WEBVTT - Will robots steal our jobs? 0:00:00.160 --> 0:00:07.240 Brought to you by Toyota. Let's go places. Welcome to 0:00:07.400 --> 0:00:14.280 Forward Thinking, Tather and welcome to Forward Thinking, the podcast 0:00:14.360 --> 0:00:16.640 that looks at the future and says, take this bot 0:00:16.720 --> 0:00:21.080 and shove it. I'm Jonathan Strickland, I'm Lauren Volga, and 0:00:21.120 --> 0:00:25.880 I'm Joe McCormick. As you might have guessed from the 0:00:25.920 --> 0:00:28.280 thing that just came out of Jonathan's mouth, today, we're 0:00:28.280 --> 0:00:31.520 going to be talking about robots, robots and jobs. Yeah. 0:00:31.520 --> 0:00:34.360 As it turns out, we've had quite a few listeners 0:00:34.400 --> 0:00:37.600 and viewers of Forward Thinking ask us to cover this topic. 0:00:37.640 --> 0:00:40.320 It's it's one that's had a lot of coverage in 0:00:40.360 --> 0:00:43.920 the media, and so we're looking at robots and jobs 0:00:44.159 --> 0:00:48.760 right well, specifically the question will robots steal our jobs? Right? Right? Yeah? 0:00:48.800 --> 0:00:50.760 I mean, which is kind of a terrific headline, which 0:00:50.800 --> 0:00:52.320 I think is part of why it's so popular in 0:00:52.360 --> 0:00:55.440 the media. But but I mean it captures our imagination 0:00:55.480 --> 0:00:57.880 in a very specific way, because I mean, we are 0:00:58.280 --> 0:01:01.000 all seeing all of this autumn nation that we've never 0:01:01.040 --> 0:01:04.480 seen before kind of come up and and influence our 0:01:04.520 --> 0:01:08.000 workforce in very interesting ways. Yeah, not just in uh, 0:01:08.000 --> 0:01:12.120 in the ways that have been traditionally depicted like in manufacturing, 0:01:12.240 --> 0:01:16.840 you know, heavy manufacturing, but in ways that affect you know, 0:01:16.959 --> 0:01:19.040 white colored jobs as well. And we're going to cover 0:01:19.160 --> 0:01:22.400 all this kind of stuff. But uh, let's let's look 0:01:22.480 --> 0:01:25.920 down memory lane, because Joe, you pulled up something fascinating, 0:01:25.959 --> 0:01:28.680 something I had heard but never looked into, and you 0:01:28.760 --> 0:01:32.400 really found some information that that taught me some stuff. Well, 0:01:32.440 --> 0:01:34.479 I want to get to the core of what we're 0:01:34.480 --> 0:01:37.360 talking about, which is not just robots in the sense 0:01:37.400 --> 0:01:39.160 of the way we picture them, which is a thing 0:01:39.160 --> 0:01:43.520 with legs and arms. You know, it's vaguely human basically, right, 0:01:43.600 --> 0:01:47.400 I go with Robbie the robot, But that's that's classic. Generally, 0:01:47.400 --> 0:01:51.040 we're talking about all automation, any any way in which 0:01:51.080 --> 0:01:53.360 a machine can do a job that previously could have 0:01:53.400 --> 0:01:56.279 only been done by a human or an animal. Maybe. 0:01:56.760 --> 0:01:59.920 Uh so, how about the Luodites. You all know the Luodite. 0:02:00.000 --> 0:02:03.040 It's not just a term we call each other when we, like, 0:02:03.120 --> 0:02:05.760 you know, accidentally sent a text message to the wrong 0:02:05.800 --> 0:02:09.440 person or something like that. It's actually a historical group. 0:02:09.639 --> 0:02:11.799 And of course you know who they were, right, Well, 0:02:11.880 --> 0:02:14.760 well I do now because you did the research, Joe. Well, 0:02:14.800 --> 0:02:17.320 they hated machines, right, that's the that's the whole thing. 0:02:17.440 --> 0:02:19.440 That's the way I the way I've always heard it 0:02:19.560 --> 0:02:21.880 used is yeah, it's people who just dog on it 0:02:21.919 --> 0:02:26.040 can't either grasp technology and therefore they hate it because 0:02:26.080 --> 0:02:29.160 of that, or they just outright think that new stuff 0:02:29.240 --> 0:02:31.560 is bad for some reason. I assumed it was people 0:02:31.600 --> 0:02:35.600 who had some kind of aesthetic or religious opposition to 0:02:35.800 --> 0:02:38.960 technology in general. And turns out I was being a 0:02:38.960 --> 0:02:42.359 total nano rod because that is not what the Luddites were. 0:02:42.560 --> 0:02:46.320 So the original Luddites were a movement of textile workers 0:02:46.360 --> 0:02:49.000 in England in the early eighteen hundreds, and they were 0:02:49.040 --> 0:02:53.120 not against technology in general. They were famous for like 0:02:53.240 --> 0:02:58.040 burning factories and smashing factory machines, but not because they 0:02:58.080 --> 0:03:00.480 believe machines were evil. In fact, they were more or 0:03:00.560 --> 0:03:04.880 less a labor movement. Uh. They were probably workers who 0:03:05.240 --> 0:03:08.359 used machines themselves in their jobs, and they arose from 0:03:08.400 --> 0:03:11.919 conditions of economic trouble and unemployment in Great Britain that 0:03:12.080 --> 0:03:15.280 was part of a depression during and following the Napoleonic 0:03:15.320 --> 0:03:18.240 Wars in the early eighteen hundred. So they were seeking 0:03:18.320 --> 0:03:22.120 better employment, more work, better wages, but part of the 0:03:22.160 --> 0:03:26.080 problem they perceived with the labor market. Then it was 0:03:26.120 --> 0:03:30.080 the so called labor saving devices and machines, which often 0:03:30.160 --> 0:03:34.080 meant that the same manufacturing job that used to require 0:03:34.120 --> 0:03:37.760 a skilled crafts person could be performed by a machine, 0:03:38.120 --> 0:03:41.440 or for a lower wage, by an unskilled worker paired 0:03:41.480 --> 0:03:44.559 with the machine. So in a kind of certain qualified 0:03:44.640 --> 0:03:48.720 since machines took their jerbs and they weren't happy about it. 0:03:48.760 --> 0:03:51.640 And you can understand why. We've heard the same story, 0:03:51.840 --> 0:03:55.000 the the apocryphal story that sabotage comes from the sabo 0:03:55.240 --> 0:03:59.120 thrown into the cogs of the machine. From this but 0:03:59.280 --> 0:04:03.520 similar story easy like uh and we Joe, you and 0:04:03.560 --> 0:04:06.120 I had had a brief conversation before we came in 0:04:06.120 --> 0:04:08.200 to record the podcast. We were just kind of talking 0:04:08.200 --> 0:04:11.760 about the subject, and we mentioned that this this complaint 0:04:11.880 --> 0:04:15.600 was again about the loss and jobs, not necessarily technology. 0:04:15.760 --> 0:04:19.080 If in fact the manufacturers had found a super cheap 0:04:19.160 --> 0:04:22.640 source of labor, the same problem would have existed. It 0:04:22.680 --> 0:04:24.839 wasn't just that it was a machine. Yeah, if you 0:04:24.880 --> 0:04:26.960 could have just found people who would do the same 0:04:27.040 --> 0:04:30.200 jobs cheaper and take those jobs away from these workers. 0:04:30.880 --> 0:04:33.320 I found a really easy way to train horses to 0:04:33.320 --> 0:04:37.240 do it. Are horses are terrible at weaving, but uh, 0:04:37.560 --> 0:04:41.440 you know they they just like all manual dexterity. But 0:04:41.960 --> 0:04:45.400 in economy in England, it would have had to be rabbits, right, 0:04:45.880 --> 0:04:48.520 they have a factory, they would have factories of rabbits 0:04:48.560 --> 0:04:51.800 weaving cloth. I think it would be hairs actually sorry, 0:04:52.320 --> 0:04:55.400 but uh, in economics we call we call this this 0:04:55.480 --> 0:04:59.839 process substitution, where we use a machine to substitute for uh, 0:05:00.040 --> 0:05:05.880 human labor. Uh. And there's another idea called complimentarianism complimenting. 0:05:06.200 --> 0:05:08.719 So we're gonna be talking a lot about substituting versus 0:05:08.800 --> 0:05:12.279 complimenting in this podcast. But as long as humans have 0:05:12.320 --> 0:05:14.960 been innovating, we've had this issue to some extent. I mean, 0:05:15.000 --> 0:05:18.000 if you look at agriculture, and we'll talk a lot 0:05:18.080 --> 0:05:22.080 about agriculture, uh, you know, just the advent of the 0:05:22.120 --> 0:05:26.359 plow made a lot of of changes because now you 0:05:26.360 --> 0:05:30.159 didn't need as many human workers howing the fields as 0:05:30.160 --> 0:05:33.599 you did before. And so this is not a new 0:05:33.680 --> 0:05:37.680 idea by any extent. It goes back, you know, centuries, 0:05:38.080 --> 0:05:43.200 but we see it uh accelerated in the era of 0:05:43.200 --> 0:05:47.080 technological advances and development. Yeah, and so I think a 0:05:47.120 --> 0:05:50.760 good place to start with the most recent modern incarnation 0:05:50.839 --> 0:05:54.640 of this worry that that machines, automation, robots will take 0:05:54.680 --> 0:05:59.320 our jobs is this pretty optimistic article that Kevin Kelly 0:05:59.360 --> 0:06:02.960 wrote for Why, aired in December, is called better than 0:06:03.080 --> 0:06:07.360 Human Why Robots will and Must take Our Jobs? Um, 0:06:07.440 --> 0:06:11.520 and Kelly says this, two hundred years ago, seventy percent 0:06:11.800 --> 0:06:14.760 of American workers were farmers. By about a hundred years 0:06:14.760 --> 0:06:18.640 after that, it was some yeah, I read in another 0:06:18.720 --> 0:06:21.120 article entirely, but I wanted to toss that in. Yeah, 0:06:21.160 --> 0:06:24.320 that that that that particular term that two hundred years 0:06:24.360 --> 0:06:27.599 ago seventy of American workers were farmers showed up a 0:06:27.640 --> 0:06:31.120 lot in our research. Joe did an amazing job of 0:06:31.160 --> 0:06:34.400 gathering tons of articles on this subject, and I must 0:06:34.400 --> 0:06:38.200 have read that one statistic at least six or seven times. 0:06:38.560 --> 0:06:40.839 The people on the internet sometimes use the same sources, 0:06:40.880 --> 0:06:44.039 it might be or each other. Well, it's the startling 0:06:44.120 --> 0:06:49.440 figure because apparently, according to Kelly, only one percent of 0:06:49.440 --> 0:06:54.000 those previous farming jobs remain today, and that's because of automation. 0:06:54.720 --> 0:06:58.200 So automation all of these jobs that used to require 0:06:58.279 --> 0:07:01.080 humans or animals to be done on land have pretty 0:07:01.160 --> 0:07:04.280 much all been replaced by machines now. But but Joe, 0:07:04.680 --> 0:07:07.680 what happened to all those people who formerly had been 0:07:07.680 --> 0:07:12.320 working on farms? Now they have other jobs, or I 0:07:12.360 --> 0:07:15.000 mean some of them might be unemployed, but the ones 0:07:15.040 --> 0:07:18.280 who are employed have found other jobs to do, either 0:07:18.400 --> 0:07:23.080 other jobs using the equipment that has created automation on farms. 0:07:23.080 --> 0:07:26.160 So now they can drive a tractor or or or 0:07:26.320 --> 0:07:31.120 help marator build a tractor, do maintenance on the chicken 0:07:31.160 --> 0:07:34.000 milking machine whatever it is. Yeah, or maybe they work 0:07:34.000 --> 0:07:37.560 in it, or maybe maybe moved to a city and yeah, 0:07:37.560 --> 0:07:39.840 I did something else. So in other words, we see 0:07:39.960 --> 0:07:44.640 job creation as well some innovation and uh which again 0:07:44.720 --> 0:07:48.440 necessity mother of invention, right, sure, But Kelly goes on 0:07:48.600 --> 0:07:51.920 from that to claim that over the next century, So 0:07:51.960 --> 0:07:55.600 in the next like ninety years, the same trend will continue, 0:07:55.680 --> 0:08:00.320 seventy of today's jobs will be replaced by automation. And 0:08:00.480 --> 0:08:03.640 if that, obviously that's just a speculation which we can't 0:08:03.640 --> 0:08:06.960 know for sure. But if that's true, what does that 0:08:07.040 --> 0:08:10.560 mean for the world? Right? Will we continue to see 0:08:10.720 --> 0:08:15.200 the same sort of of of progression where new jobs 0:08:15.240 --> 0:08:19.080 get created that are totally either dependent upon the fact 0:08:19.120 --> 0:08:22.320 that we have robots or or just totally new that 0:08:22.360 --> 0:08:27.120 people then will enter into. And I mean it's it's 0:08:27.160 --> 0:08:30.560 a very exciting thing to think about, but also a 0:08:30.560 --> 0:08:34.200 little bit terrifying. Yeah, sure, right, Well, nobody wants to 0:08:34.240 --> 0:08:37.160 lose their job. And your job, your job is you 0:08:37.280 --> 0:08:39.360 in many ways. It's a huge part of your identity, 0:08:39.360 --> 0:08:41.199 and it's how you make your money, which is how 0:08:41.240 --> 0:08:44.480 you do everything else that isn't your job exactly right, 0:08:44.480 --> 0:08:48.240 I mean, without your job, you're in big trouble. So 0:08:48.320 --> 0:08:50.800 we all like to think that our jobs can't be 0:08:50.840 --> 0:08:54.800 replaced by robots. There is no way a computer program 0:08:54.920 --> 0:08:57.920 or an autonomous robot or some other kind of machine 0:08:57.960 --> 0:09:03.480 could do my job, right right, Well, I don't know 0:09:03.520 --> 0:09:05.680 about that. There are some people who have made I think, 0:09:05.760 --> 0:09:10.120 pretty convincing cases that yes, your job will be replaced 0:09:10.120 --> 0:09:13.000 by a robot almost no matter what you do. The 0:09:13.120 --> 0:09:16.160 chances are, whatever you do, it's probably going to be 0:09:16.200 --> 0:09:19.440 done by a machine before too long. Now, the before 0:09:19.480 --> 0:09:24.120 too long does require a little more examination because some 0:09:24.120 --> 0:09:29.640 some jobs are more easily automated than others. Right, So, 0:09:29.840 --> 0:09:34.600 so jobs, for example, that have a repetitive action that 0:09:34.679 --> 0:09:38.959 must be done over and over, those are prime candidates 0:09:39.000 --> 0:09:42.160 to be replaced by a computer or by a machine, 0:09:42.200 --> 0:09:46.280 and we've seen that happen already things like Amazon's warehouses, 0:09:46.400 --> 0:09:50.360 where they're depending more and more heavily upon robots, including 0:09:50.480 --> 0:09:55.360 robotic shelves that will zoom over to the packaging line 0:09:55.679 --> 0:09:58.920 whenever someone orders a specific item and then zoom back 0:09:58.920 --> 0:10:01.040 to where they were supposed to be, so instead of 0:10:01.480 --> 0:10:04.400 a worker going out to retrieve something from a shelf, 0:10:04.679 --> 0:10:08.080 the shelf comes to the worker. Right. On the other hand, 0:10:08.200 --> 0:10:11.679 jobs that require a lot of flexibility, where you're constantly 0:10:11.760 --> 0:10:15.720 moving from different kinds of tasks to other ones, those 0:10:15.760 --> 0:10:18.600 are going to be harder to automate, right, But we 0:10:18.600 --> 0:10:22.120 shouldn't be able to count on them being indefinitely difficult 0:10:22.160 --> 0:10:25.400 to automate, or at least to divide up among many 0:10:25.440 --> 0:10:28.000 other automated machines that can do the different parts of 0:10:28.000 --> 0:10:30.400 the tasks. Um, So I think we should look first 0:10:30.440 --> 0:10:33.600 at h There was a book that came out called 0:10:33.720 --> 0:10:38.120 Race Against the Machine by Eric Brynjolfson and Andrew McAfee, 0:10:38.160 --> 0:10:41.760 and they have made the case that, yeah, technology is 0:10:41.920 --> 0:10:44.560 very much going to be replacing jobs. Now. They might 0:10:44.600 --> 0:10:47.920 have a spin on it, says that's not necessarily a 0:10:47.960 --> 0:10:51.959 bad thing. But what's their case. Well, you know, they 0:10:51.960 --> 0:10:54.640 do say the sort of things we've been talking about already, 0:10:54.640 --> 0:10:58.920 that technology has always replaced jobs and that this is 0:10:58.960 --> 0:11:03.000 something that we've seen throughout history. But they claim that also, 0:11:03.240 --> 0:11:05.320 you know, this current era we're in is a little 0:11:05.360 --> 0:11:09.160 different from others uh that we've seen. We're seeing more 0:11:09.200 --> 0:11:13.000 of the replacement and more automation and uh quote less 0:11:13.040 --> 0:11:16.200 of the complimenting and creating of new jobs end quote. 0:11:16.640 --> 0:11:19.320 So in other words, there was an era early in 0:11:19.320 --> 0:11:22.480 the two thousands that were still in where we saw 0:11:22.559 --> 0:11:26.360 a dip in the number of jobs that were available, 0:11:26.880 --> 0:11:31.079 but an increase in productivity, which was kind of unprecedented, 0:11:31.400 --> 0:11:35.080 where where we didn't see the jobs rebound, we saw 0:11:35.120 --> 0:11:39.280 the productivity hold steady, but we didn't see new jobs 0:11:39.320 --> 0:11:44.880 being created. And there's a potential that this could be uh, 0:11:44.960 --> 0:11:47.800 you know, a long term trend, not something that is 0:11:47.840 --> 0:11:51.600 a little you know, just blip, yeah. Yeah. Andrew McAfee 0:11:51.640 --> 0:11:54.960 gave a ted X talk in Boston in June where 0:11:54.960 --> 0:11:58.280 he showed, as part of his presentation the data on 0:11:58.440 --> 0:12:02.800 the Great Recession where where it seemed okay as things 0:12:02.880 --> 0:12:06.640 started getting better towards the end of the Great Recession. Uh, 0:12:06.880 --> 0:12:09.319 we were seeing GDP come back up, we were seeing 0:12:09.320 --> 0:12:12.400 profits come back up. It looked like from a zoomed 0:12:12.440 --> 0:12:15.920 out level that the economy was doing better again, except 0:12:16.120 --> 0:12:19.520 the number of people employed did not rebound at the 0:12:19.559 --> 0:12:23.720 same time. Uh. So you may be experiencing a situation 0:12:23.760 --> 0:12:27.560 here where the economy as a whole might be doing fine, 0:12:27.880 --> 0:12:31.160 but lots of people aren't. Yeah, and well, it also 0:12:31.200 --> 0:12:34.040 depends on how you're defining how well the economy does. 0:12:34.080 --> 0:12:36.920 If you if you're talking about total wealth generated, right, 0:12:36.920 --> 0:12:39.440 if you're looking at it as a measurement of the 0:12:39.520 --> 0:12:43.080 number of people employed or percentage of employment, that it's 0:12:43.160 --> 0:12:46.080 not doing so well. Right, right, Well, I mean there's 0:12:46.280 --> 0:12:49.920 this is a multi factor issue, of course, partially related 0:12:49.960 --> 0:12:52.600 to how hard you can convince people to work, uh 0:12:53.320 --> 0:12:56.640 for a lower amount of money. But yeah, yeah, certainly, Uh, 0:12:56.720 --> 0:12:59.920 and that's got to compete with automation also, right, I mean, 0:13:00.000 --> 0:13:03.600 and like, would it be cheaper to hire somebody to 0:13:03.679 --> 0:13:06.200 work for a really low wage or to just pay 0:13:06.320 --> 0:13:09.160 up for the robots to do it for us? You know, 0:13:09.240 --> 0:13:12.920 it's a calculated decision that the the employer must make. 0:13:13.200 --> 0:13:17.600 Can you compete with increasingly efficient automation. That's a tough decision. 0:13:17.840 --> 0:13:21.480 But anyway, Uh so McAfee said pretty much, Yes, the 0:13:21.559 --> 0:13:25.480 droids are definitely coming for our jobs. Uh even the 0:13:25.600 --> 0:13:28.800 jobs of knowledge workers, he claims. So it's not just 0:13:29.160 --> 0:13:31.920 the three point five million truck drivers in the United 0:13:31.960 --> 0:13:35.320 States should be worried about the Google autonomous car. They should, 0:13:36.200 --> 0:13:40.320 but it's also that, for example, finance writers should have 0:13:40.440 --> 0:13:44.240 their eye on algorithms that can already write perfect journalistic 0:13:44.320 --> 0:13:47.439 reports on stock performance based off of the daily data 0:13:47.480 --> 0:13:50.440 that comes into You can send this program some numbers 0:13:50.760 --> 0:13:54.600 and it will generate a completely perfect report on the 0:13:54.640 --> 0:13:58.000 stock performance in English that can be read by humans. 0:13:58.480 --> 0:14:01.079 There are plenty of other examples of this too. There are, 0:14:01.120 --> 0:14:05.160 in fact, lots of trading algorithms that that stock traders 0:14:05.160 --> 0:14:07.960 are depending more and more heavily upon. In fact, we 0:14:08.000 --> 0:14:10.360 talked about that in the previous episode. Yeah. Yeah, it 0:14:10.440 --> 0:14:12.880 used to be people crunching numbers, and now it's computers 0:14:12.880 --> 0:14:16.920 crunching numbers way better than the people really could have. Now, 0:14:16.960 --> 0:14:19.120 I don't want to give the wrong impression about McAfee, 0:14:19.120 --> 0:14:22.880 because he's revealed in other places and uh, he's basically 0:14:22.920 --> 0:14:26.800 an optimist about the overall implications of technology for human existence. 0:14:27.240 --> 0:14:29.320 You know, we can do good things with it, but 0:14:29.360 --> 0:14:32.520 they're there are different paths that we could take from here, 0:14:32.560 --> 0:14:35.480 and some of them might not be good, right, uh, 0:14:35.520 --> 0:14:38.680 And almost all of them are going to involve the 0:14:38.760 --> 0:14:41.880 droids taking our jobs. That's that's going to be hard 0:14:41.920 --> 0:14:44.960 to escape at this point. Right. Again, it's a question 0:14:45.000 --> 0:14:49.240 of time scales, right right. And also the thing where 0:14:49.280 --> 0:14:53.200 in here in in in America are jobs have not 0:14:53.280 --> 0:14:58.320 really increased in UH an alignment with automation. But that's 0:14:58.320 --> 0:15:01.320 not true for all countries, is it. No, Well, for example, 0:15:01.760 --> 0:15:05.400 the i f R, the International Federation of Robotics, they 0:15:05.760 --> 0:15:08.440 found a piece where they were drawing attention to a 0:15:08.560 --> 0:15:11.920 study showing that in some countries rates of employment grew 0:15:12.200 --> 0:15:16.480 alongside increased use of industrial robots. But then at the 0:15:16.520 --> 0:15:19.320 same time i I I found an interesting observation made by 0:15:19.320 --> 0:15:22.440 a piece UH in April in the m I T 0:15:22.440 --> 0:15:26.120 Technology Review, where they pointed out this study cited by 0:15:26.160 --> 0:15:28.800 the International Federation of Robotics, which by the way, is 0:15:28.840 --> 0:15:31.600 a trade organization for robotics, so they sort of have 0:15:31.680 --> 0:15:37.160 ah UM pointed out that this study they're referring to 0:15:37.360 --> 0:15:41.360 is talking about dangerous and stupid robots that are not 0:15:41.520 --> 0:15:44.480 very versatile, like the ones that are cutting out our 0:15:44.560 --> 0:15:48.120 car bits, maybe not the ones that are potentially handling 0:15:48.120 --> 0:15:51.240 our children exactly right, So the effect could be very 0:15:51.360 --> 0:15:55.000 different when a smarter, next generation robot shows up that 0:15:55.080 --> 0:15:59.880 can more effectively replace human workers without needing so much handling. 0:16:00.160 --> 0:16:03.360 Now that being said, David au Tour of m I 0:16:03.400 --> 0:16:06.800 T has actually expressed some skepticism that machines will take 0:16:06.840 --> 0:16:10.000 over most jobs for the foreseeable future. And now he 0:16:10.040 --> 0:16:13.360 doesn't say that it's uh, you know that we're always 0:16:13.400 --> 0:16:15.520 going to have people in these jobs and that's that's 0:16:15.560 --> 0:16:18.200 going to be the fact forever and ever, but rather 0:16:18.320 --> 0:16:21.480 that this may be a longer timeline than what some 0:16:21.560 --> 0:16:24.520 people might have you believe. He points out that we've 0:16:24.520 --> 0:16:27.400 made machines that are really good at handling those repetitive, 0:16:27.400 --> 0:16:30.320 predictable tasks, but they aren't, like we said, as good 0:16:30.360 --> 0:16:34.120 at flexible ones, uh and responding to situations that have 0:16:34.200 --> 0:16:38.640 dynamic conditions like a human interaction. So, in other words, 0:16:38.640 --> 0:16:41.720 like if you've ever had to call into any kind 0:16:41.920 --> 0:16:45.720 of of tech support where you get the automated menus. 0:16:45.760 --> 0:16:48.800 The automated menus are really good at channeling you to 0:16:49.040 --> 0:16:53.200 the specific person who can help you. They're not so 0:16:53.280 --> 0:16:56.640 good at being able to handle the actual problem. I 0:16:56.680 --> 0:16:59.040 don't know if they're always even as good at the 0:16:59.040 --> 0:17:02.800 first thing you make. And I've been like, none of 0:17:02.840 --> 0:17:05.320 the options you just listed are what I want. Well, 0:17:05.320 --> 0:17:09.520 that that's that is again another limitation on the system, though, right. 0:17:09.560 --> 0:17:11.520 I mean, if it were a person that you were 0:17:11.520 --> 0:17:14.960 talking to, they could at least respond by saying, oh, well, 0:17:15.000 --> 0:17:18.760 then the best place to funnel your problem is to 0:17:18.880 --> 0:17:21.720 this person. Uh So that's kind of his point is 0:17:21.720 --> 0:17:24.320 saying that, you know, machines are not that great at 0:17:24.359 --> 0:17:27.920 those kind of tasks, and there's no reason to believe 0:17:28.040 --> 0:17:31.720 that artificial intelligence is going to reach a point that 0:17:31.760 --> 0:17:36.080 will make them comparable to human performance in terms of 0:17:36.200 --> 0:17:39.159 things like problem solving in common sense, Yeah, common sense, 0:17:39.200 --> 0:17:41.800 critical thinking, that kind of thing. That that sort of 0:17:41.800 --> 0:17:44.199 stuff is largely going to be in the human domain 0:17:44.280 --> 0:17:48.320 for the foreseeable future. Not that machines will never have 0:17:48.640 --> 0:17:51.520 a stab at this kind of thing, but that it's 0:17:51.560 --> 0:17:55.040 not as uh, it's not as imminent as something like 0:17:55.119 --> 0:17:59.920 the automation of routine like the dangerous dirty uh job 0:18:00.160 --> 0:18:04.159 that a lot of of robotic experts talk about, you know, 0:18:04.320 --> 0:18:07.800 these machines taking over for us. The experts in general 0:18:07.880 --> 0:18:11.000 are really divided on how they think all of this 0:18:11.080 --> 0:18:12.640 is going to play out. I mean, you know, it's 0:18:12.680 --> 0:18:18.600 it's easy for us being relatively uh amateurish in our opinions, 0:18:18.720 --> 0:18:21.200 and you know, you know, but but these people who 0:18:21.240 --> 0:18:24.240 work in this industry every day can't really agree whether 0:18:24.240 --> 0:18:27.080 this is leading to a utopia or a dystopia. It's 0:18:27.080 --> 0:18:30.240 a coin flip. Well, yeah, it almost is. Because there 0:18:30.280 --> 0:18:33.879 was a Pew survey released in augusteen that pulled almost 0:18:33.960 --> 0:18:38.320 two thousand experts in relevant fields like robotics, or economics 0:18:38.400 --> 0:18:41.880 or AI about the effects of robotics and AI on 0:18:41.920 --> 0:18:46.159 our economies, and the results were that fifty two per 0:18:46.240 --> 0:18:50.000 cent of these experts predicted a quote optimistic path, which 0:18:50.160 --> 0:18:53.760 entailed quote a future in which robots and digital agents 0:18:53.840 --> 0:18:57.879 do not displace more jobs than they create unquote, and 0:18:57.960 --> 0:19:00.080 at the same time, forty percent of the x or 0:19:00.119 --> 0:19:04.920 it's predicted a pessimistic outcome in which robots quote will 0:19:05.000 --> 0:19:09.000 display significant numbers of both blue and white collar workers 0:19:09.119 --> 0:19:13.040 and many of the experts expressed concern that this will 0:19:13.119 --> 0:19:17.240 lead to vast increases in income inequality, masses of people 0:19:17.240 --> 0:19:21.080 who are effectively unemployable, and breakdowns in the social order. 0:19:21.359 --> 0:19:25.680 That's that's what we would call a a bad outcome. Yeah, 0:19:25.760 --> 0:19:28.400 it would be chaotic, it would be uh and we'll 0:19:28.400 --> 0:19:33.320 talk more about that kind of dystopian outcome in the 0:19:34.119 --> 0:19:36.480 a little bit later in the episode. Yeah. Now, some people, 0:19:36.520 --> 0:19:39.399 I guess would argue that it's not so stark that 0:19:39.440 --> 0:19:43.320 a robot will either just completely do your job, like 0:19:43.400 --> 0:19:47.439 replace you outright, but the more robots may sort of 0:19:47.640 --> 0:19:50.920 enter the workforce in middle roles. You know what I mean. 0:19:50.960 --> 0:19:54.359 This is that complementary approach to the idea that we 0:19:54.440 --> 0:19:58.000 will have machines that will complement what we do. Yeah, 0:19:58.040 --> 0:20:00.720 construction is a really good ample of how this is 0:20:00.760 --> 0:20:03.040 working today because you know, we've got a lot of 0:20:03.080 --> 0:20:06.440 machines that do the heavy lifting and the precision cutting 0:20:06.480 --> 0:20:09.000 and stuff like that. But this this work does in 0:20:09.040 --> 0:20:13.479 fact complement, not replace, skilled construction workers who can do 0:20:13.520 --> 0:20:16.040 the planning and the physical control in the in the 0:20:16.080 --> 0:20:19.880 moment judgments. Right, it's that flexibility we mentioned that the 0:20:19.920 --> 0:20:22.800 workers themselves have that the robots don't have I mean, 0:20:23.400 --> 0:20:25.840 a robot is really good at doing one thing over 0:20:25.880 --> 0:20:28.520 and over, but it can't walk around the site and 0:20:28.640 --> 0:20:30.879 you know, figure out what's the next job that somebody 0:20:30.920 --> 0:20:34.480 needs help with. Right. Robot surgery is another great example. 0:20:34.600 --> 0:20:39.400 The robot surgery tools are tools. They are extensions of 0:20:39.440 --> 0:20:43.640 an actual human surgeon. The human surgeon uses a device 0:20:43.800 --> 0:20:48.600 that allows him to or her to make control the incisions, 0:20:49.160 --> 0:20:51.800 and you know, you have the robotics that are able 0:20:51.840 --> 0:20:56.800 to translate those movements into actual actions against the patient. 0:20:57.000 --> 0:21:00.200 So you could have larger movements being trans lay it 0:21:00.280 --> 0:21:03.600 into very precise movements on the robotic scale. Yeah. Yeah, 0:21:03.880 --> 0:21:06.520 Together the machine and the human can be more precise 0:21:06.560 --> 0:21:08.760 than either would have been able to be alone. Right, 0:21:08.880 --> 0:21:11.640 So the human can make human decisions, the robot can 0:21:11.720 --> 0:21:16.119 translate motions into very precise movements, and you get the 0:21:16.200 --> 0:21:19.680 best of both worlds. But again, it's it's complementary, it's 0:21:19.720 --> 0:21:23.879 not substitution. Now, I guess the question is, but how 0:21:23.920 --> 0:21:26.520 long will that be the case, Because as robots get 0:21:26.640 --> 0:21:30.840 smarter and more agile and more flexible, they're going to 0:21:30.960 --> 0:21:34.120 increasingly be able to do these things that Right now, 0:21:34.160 --> 0:21:36.880 we're feeling like few only humans can do them. Well, yeah, 0:21:36.920 --> 0:21:39.520 I mean, let's let's go back to the driverless cars 0:21:39.560 --> 0:21:42.520 as an example. We talk about that in a positive sense, 0:21:42.520 --> 0:21:46.000 about how the cars are able to sense changing conditions 0:21:46.080 --> 0:21:49.159 much more quickly than humans are. So, for example, our 0:21:49.200 --> 0:21:53.600 our human reaction time means that when something happens, there's 0:21:53.640 --> 0:21:55.560 a delay between when we perceive it and when we 0:21:55.560 --> 0:21:59.080 can take any action. That delay is much much shorter 0:21:59.400 --> 0:22:03.600 for a robotic system that can react almost I mean 0:22:03.680 --> 0:22:07.159 to us it seems instantly. Uh, they can react to 0:22:07.640 --> 0:22:10.760 changing conditions. So when we look at the example of 0:22:10.760 --> 0:22:13.479 the driverless cars, like Google's driverless cars, they've been involved 0:22:13.480 --> 0:22:16.480 in two accidents, neither of which were caused by the car, 0:22:17.280 --> 0:22:20.120 right and at least not the driverless car system. They 0:22:20.119 --> 0:22:22.679 were both human error. I think one was when a 0:22:22.800 --> 0:22:27.200 human operator was operating the car under manual control exactly. Yeah, yeah, 0:22:27.280 --> 0:22:30.000 neither of them were the actual robotic system. So we 0:22:30.040 --> 0:22:33.120 can already see that at least in that in that 0:22:33.400 --> 0:22:37.199 kind of test scenario, because of course that's not a 0:22:37.240 --> 0:22:40.359 wide rollout, but we can see within that controlled test 0:22:40.440 --> 0:22:44.119 scenario that it appears the robots have the edge on 0:22:44.240 --> 0:22:47.200 us in that field. Already, so it stands to reason 0:22:47.240 --> 0:22:51.560 that we will see this continue in other disciplines over time. Obviously, 0:22:51.600 --> 0:22:54.520 some are gonna take a lot longer than others, because 0:22:54.560 --> 0:22:58.080 some tasks are more innately human than others. Yeah, So 0:22:58.240 --> 0:23:00.359 I think a theme I'm seeing immer ridge and the 0:23:00.440 --> 0:23:03.200 question of will robots take our jobs? Is the people 0:23:03.240 --> 0:23:07.440 who are optimistic about it aren't usually saying no, robots 0:23:07.480 --> 0:23:10.000 will not take most of our jobs. They're saying, yeah, 0:23:10.080 --> 0:23:12.480 they will, but it will be okay for one reason 0:23:12.560 --> 0:23:15.880 or another. Yeah, it seems to be most people agree. Yeah, 0:23:16.000 --> 0:23:19.040 robots are going to take a huge portion of our 0:23:19.160 --> 0:23:23.280 jobs that exist today, maybe eventually all of them. And 0:23:23.359 --> 0:23:26.720