WEBVTT - Inside the 2025 Economy - Lab 118 0:00:00.520 --> 0:00:04.120 It feels like we all have whiplash from the policy 0:00:04.240 --> 0:00:07.480 changes that are happening in the United States of America right. 0:00:07.360 --> 0:00:11.160 Now, right right. The rent is high, groceries are high. 0:00:11.240 --> 0:00:13.560 You want to play sixty five dollars to make a 0:00:13.800 --> 0:00:14.920 turkey and cheese sandwich. 0:00:16.960 --> 0:00:20.800 Wow, that's no condiments. People are being laid off. Jobs 0:00:20.800 --> 0:00:23.439 are hard to come by. We even had a listener 0:00:23.520 --> 0:00:26.080 right in and ask us. They say, hey, and Dope 0:00:26.160 --> 0:00:28.520 Labs cover the current state of the economy and the 0:00:28.600 --> 0:00:31.600 possibility for the future. Hey, you know what that means. 0:00:31.920 --> 0:00:36.040 Your wish is our command. Friend. I'm TT and I'm Zakiyah, 0:00:36.200 --> 0:00:43.360 and this is Dope Labs. Welcome to Dope Labs, a 0:00:43.400 --> 0:00:46.839 weekly podcast that mixes hardcore science with pop culture and 0:00:46.880 --> 0:00:48.360 a healthy dose of friendship. 0:00:53.040 --> 0:00:55.320 This week, we're breaking down the vital signs of the 0:00:55.400 --> 0:00:59.760 US economy, zooming in on the stem and life sciences world, 0:01:00.280 --> 0:01:03.440 asking an economists how we got here and what comes next. 0:01:04.040 --> 0:01:05.280 Let's get into the recitation. 0:01:05.880 --> 0:01:10.600 I know that the economy is a big word, okay, 0:01:10.840 --> 0:01:15.680 and it feels unpredictable and like something that my mind 0:01:15.760 --> 0:01:19.000 can't fully wrap itself around, Like the economy is how 0:01:19.080 --> 0:01:23.200 much groceries, cout how much fundings universities get, and there 0:01:23.240 --> 0:01:25.840 are so many different lists that you have to consider 0:01:25.840 --> 0:01:30.000 when you're talking about the economy. Yes, no, yes, and 0:01:30.200 --> 0:01:33.319 even within that, like how does the labor market fit 0:01:33.319 --> 0:01:35.720 into that? Because the jobs numbers are swinging And I 0:01:35.760 --> 0:01:37.560 don't know about you, but when I submit a report, 0:01:37.600 --> 0:01:40.120 it's supposed to be done no revisions, but they're coming 0:01:40.160 --> 0:01:43.119 back with revisions months later, and that. 0:01:43.040 --> 0:01:44.080 Feels confusing to me. 0:01:44.400 --> 0:01:48.320 Right, they're saying, oh, psych, there's actually a million less 0:01:48.400 --> 0:01:49.600 jobs than we say. 0:01:49.600 --> 0:01:51.320 And we only said nine hundred thousand. 0:01:52.360 --> 0:01:56.560 There's negative jobs. There's negative jobs, and it feels like 0:01:56.600 --> 0:02:00.480 with jobs that stem jobs, they're being really hard too. 0:02:00.640 --> 0:02:03.559 Yeah, I just know that I'm tired. And it feels 0:02:03.600 --> 0:02:07.440 like everyone is anxious, Like the conversation about the economy 0:02:07.520 --> 0:02:09.960 is showing up. You're like, ah, yes, I like a 0:02:10.040 --> 0:02:13.280 macha and they're like, yeah, but the economy, like it's 0:02:13.280 --> 0:02:14.239 showing up everywhere. 0:02:14.280 --> 0:02:16.640 Macha in this economy. Yeah yeah, I don't know. 0:02:16.680 --> 0:02:18.760 I'm making my macha home. That's me talking to myself 0:02:18.760 --> 0:02:19.320 in the kitchen. 0:02:20.800 --> 0:02:22.080 So what do we want to know? 0:02:22.639 --> 0:02:25.639 Well, I want to know how economists are actually measuring 0:02:25.800 --> 0:02:28.080 this stuff like the economy, and is the labor market 0:02:28.080 --> 0:02:31.760 included in that? Is a labor market measured separately? Like 0:02:32.240 --> 0:02:32.880 what's happening? 0:02:33.000 --> 0:02:36.080 And why are the job numbers swinging so wildly? 0:02:36.200 --> 0:02:39.600 You know what I mean? Like a million jobs? Yeah, 0:02:39.639 --> 0:02:41.200 that's a lot of job That doesn't feel like a 0:02:41.280 --> 0:02:44.600 rounding error. No, that feels like somebody was asleep at 0:02:44.639 --> 0:02:51.920 the keyboard, just held down to zero exact. And what's 0:02:52.080 --> 0:02:55.440 been the ripple effects of the cuts to federal research 0:02:55.480 --> 0:02:56.919 funding that we saw at the top of the year. 0:02:57.160 --> 0:02:58.000 Is that what. 0:02:57.880 --> 0:03:00.279 We're seeing now with the stem job landscape? 0:03:00.680 --> 0:03:04.000 Right? And what about AI You know that's a dirty 0:03:04.040 --> 0:03:06.800 word for some folks, But how is that changing the 0:03:06.919 --> 0:03:09.600 job landscape? I thought it was going to be like 0:03:09.639 --> 0:03:14.040 a boom, so I'm interested in that. And then where 0:03:14.040 --> 0:03:16.760 does immigration fit into all of this because there's been 0:03:16.840 --> 0:03:20.360 a lot of rhetoric online m hm hm. And how 0:03:20.400 --> 0:03:26.720 can we I guess, students, workers, everybody that is involved 0:03:26.720 --> 0:03:28.400 in the economy adapt. 0:03:28.120 --> 0:03:30.160 Yeah, how do we get some stability? I want them 0:03:30.200 --> 0:03:31.720 to stop shaking the table. 0:03:31.960 --> 0:03:34.880 To answer these questions, We're talking to Daryl West from 0:03:34.920 --> 0:03:38.880 the Brookings Institution, which is a Washington, DC based think tank. 0:03:38.960 --> 0:03:42.320 They do research on a wide variety of public policy topics, 0:03:42.760 --> 0:03:46.119 and prior to that, Daryl was a professor of political 0:03:46.160 --> 0:03:53.000 science and public policy at Brown University. 0:03:53.800 --> 0:03:56.920 So, Daryl, before we jump into science funding, I think 0:03:56.960 --> 0:03:59.000 it's important for us to make sure that we're all 0:03:59.000 --> 0:04:01.960 on the same page because people are throwing terms around 0:04:02.000 --> 0:04:06.160 like the economy and the labor market, and these mean 0:04:06.280 --> 0:04:09.400 different things to people depending on who you ask. And 0:04:09.480 --> 0:04:15.160 so when an economist says the economy, what exactly is 0:04:15.280 --> 0:04:17.560 included in that picture? Like what are those markers? 0:04:17.960 --> 0:04:20.279 Those are all the economic activities that take place in 0:04:20.320 --> 0:04:24.080 our country. So that includes unemployment, is certainly one of 0:04:24.080 --> 0:04:29.720 the big indicators, inflation rate, gross domestic product output, all 0:04:29.800 --> 0:04:34.800 the subsectors that make up the economy healthcare, education, transportation, technology, 0:04:34.920 --> 0:04:39.240 and the like. So the term economy really encapsulates all 0:04:39.320 --> 0:04:43.799 of the activities paid or some unpaid, that take place. 0:04:44.200 --> 0:04:47.279 That's great, and I mean that makes economy sound just 0:04:47.320 --> 0:04:49.880 as big as we feel like it is because it's 0:04:49.920 --> 0:04:52.320 always a hot button topic. It's what is on the 0:04:52.320 --> 0:04:56.000 tip of everyone's tongue these days. And we've seen some 0:04:56.160 --> 0:05:01.080 really big swings in the jobs numbers with the most 0:05:01.120 --> 0:05:04.960 recent furlough to cuts for government jobs and cuts and 0:05:05.040 --> 0:05:08.120 research and just the job market just really being a 0:05:08.160 --> 0:05:11.680 tough place right now. And sometimes it feels like the 0:05:11.720 --> 0:05:14.440 economy is cooling and other times it feels like there's 0:05:14.480 --> 0:05:18.039 record job growth. Can you help us understand what drives 0:05:18.080 --> 0:05:21.680 those shifts and what the job numbers really tells us 0:05:21.720 --> 0:05:23.240 about the health of our economy. 0:05:23.360 --> 0:05:26.160 The economy does seem to be slowing down overall. When 0:05:26.200 --> 0:05:31.359 you look at unemployment, it is rising. Certainly, the tariff 0:05:31.520 --> 0:05:34.960 policies of President Trump has created a lot of uncertainty 0:05:35.000 --> 0:05:38.480 in the business community. When business leaders are cautious, they 0:05:38.520 --> 0:05:42.200 tend to pull back on hiring. So the unemployment rate 0:05:42.320 --> 0:05:45.599 is probably the basic indicator that most people follow, but 0:05:45.640 --> 0:05:49.040 it's an aggregate number, so there's a lot of noise 0:05:49.080 --> 0:05:53.000 and activity that takes place below that number. Different types 0:05:53.000 --> 0:05:57.320 of people in the population have different unemployment levels. People 0:05:57.320 --> 0:06:01.760 look at the overall participation in the job market. Technically, 0:06:01.839 --> 0:06:05.960 the unemployment rate just measures of the percentage of those 0:06:06.000 --> 0:06:10.000 people who are looking for jobs. How many people are unemployed, 0:06:10.560 --> 0:06:15.200 So the employment aspect can mask different things that are 0:06:15.240 --> 0:06:18.159 going on, like if the economy is really bad. People 0:06:18.200 --> 0:06:21.560 get discouraged from looking, and so they quit looking. Technically, 0:06:21.600 --> 0:06:23.960 they no longer are part of the unemployment rate at 0:06:23.960 --> 0:06:27.360 that point, because the unemployment rate just focuses on those 0:06:27.400 --> 0:06:29.520 who are looking who are not able to find a job. 0:06:29.960 --> 0:06:33.960 Wait a minute, Wow, how do they That is mind 0:06:33.960 --> 0:06:36.680 blowing for me? Is it after thirty days you drop off? 0:06:36.720 --> 0:06:36.800 Like? 0:06:36.800 --> 0:06:37.560 What's the cutoff? 0:06:37.800 --> 0:06:40.640 Well, this is the reason why the unemployment rate can 0:06:40.960 --> 0:06:43.120 mask a lot of other things that are going on. 0:06:43.320 --> 0:06:45.840 Like right now, the official unemployment rate in the United 0:06:45.880 --> 0:06:49.000 States is about four and a half percent, which doesn't 0:06:49.040 --> 0:06:52.039 sound very high by historic standards. It's actually at the 0:06:52.080 --> 0:06:56.600 lower end in terms of the employment figures. But there 0:06:56.640 --> 0:07:00.200 are people who are called discouraged workers, people who want 0:07:00.240 --> 0:07:02.839 to work, maybe have tried for a little while, have 0:07:02.920 --> 0:07:05.200 not been able to find a job. They get discouraged 0:07:05.279 --> 0:07:07.520 and they quit looking. Therefore they drop out of the 0:07:07.600 --> 0:07:10.200 unemployment rate. They are still there, they still do not 0:07:10.320 --> 0:07:13.840 have a job. So sometimes the economy is worse than 0:07:14.240 --> 0:07:18.520 the economic numbers would actually suggest, and I think that 0:07:18.640 --> 0:07:21.640 is likely to be the case right now. There are 0:07:21.680 --> 0:07:25.560 probably people who would like to have a job. They 0:07:25.600 --> 0:07:28.200 perhaps have gotten discouraged because they've been looking and not 0:07:28.480 --> 0:07:31.040 able to find anything. A lot of the big companies 0:07:31.280 --> 0:07:35.240 have announced layoffs in a recent months, so I think 0:07:35.240 --> 0:07:37.440 it's one of the reasons why you can have a 0:07:37.520 --> 0:07:41.040 relatively low unemployment rate, but yet the economy still is 0:07:41.080 --> 0:07:44.480 not doing very well and people feel poorly about the 0:07:44.600 --> 0:07:45.440 national economy. 0:07:46.120 --> 0:07:48.800 But I'm curious how that's tracked. How do they track 0:07:48.840 --> 0:07:52.640 when somebody has disengaged from looking for a job. 0:07:53.040 --> 0:07:56.920 There are both public surveys and surveys of businesses that 0:07:57.080 --> 0:08:01.720 track a variety of economic indicators. With businesses, they're asking 0:08:01.760 --> 0:08:05.840 people about their hiring rates each month. There are surveys 0:08:05.840 --> 0:08:08.520 that go out to a large number of businesses that 0:08:08.800 --> 0:08:11.120 you know, ask a series of questions. Now, of course, 0:08:11.280 --> 0:08:14.360 the problem right now is with the government shutdown, those 0:08:14.400 --> 0:08:17.960 surveys actually are not taking place, and so many of 0:08:18.000 --> 0:08:22.040 the economic indicators that we typically follow are at least 0:08:22.080 --> 0:08:25.679 a month out of date because the people who would 0:08:25.760 --> 0:08:29.720 collect that information have been furloughed. They're not working, they're 0:08:29.720 --> 0:08:33.679 not collecting the survey information. So we're actually flying a 0:08:33.679 --> 0:08:36.920 bit blind as a result of the government shutdown, And 0:08:37.200 --> 0:08:40.120 obviously the longer that shutdown continues, the more of a 0:08:40.160 --> 0:08:43.160 problem that creates because you know, business leaders have to 0:08:43.160 --> 0:08:46.400 make decisions. They want the best and most up to 0:08:46.480 --> 0:08:49.520 date information. We're not getting that right now, So the 0:08:49.559 --> 0:08:52.120 government shutdown creates a lot of problems in terms of 0:08:52.160 --> 0:08:53.480 collecting economic data. 0:08:53.880 --> 0:08:56.160 That makes a lot of sense. Now, I want to 0:08:56.200 --> 0:08:59.839 go back a little bit too, before the government shut down, 0:09:00.120 --> 0:09:03.120 when we saw the reporting of numbers of this many 0:09:03.200 --> 0:09:05.920 jobs being available, then the switch to like, no, it 0:09:05.960 --> 0:09:09.360 wasn't there aren't these many jobs available. And you've helped 0:09:09.400 --> 0:09:13.120 us understand economy and all these different factors for the economy. 0:09:13.720 --> 0:09:16.160 But when we talk about like labor market, I've been 0:09:16.200 --> 0:09:18.640 hearing reports that say, like the labor market is tight 0:09:18.800 --> 0:09:21.080 or is soft, and I'm like, what does that mean? 0:09:21.640 --> 0:09:25.520 In plane talk? And then what's going into determining that. 0:09:25.960 --> 0:09:28.800 One of the things that creates the greatest difficulty for 0:09:28.960 --> 0:09:32.760 people who even follow these statistics is the Bureau of 0:09:32.840 --> 0:09:36.040 Labor Statistics is the part of the government that collects 0:09:36.080 --> 0:09:38.920 all this information, and so on a monthly basis, they 0:09:38.960 --> 0:09:41.720 do these surveys and then once a month they put 0:09:41.720 --> 0:09:46.000 out the unemployment rate. But then a lot of times, 0:09:46.040 --> 0:09:51.079 since the data are based on surveys of businesses, the 0:09:51.120 --> 0:09:55.840 preliminary number can be revised in the following month because 0:09:56.000 --> 0:09:59.760 more businesses have responded with any survey that you're sending, 0:10:00.360 --> 0:10:02.720 Like there are a bunch of people who respond right away, 0:10:03.000 --> 0:10:05.440 and then there are other people who respond two weeks later, 0:10:05.559 --> 0:10:08.800 three weeks later, or four weeks later. So the beer 0:10:08.800 --> 0:10:12.920 of labor statistics will revise the numbers, and in recent 0:10:13.000 --> 0:10:16.840 months sometimes the revisions have actually been really big in 0:10:16.880 --> 0:10:19.480 either direction. Either they can make the economy look better 0:10:19.559 --> 0:10:22.920 or worse based on that revision. This is upsetting to 0:10:23.040 --> 0:10:27.160 people like Trump used that as an argument that the 0:10:27.240 --> 0:10:30.800 numbers are unreliable, that the people who work there are biased, 0:10:31.040 --> 0:10:34.080 they're trying to make him look bad by reporting bad 0:10:34.160 --> 0:10:36.880 numbers for the economy. That actually is not the case. 0:10:37.040 --> 0:10:41.160 You know, these are professional economists who are compiling the data. 0:10:41.320 --> 0:10:45.480 But when you have big revisions each month, it does 0:10:45.559 --> 0:10:48.439 make people wonder, like, why are there so many revisions, 0:10:48.520 --> 0:10:51.400 Why aren't the numbers more consistent and more reliable? 0:10:52.040 --> 0:10:54.520 And I feel like those numbers will also contribute to 0:10:54.559 --> 0:10:58.040 what you were saying when someone gets fatigued with applying 0:10:58.080 --> 0:11:01.439 for jobs, because if you realize there's actually a million 0:11:01.760 --> 0:11:05.720 less jobs, available. I would imagine that that might end 0:11:05.800 --> 0:11:09.080 up fluctuating that number as well. Like Takia was saying 0:11:09.120 --> 0:11:12.200 at the very beginning, I look a lot at the 0:11:12.520 --> 0:11:14.880 research funding and things like that, and means a key 0:11:14.960 --> 0:11:17.240 have a lot of conversations about this because you know, 0:11:17.280 --> 0:11:20.679 we both have doctorates, we both benefited from research funding. 0:11:21.240 --> 0:11:25.280 And when the federal government cut back on research funding, 0:11:25.559 --> 0:11:28.960 can you talk about the ripple effects that that has 0:11:29.200 --> 0:11:32.040 on the broader economy, Because some people when they hear 0:11:32.080 --> 0:11:34.760 these things, they're like, Okay, who cares, so you won't 0:11:34.760 --> 0:11:37.719 be able to test that frog or whatever, But we 0:11:37.760 --> 0:11:38.680 know it's bigger than that. 0:11:39.120 --> 0:11:41.840 Now, you're exactly right, that's a very good question. I mean, 0:11:41.880 --> 0:11:44.520 when the government over the last year has cut back 0:11:44.800 --> 0:11:48.599 on research funding, especially money that was going to universities, 0:11:48.800 --> 0:11:51.480 it's actually been devastating. Like there are a lot of 0:11:51.520 --> 0:11:54.280 young people and a lot of professors who depend on 0:11:54.320 --> 0:11:57.199 that money for their research. As soon as the money 0:11:57.240 --> 0:12:01.800 either slowed or got eliminated, me a lot of universities 0:12:01.840 --> 0:12:03.480 had to lay off people. You know, this would be 0:12:03.480 --> 0:12:06.120 devastating for a young person starting out in the field 0:12:06.160 --> 0:12:10.200 of science, engineering, math, or otherwise. Like they were counting 0:12:10.200 --> 0:12:13.520 on a certain level of support for their graduate studies 0:12:13.760 --> 0:12:16.520 and the money basically got yanked. So that would be 0:12:16.800 --> 0:12:20.000 devastating for those individuals. But you're also right, there's a 0:12:20.040 --> 0:12:23.400 broader issue, like beyond those individuals, you know, the impact 0:12:23.600 --> 0:12:28.040 on the academics who were assuming that funding was going 0:12:28.080 --> 0:12:31.920 to come through. The economic impact for entire communities can 0:12:31.960 --> 0:12:36.240 actually be quite substantial. In many cities across the United States, 0:12:36.559 --> 0:12:39.640 two of the big drivers are what we call eds 0:12:39.760 --> 0:12:43.559 and mets, educational institutions and all the medical and health 0:12:43.600 --> 0:12:48.320 related institutions. The whole hospital establishment, the healthcare community, the 0:12:48.360 --> 0:12:51.839 doctors like that generates a lot of jobs. And what 0:12:51.880 --> 0:12:57.280 the administration has done has disrupted both the educational communities 0:12:57.480 --> 0:13:02.080 and the healthcare establishment, and so devastating for many cities. 0:13:02.320 --> 0:13:05.560 They have counted on the economic growth and the jobs 0:13:05.920 --> 0:13:09.960 generated by these types of institutions, and in the last 0:13:10.000 --> 0:13:13.000 six months they can no longer count on that money. 0:13:13.320 --> 0:13:15.840 Even when there are being court rulings demanding that the 0:13:15.840 --> 0:13:19.480 federal government resume the funding, it's not clear that the 0:13:19.520 --> 0:13:23.440 administration has followed up to the degree that judges have required. 0:13:38.600 --> 0:13:40.440 Daryl, I want to share with you a letter that 0:13:40.840 --> 0:13:45.600 we received from a Dope Labs listener, and they wrote 0:13:45.640 --> 0:13:47.640 this to us in August and as part of why 0:13:47.640 --> 0:13:49.559 we're talking to you, and I'd love to just hear 0:13:49.600 --> 0:13:52.160 your reaction or what you think based on what they said. 0:13:52.400 --> 0:13:55.079 They said, Hi, Dope Labs. I think a podcast episode 0:13:55.120 --> 0:13:57.800 focusing on today's science job market would be a great idea. 0:13:58.000 --> 0:14:01.000 I've spent over seven years working in the farharmaceutical industry, 0:14:01.200 --> 0:14:03.800 but after being laid off from a major biotech company, 0:14:03.880 --> 0:14:06.440 I've found it incredibly difficult to secure a new role. 0:14:06.800 --> 0:14:10.280 I've seen many others share similar struggles in online communities 0:14:10.320 --> 0:14:14.280 like Reddit, and it's discouraging to realize how widespread this 0:14:14.320 --> 0:14:18.079 has become. So many of us have dedicated our careers 0:14:18.120 --> 0:14:21.800 and lives to advancing science, yet with the way things 0:14:21.800 --> 0:14:24.200 are now, it can feel like this work is no 0:14:24.240 --> 0:14:28.560 longer appreciated or valued. Covering this topic could remind people 0:14:28.640 --> 0:14:30.800 why it is worth staying the course in their studies 0:14:30.920 --> 0:14:33.480 or in careers in science and give them hope to 0:14:33.560 --> 0:14:36.080 keep moving forward. And I won't share their name, but 0:14:36.560 --> 0:14:39.400 I'm curious your response to this, and I don't know 0:14:39.400 --> 0:14:41.160 if you can give that type of recommendation, but if 0:14:41.160 --> 0:14:44.480 you have any kind of forecasting. Should people be following 0:14:44.520 --> 0:14:46.680 these careers, Should they pursue this with the way things 0:14:46.680 --> 0:14:47.160 look now? 0:14:47.520 --> 0:14:50.280 Well, first of all, I feel for that person. That 0:14:50.320 --> 0:14:54.400 person is not unique. I know there are many examples 0:14:54.440 --> 0:14:57.480 of other people who have had exactly the same experience 0:14:57.520 --> 0:15:00.280 over the last year. Some do to cut back and 0:15:00.320 --> 0:15:04.400 government funding, some do to as in this case, companies 0:15:04.520 --> 0:15:07.560 just laying off individuals. You know, we've all seen the 0:15:07.600 --> 0:15:12.640 stories about AI starting to affect a number of different industries. 0:15:12.760 --> 0:15:15.960 AI is doing more and more sophisticated tasks, including in 0:15:16.000 --> 0:15:19.440 the research area. AI can do things that gradu students 0:15:19.480 --> 0:15:22.960 and faculty used to do on their own. So the 0:15:23.000 --> 0:15:26.400 combination of all these things has been very destabilizing, and 0:15:26.920 --> 0:15:29.560 I do worry what it's going to mean for the 0:15:29.600 --> 0:15:33.000 future in the United States, because you know, what actually 0:15:33.000 --> 0:15:36.880 has made America great has been the innovation economy, our 0:15:36.960 --> 0:15:40.480 scientific establishment. Like this is the reason so many foreign 0:15:40.520 --> 0:15:43.320 students want to come to the United States because they 0:15:43.400 --> 0:15:47.200 know America has the best universities in the world, and 0:15:47.360 --> 0:15:49.840 a lot of these people come here they'd like to stay. 0:15:50.360 --> 0:15:53.120 Some of them end up starting their own companies. So 0:15:53.560 --> 0:15:57.920 they're a vital part of what is propelled American prosperity 0:15:58.640 --> 0:16:01.720 the creation of jobs and the fact that the United 0:16:01.760 --> 0:16:05.760 States has been very innovative in a lot of different areas. 0:16:05.840 --> 0:16:08.520 So to the extent that the we're cutting back in 0:16:08.600 --> 0:16:13.000 that area, either through research funding or if big pharmaceutical 0:16:13.040 --> 0:16:17.520 companies are laying off people, or if immigration policies are 0:16:17.560 --> 0:16:21.840 making it very difficult for foreign students who get educated 0:16:21.880 --> 0:16:24.640 here and would like to stay but they're no longer 0:16:24.680 --> 0:16:27.080 able to do that, all of that is going to 0:16:27.160 --> 0:16:31.040 have a very detrimental effect on our future economy. Like 0:16:31.120 --> 0:16:33.720 people seem to think we can do all these things 0:16:34.000 --> 0:16:36.120 and everything else is going to stay the same, and 0:16:36.160 --> 0:16:39.160 that is just simply not the case. Without all of 0:16:39.200 --> 0:16:42.400 the ingredients that drive the innovation economy, we're not going 0:16:42.440 --> 0:16:45.400 to have the same level of economic prosperity in the 0:16:45.440 --> 0:16:48.600 future that we have had over the last couple of decades. 0:16:49.280 --> 0:16:51.720 Yes, and I know that you often talk about the 0:16:51.760 --> 0:16:55.960 future of work and so, like Zekia was saying, folks 0:16:56.000 --> 0:16:58.440 that are post docs in the life science, is post 0:16:58.520 --> 0:17:03.120 docs technicians even undergrads thinking about research careers. I feel 0:17:03.160 --> 0:17:05.960 like we're going to see a decrease in the amount 0:17:06.000 --> 0:17:08.760 of folks interested in it, and I think that that 0:17:09.000 --> 0:17:13.159 is overall just a bad situation for the country. I 0:17:13.240 --> 0:17:15.480 do want to touch on something that you brought up 0:17:16.119 --> 0:17:19.240 just now. I would love to hear more about how 0:17:19.320 --> 0:17:21.680 AI is affecting the job market. 0:17:21.920 --> 0:17:24.919 This has been the big topic in recent months. I mean, 0:17:24.920 --> 0:17:29.159 there have been lots of headlines where companies have announced 0:17:29.400 --> 0:17:33.080 layoffs and the companies themselves are saying one of the 0:17:33.200 --> 0:17:36.760 reasons they're getting rid of humans is AI is doing 0:17:36.760 --> 0:17:39.520 the work that these humans used to do. For example, 0:17:39.960 --> 0:17:43.520 software coding development, all these things have been in very 0:17:43.520 --> 0:17:46.840 hot demand for a number of years. It turns out 0:17:46.920 --> 0:17:50.160 AI can actually do that stuff pretty well, and so 0:17:50.200 --> 0:17:53.119 some of these companies have said, you know, these are 0:17:53.160 --> 0:17:56.520 tech companies, forty percent of their layoffs have been due 0:17:56.760 --> 0:17:59.640 to AI being able to do the jobs that these 0:17:59.680 --> 0:18:02.399 humans used to do. So I think it is creating 0:18:02.400 --> 0:18:05.520 a problem in the entire STEM field, and it's not 0:18:05.640 --> 0:18:08.280 just in the computer area. Like a lot of what 0:18:08.880 --> 0:18:14.560 happens in the knowledge sector is basic research, and basic 0:18:14.640 --> 0:18:18.639 research consists of a variety of different things. It's like 0:18:18.760 --> 0:18:21.240 doing a literature review to find out what's going on 0:18:21.280 --> 0:18:25.840 in the field, collecting data, analyzing, data, interpreting the data, 0:18:26.320 --> 0:18:30.680 writing reports, having summaries of what comes out of various studies. 0:18:31.200 --> 0:18:34.280 It turns out AI can actually do many of those things, 0:18:34.400 --> 0:18:38.119 and so the implications of the rise of AI for 0:18:38.400 --> 0:18:42.520 the entire knowledge sector, I think are actually quite serious, 0:18:42.560 --> 0:18:45.720 and so we need to think about how we build 0:18:45.760 --> 0:18:49.639 the next generation of scientific talent in a world that 0:18:49.760 --> 0:18:54.200 increasingly is being driven by AI. You don't want robots 0:18:54.200 --> 0:18:56.760 and AI to be doing all the jobs and humans 0:18:56.800 --> 0:18:59.600 having no role in it. Like, that's not a good 0:18:59.600 --> 0:19:02.800 rest of for creative solutions coming out of the future. 0:19:03.040 --> 0:19:06.480 But then I'm curious, what is it then? Right then, 0:19:06.480 --> 0:19:09.040 what does it look like to be a scientist prepared 0:19:09.160 --> 0:19:12.280 for work in the future. What does it look like 0:19:12.400 --> 0:19:15.480 to adapt and be ready to respond to these changes? 0:19:16.160 --> 0:19:18.639 Well, there certainly are jobs that are going to be lost, 0:19:18.760 --> 0:19:21.520 and we're already seeing that. But the good news is 0:19:21.640 --> 0:19:24.720 there actually are new kinds of jobs that are being created, 0:19:24.800 --> 0:19:28.120 So this is kind of the optimistic side of all this. 0:19:29.359 --> 0:19:33.360 In the data area, people who have really good data 0:19:33.400 --> 0:19:37.680 analysis skills are still in hot demand, particularly those who 0:19:37.720 --> 0:19:41.520 are skilled at working with very large data sets, data 0:19:41.560 --> 0:19:44.800 sets that may number in the hundreds of thousands or 0:19:44.800 --> 0:19:48.320 even millions of records associated with them, So that's an 0:19:48.320 --> 0:19:51.800 important skill, and the digital economy is just creating so 0:19:51.920 --> 0:19:56.000 much data. Anybody who has data skills like cleaning data sets, 0:19:56.160 --> 0:20:01.440 analyzing information, interpreting information, I think still be an important thing. 0:20:02.480 --> 0:20:05.480 There are other types of new jobs where companies and 0:20:05.640 --> 0:20:10.399 organizations are trying to integrate AI into their operations and 0:20:10.480 --> 0:20:17.119 improve their administrative processing, their financial management. Like there's a 0:20:17.119 --> 0:20:20.320 wide variety of things, but it actually is not such 0:20:20.359 --> 0:20:24.160 a simple matter just to add AI to your organization 0:20:24.680 --> 0:20:26.600 and expect people to be able to figure it out. 0:20:26.720 --> 0:20:29.720 So they're going to mean new jobs that I would 0:20:29.840 --> 0:20:35.639 describe as something like management, innovation, organizational dynamics, kind of 0:20:35.680 --> 0:20:39.600 figuring out how AI works in the ways that organizations 0:20:39.640 --> 0:20:43.720 particularly need, Like to really automate functions, you have to 0:20:43.760 --> 0:20:49.000 break down every administrative task into its component parts, and 0:20:49.119 --> 0:20:52.000 even the simple thing like paying a bill, there may 0:20:52.040 --> 0:20:55.000 be like five six or seven steps involved with that, 0:20:55.400 --> 0:20:59.119 and so the process of automation means taking a look 0:20:59.240 --> 0:21:01.680 at each of those those five six or seven steps, 0:21:01.840 --> 0:21:04.959 figuring out how to automate that, how to link that 0:21:05.040 --> 0:21:08.399 sequence of activities, and then how to integrate all that 0:21:08.760 --> 0:21:10.639 so you actually get the right answer. At the end 0:21:10.640 --> 0:21:12.800 of that, there are going to be jobs for people 0:21:12.840 --> 0:21:15.600 who actually know how to do that. So that will 0:21:15.600 --> 0:21:20.439 involve scientists who understand AI, people who understand organizations, and 0:21:20.480 --> 0:21:22.880 then people who are used to dealing with human beings 0:21:23.040 --> 0:21:25.199 that can actually sit down with you or I and 0:21:25.320 --> 0:21:28.040 explain you know, this is how we're integrating AI into 0:21:28.080 --> 0:21:31.040 our operations. So there are going to be a bunch 0:21:31.080 --> 0:21:34.000 of new types of jobs that are being created. If 0:21:34.040 --> 0:21:38.160 you look at the types of job ads that organizations 0:21:38.160 --> 0:21:42.040 are starting to put out now, there are job listings 0:21:42.080 --> 0:21:45.199 that have the strangest titles like jobs I've never heard of. 0:21:45.640 --> 0:21:50.080 But yet these organizations are understanding that as technology gets 0:21:50.119 --> 0:21:54.399 integrated into their operations, they need new types of people 0:21:54.560 --> 0:21:57.600 who have different types of skills. So there will be 0:21:57.920 --> 0:22:00.800 lots of new opportunities. But the key thing is making 0:22:00.840 --> 0:22:04.280 sure people have the training that will qualify them for 0:22:04.440 --> 0:22:05.600 those new types of jobs. 0:22:05.960 --> 0:22:09.360 And that means changing the perspective that a lot of 0:22:09.680 --> 0:22:13.160 folks in higher education have on AI, because I think 0:22:13.240 --> 0:22:15.919 in the beginning it was like, Oh, all these students, 0:22:15.920 --> 0:22:19.040 they're just cheaters, they're using AI for everything. But I 0:22:19.040 --> 0:22:21.119 think we're past that now, and now we have to 0:22:21.160 --> 0:22:23.160 start teaching them how to use it to their benefit. 0:22:23.640 --> 0:22:26.280 Just like when Google hit the scene and everybody felt 0:22:26.320 --> 0:22:28.840 like there was just all this information at your fingertips, 0:22:28.840 --> 0:22:30.440 no one had to think about anything. But now we've 0:22:30.520 --> 0:22:32.639 learned how to use it in better ways, even though 0:22:32.680 --> 0:22:36.840 some people's Google searches are very different from the rest 0:22:36.840 --> 0:22:39.480 of the population. We've talked about a lot of the 0:22:39.880 --> 0:22:42.080 tough things going on with the economy, but I am 0:22:42.200 --> 0:22:46.719