrs. Henrietta Mason, was amazing. 00:32:36.590 --> 00:32:39.870 align:middle line:84% When I was a college student, Saul Levmore, Sharon Oster, 00:32:39.870 --> 00:32:41.540 align:middle line:90% Herb Scarf, amazing. 00:32:41.540 --> 00:32:45.620 align:middle line:84% As a graduate student, Andy Abel, Jerry Houseman-- 00:32:45.620 --> 00:32:48.620 align:middle line:84% I remember all of these teachers' names. 00:32:48.620 --> 00:32:51.000 align:middle line:84% It's because they just made a huge impact on me. 00:32:51.000 --> 00:32:52.610 align:middle line:90% They changed my life. 00:32:52.610 --> 00:32:56.780 align:middle line:84% And so part of why I spend time on teaching-- and I think this 00:32:56.780 --> 00:32:57.950 align:middle line:90% is another aspect. 00:32:57.950 --> 00:33:00.840 align:middle line:84% Some of my colleagues are so focused on research 00:33:00.840 --> 00:33:02.700 align:middle line:84% that they feel like they can't afford 00:33:02.700 --> 00:33:04.270 align:middle line:90% to spend time on teaching. 00:33:04.270 --> 00:33:07.000 align:middle line:84% But because I remember what it was like as a student 00:33:07.000 --> 00:33:11.010 align:middle line:84% when faculty didn't take the time to try to explain something 00:33:11.010 --> 00:33:13.150 align:middle line:84% in a way that would be more understandable, 00:33:13.150 --> 00:33:16.240 align:middle line:84% I decided to spend the time on working on my lectures. 00:33:16.240 --> 00:33:19.440 align:middle line:84% Someone once said that great writing is not 00:33:19.440 --> 00:33:22.480 align:middle line:84% writing so that other people can understand. 00:33:22.480 --> 00:33:25.080 align:middle line:84% It's writing so that other people cannot possibly 00:33:25.080 --> 00:33:25.720 align:middle line:90% misunderstand. 00:33:25.720 --> 00:33:27.220 align:middle line:84% SARAH HANSEN: Oh, that's a good one. 00:33:27.220 --> 00:33:27.887 align:middle line:90% ANDREW LO: Yeah. 00:33:27.887 --> 00:33:31.500 align:middle line:84% That's a very difficult standard to adhere to. 00:33:31.500 --> 00:33:33.250 align:middle line:84% But I think that's the same with teaching. 00:33:33.250 --> 00:33:37.110 align:middle line:84% Teaching is lecturing so that students cannot possibly 00:33:37.110 --> 00:33:38.530 align:middle line:90% misunderstand. 00:33:38.530 --> 00:33:40.660 align:middle line:84% And that does take a little bit more time. 00:33:40.660 --> 00:33:45.040 align:middle line:84% But when you are able to land a concept with an audience, 00:33:45.040 --> 00:33:48.090 align:middle line:84% there is no better feeling, from my perspective. 00:33:48.090 --> 00:33:50.340 align:middle line:84% It is like, I don't know, gymnasts 00:33:50.340 --> 00:33:53.100 align:middle line:84% hitting a perfect landing, ice skaters 00:33:53.100 --> 00:33:55.710 align:middle line:84% being able to do a triple axel without falling. 00:33:55.710 --> 00:34:00.700 align:middle line:84% For me, that is just an incredible feeling, a rush, 00:34:00.700 --> 00:34:04.160 align:middle line:84% that I can communicate something that somebody didn't understand. 00:34:04.160 --> 00:34:06.110 align:middle line:90% And now their faces light up. 00:34:06.110 --> 00:34:07.451 align:middle line:90% And I get it now. 00:34:07.451 --> 00:34:08.409 align:middle line:90% And they will forever-- 00:34:08.409 --> 00:34:09.880 align:middle line:84% from that point, they will forever 00:34:09.880 --> 00:34:13.159 align:middle line:84% have that to use and to benefit from. 00:34:13.159 --> 00:34:17.469 align:middle line:84% And also, one of the things that makes me particularly 00:34:17.469 --> 00:34:21.620 align:middle line:84% grateful to OpenCourseWare is that it is the great equalizer. 00:34:21.620 --> 00:34:26.565 align:middle line:84% There are so many people that can't learn on a schedule 00:34:26.565 --> 00:34:27.940 align:middle line:84% and that have all sorts of issues 00:34:27.940 --> 00:34:31.690 align:middle line:84% that don't allow them to excel in a classroom with 30 00:34:31.690 --> 00:34:32.690 align:middle line:90% other kids. 00:34:32.690 --> 00:34:35.090 align:middle line:84% And yet they're perfectly intelligent, 00:34:35.090 --> 00:34:36.790 align:middle line:84% in some cases, super intelligent. 00:34:36.790 --> 00:34:38.120 align:middle line:90% But they have these challenges. 00:34:38.120 --> 00:34:41.330 align:middle line:84% OpenCourseWare gives them a platform, at least, 00:34:41.330 --> 00:34:43.280 align:middle line:84% to be able to learn at their own pace, 00:34:43.280 --> 00:34:45.563 align:middle line:84% to be able to stop the video, to think about it, 00:34:45.563 --> 00:34:47.230 align:middle line:84% to start it up again when they're ready. 00:34:47.230 --> 00:34:49.188 align:middle line:84% And there's nobody looking over their shoulder, 00:34:49.188 --> 00:34:51.800 align:middle line:84% seeing how well they're doing relative to their competitors. 00:34:51.800 --> 00:34:55.218 align:middle line:84% It changes the learning field, and I think, 00:34:55.218 --> 00:34:57.010 align:middle line:84% gives opportunities that weren't available. 00:34:57.010 --> 00:34:59.520 align:middle line:84% So I can't tell you how honored I am to be part of this, 00:34:59.520 --> 00:35:01.740 align:middle line:84% and to be part of the institution that came up 00:35:01.740 --> 00:35:04.770 align:middle line:84% with this platform, and basically gave knowledge away 00:35:04.770 --> 00:35:05.950 align:middle line:90% to the rest of the world. 00:35:05.950 --> 00:35:08.472 align:middle line:84% SARAH HANSEN: You brought something with you today. 00:35:08.472 --> 00:35:09.180 align:middle line:90% ANDREW LO: I did. 00:35:09.180 --> 00:35:12.000 align:middle line:84% So when I was asked to come on this program, 00:35:12.000 --> 00:35:15.180 align:middle line:84% you asked me to bring a meaningful memento, something 00:35:15.180 --> 00:35:16.650 align:middle line:90% small that I can carry. 00:35:16.650 --> 00:35:19.540 align:middle line:84% And I have to tell you, that was a terrible assignment. 00:35:19.540 --> 00:35:22.630 align:middle line:84% It took me a long time, because I-- what should I bring? 00:35:22.630 --> 00:35:25.200 align:middle line:84% Little art objects that my kids made that are dear 00:35:25.200 --> 00:35:28.740 align:middle line:90% to me, my high school diploma? 00:35:28.740 --> 00:35:32.190 align:middle line:84% But I decided to bring the most important reason 00:35:32.190 --> 00:35:33.700 align:middle line:90% for where I am today. 00:35:33.700 --> 00:35:35.500 align:middle line:84% And this is a picture of my mother. 00:35:35.500 --> 00:35:36.754 align:middle line:90% SARAH HANSEN: Oh, lovely. 00:35:36.754 --> 00:35:41.700 align:middle line:84% ANDREW LO: So I mentioned that we grew up in New York City. 00:35:41.700 --> 00:35:43.570 align:middle line:84% We were a single-parent household. 00:35:43.570 --> 00:35:50.490 align:middle line:84% She worked one job with overtime to be 00:35:50.490 --> 00:35:52.180 align:middle line:84% able to raise three kids by herself-- 00:35:52.180 --> 00:35:53.440 align:middle line:90% I was the youngest of three-- 00:35:53.440 --> 00:35:56.950 align:middle line:84% and instilled in me and my brother and sister 00:35:56.950 --> 00:36:00.550 align:middle line:84% a love of learning, and the importance of hard work, 00:36:00.550 --> 00:36:04.570 align:middle line:84% and focusing on the longer game as opposed 00:36:04.570 --> 00:36:07.330 align:middle line:84% to short-term issues, which is ironic, 00:36:07.330 --> 00:36:10.720 align:middle line:84% because most of her young life as a mother 00:36:10.720 --> 00:36:14.210 align:middle line:84% was focused on trying to make ends meet. 00:36:14.210 --> 00:36:18.100 align:middle line:84% I would remember conversations about finance pretty much 00:36:18.100 --> 00:36:19.370 align:middle line:90% every single month. 00:36:19.370 --> 00:36:23.620 align:middle line:84% And it was tough, because we did not grow up with a lot. 00:36:23.620 --> 00:36:27.250 align:middle line:90% And she was divorced. 00:36:27.250 --> 00:36:29.890 align:middle line:84% And that was a time when it was very 00:36:29.890 --> 00:36:34.780 align:middle line:84% difficult to survive as a single woman with three kids. 00:36:34.780 --> 00:36:36.800 align:middle line:90% But she did an amazing job. 00:36:36.800 --> 00:36:39.580 align:middle line:90% And so I owe her a lot. 00:36:39.580 --> 00:36:42.590 align:middle line:84% SARAH HANSEN: So if she was here with us now, 00:36:42.590 --> 00:36:48.010 align:middle line:84% what would she say to me about balancing the ends meet 00:36:48.010 --> 00:36:48.943 align:middle line:90% with the long game? 00:36:48.943 --> 00:36:49.610 align:middle line:90% ANDREW LO: Yeah. 00:36:49.610 --> 00:36:53.000 align:middle line:84% Well, I don't know that her advice would be something 00:36:53.000 --> 00:36:56.420 align:middle line:84% that anybody would or could do, because she 00:36:56.420 --> 00:36:59.910 align:middle line:90% sacrificed her career for us. 00:36:59.910 --> 00:37:03.110 align:middle line:84% She was a lawyer by training, left 00:37:03.110 --> 00:37:06.710 align:middle line:84% China when the Communist Revolution took place, 00:37:06.710 --> 00:37:14.690 align:middle line:84% then married someone who was not ideal, an abusive husband, 00:37:14.690 --> 00:37:18.320 align:middle line:84% took a long time for her to see that and get divorced, 00:37:18.320 --> 00:37:19.170 align:middle line:90% as she did. 00:37:19.170 --> 00:37:21.290 align:middle line:90% It was a very messy divorce. 00:37:21.290 --> 00:37:23.540 align:middle line:84% And because he was a foreign national 00:37:23.540 --> 00:37:25.980 align:middle line:84% and ended up being a diplomat, he was also-- 00:37:25.980 --> 00:37:27.740 align:middle line:84% the best thing about that marriage 00:37:27.740 --> 00:37:32.090 align:middle line:84% was that he was an absentee father, because he was abusive 00:37:32.090 --> 00:37:33.320 align:middle line:90% when he was around. 00:37:33.320 --> 00:37:40.700 align:middle line:84% And so she dedicated her life to her kids 00:37:40.700 --> 00:37:43.580 align:middle line:84% and held a menial secretarial position, 00:37:43.580 --> 00:37:47.810 align:middle line:84% despite the fact that she was educated in law from China, 00:37:47.810 --> 00:37:53.400 align:middle line:84% and ultimately, I think, really put the three of us 00:37:53.400 --> 00:37:56.580 align:middle line:84% through school so that we could have the careers that we do now. 00:37:56.580 --> 00:38:00.570 align:middle line:84% I don't know that that's the right advice in general 00:38:00.570 --> 00:38:02.710 align:middle line:84% for women that are in that position, 00:38:02.710 --> 00:38:05.590 align:middle line:84% because I think there has to be more of a balance. 00:38:05.590 --> 00:38:08.310 align:middle line:84% But for her, it was just really important 00:38:08.310 --> 00:38:12.940 align:middle line:84% for her kids to reach the career goals that she set out for us. 00:38:12.940 --> 00:38:14.190 align:middle line:90% SARAH HANSEN: What's her name? 00:38:14.190 --> 00:38:16.200 align:middle line:90% ANDREW LO: Julia Yao Lo. 00:38:16.200 --> 00:38:17.460 align:middle line:90% SARAH HANSEN: That's lovely. 00:38:17.460 --> 00:38:18.340 align:middle line:90% Thank you. 00:38:18.340 --> 00:38:19.420 align:middle line:90% Thank you for being here. 00:38:19.420 --> 00:38:21.280 align:middle line:84% I really enjoyed getting to know you. 00:38:21.280 --> 00:38:24.510 align:middle line:84% And you've completely changed my perspective 00:38:24.510 --> 00:38:27.570 align:middle line:84% on what's possible in terms of my relationship 00:38:27.570 --> 00:38:30.203 align:middle line:90% to mathematics and to finance. 00:38:30.203 --> 00:38:30.870 align:middle line:90% ANDREW LO: Good. 00:38:30.870 --> 00:38:33.130 align:middle line:84% I am honored to have played that role. 00:38:33.130 --> 00:38:33.840 align:middle line:90% Thank you. 00:38:33.840 --> 00:38:37.190 align:middle line:90% [MUSIC PLAYING] 00:38:37.190 --> 00:38:49.000 align:middle line:90%