At Davos, Palantir CEO Explains EXACTLY How AI Will Impact Jobs | ‘Exposing Job’s Real Market Value’ (YouTube Video Transcript)

(00:00:00) Your YouTube transcript will appear here (00:00:00) Is AI going to create jobs or destroy (00:00:02) jobs overall? (00:00:03) >> It Yeah. I think one of the unfortunate (00:00:06) things of the narrative in the west is (00:00:09) it it will destroy humanity's (00:00:13) jobs of like you know you went to an (00:00:16) elite school and you studied philosophy. (00:00:20) Use myself as an example. Um (00:00:23) >> I did too. (00:00:24) >> Yeah. You it hopefully you have some (00:00:26) other skill. That one is going to be (00:00:29) hard to market. Uh, and it was thought (00:00:32) was hard to market. (00:00:32) >> It was hard to market. Very hard. Uh, (00:00:35) >> it was a good education. (00:00:36) >> A very, very strong education. If you (00:00:37) can get a job, you might keep it. But (00:00:39) the hard That's what I always thought. (00:00:40) It was like, if I finally get a job, (00:00:41) I'll probably keep it and do well, but (00:00:43) I'm not sure who's going to give me my (00:00:45) first job. Um, and uh um uh uh but like (00:00:51) techn like technicians. Yeah, (00:00:53) >> if you're a vocational technician (00:00:56) >> or like we're building batteries for a (00:00:58) battery company and the people who are (00:01:01) doing it in America are doing roughly (00:01:03) the same job that Japanese engineers are (00:01:04) doing and they went to high school and (00:01:06) now they're very valuable if not (00:01:09) irreplaceable because we can make them (00:01:11) into something different than what they (00:01:14) were very rapidly and those jobs are (00:01:16) going to become more valuable. (00:01:18) Um, I mean, you know, I I not not to (00:01:21) diverge into my usual political screeds, (00:01:24) but it there are will be more than (00:01:27) enough jobs for the citizens of your (00:01:29) nation, especially those with vocational (00:01:31) training. I do think these these trends (00:01:33) really do make it hard to imagine why we (00:01:36) should have large scale immigration (00:01:37) unless you have a very specialized skill (00:01:40) because (00:01:40) >> what about (00:01:42) the foundation for white collar work in (00:01:45) Europe in the United States has been (00:01:47) through the universities but I just (00:01:49) heard you say we're going to need more (00:01:51) vocational men and women and they may (00:01:54) they're going to be but are you also (00:01:56) insinuating we're probably going to need (00:01:57) less white collar? I think like I think (00:02:00) what we need to do is yes, but I I think (00:02:03) we need different ways of testing (00:02:04) aptitude. You know, it's like um you you (00:02:08) know there are a lot of people doing X (00:02:10) that should be doing Y. Like if you (00:02:12) could manage one of our system like just (00:02:14) the person managing our maven system in (00:02:17) the US Army is a former police officer (00:02:20) who I think went to a junior college and (00:02:23) they're doing very very high-end very (00:02:26) complicated targeting globally and that (00:02:29) person actually is irreplaceable (00:02:33) and I think in the past the way we (00:02:35) tested for aptitude (00:02:37) uh would not have fully exposed how (00:02:40) irreplaceable that person's talents are (00:02:42) and would they been as talented if they (00:02:44) had not gone to their college? Yes. Um (00:02:48) and but I think the the I tend to even (00:02:51) inside Palunteer if you look at inside (00:02:53) Palunteer what am I really doing all (00:02:55) day? I'm want walking around figuring (00:02:58) out what is someone's outlier aptitude (00:03:01) and then I'm putting them on that thing (00:03:03) and trying to get them to stay on that (00:03:04) thing and not on the five other things (00:03:06) they think they're great at like you (00:03:08) know (00:03:09) >> keeping their (00:03:10) >> Yeah. It's like well you know everyone (00:03:11) at Palanteer every every engineer at (00:03:13) Palanteer uh it's it's the most wherever (00:03:16) I go in the like for for as you know (00:03:19) maybe for 18 years everyone thought we (00:03:21) were like a business joke and now lots (00:03:23) of business people want my advice you (00:03:24) know the only people who don't want my (00:03:26) advice at Palanteer about business are (00:03:28) Palunteer engineers they're like hey (00:03:29) Alex I have an idea about how we could (00:03:31) just be in a much better company and (00:03:34) it's it's always like yeah it's like (00:03:36) it's like literally McDonald's but it's (00:03:38) like we should have some titles (00:03:40) and you should stop speaking in public. (00:03:42) And uh yeah, and then I mean there's (00:03:44) probably right about speaking in public (00:03:46) sometimes. I certainly admit that. (00:03:48) >> I don't think you uh I don't think you (00:03:50) did anything wrong today. (00:03:51) >> Yeah. So uh yeah, thank you for that (00:03:53) high praise. (00:03:56) One of the keys to success is setting (00:03:58) the bar very low. (00:03:59) >> Yes. No, I don't believe that's how you (00:04:01) uh operate Palunteer. Um one last (00:04:04) question. (00:04:07) Where where is this where will the curve (00:04:10) of AI go in the utilization uh in the (00:04:14) United States and other developed (00:04:16) economies? What about the developing (00:04:19) economies? How can they participate in (00:04:22) this? I mean, I read a research report (00:04:25) yesterday that said the application of (00:04:28) AI has been so dominant by societies of (00:04:32) high education or companies of high (00:04:34) education and they're seeing a very big (00:04:38) um divergence that is occurring already (00:04:41) and it's so much based on the (00:04:44) application of education and how that is (00:04:46) being utilized. (00:04:47) Is AI going to create more um a more a (00:04:51) greater imbalance in our in our world in (00:04:54) terms of growth? (00:04:55) >> Well, I think the obvious first (00:04:57) imbalance is it seems like America and (00:05:00) China understand versions of making this (00:05:04) work and they're different. (00:05:05) >> Yes. (00:05:05) >> But they both work and they work at (00:05:07) scale and I think that is very likely to (00:05:10) accelerate way beyond what most people (00:05:12) believe is possible. like the discount (00:05:14) rate I think and not in the short term (00:05:16) but in the long term is way too high on (00:05:19) what will be done and how this will (00:05:21) impact every aspect of our society and I (00:05:23) would say especially on military and (00:05:26) then I I tend to be a realist and that I (00:05:29) think you know you have wide divergences (00:05:31) it's going to be hard to have the kind (00:05:33) of discussions people want to have where (00:05:35) two countries are and and with a maybe a (00:05:38) third following of Russia on the new on (00:05:40) like that because they they're so good (00:05:41) at fighting But um and then and then I I (00:05:46) look I spent and I'll get to the (00:05:47) developing world. I spent a lot of my (00:05:50) life my most important years and my (00:05:52) father's family came from a part of (00:05:55) Germany and I I really care about Europe (00:05:58) and especially the German parts of (00:06:00) Europe uh where I had many of my best (00:06:02) years. I still fantasize of going back (00:06:04) to grad school for not for the learning (00:06:08) reasons. Um uh and um (00:06:11) >> you going to have more fun? (00:06:12) >> Uh I had so much fun. Oh, we we won't go (00:06:14) into that. Uh but uh it's like endless. (00:06:17) I sometimes when I'm traveling across (00:06:18) the country, I just think of grad (00:06:20) school. But um uh it's uh uh um but um (00:06:26) um uh I I the the tech adoption in in in (00:06:33) Europe is a serious and very very (00:06:36) structural problem. And what scares me (00:06:39) the most is I haven't seen any political (00:06:42) leader just stand up and say we have a (00:06:44) serious and structural problem that we (00:06:46) are going to fix. So that then you get (00:06:49) to the developing world. I would imagine (00:06:52) it also depends what you mean by the (00:06:53) developing world. I would imagine with (00:06:57) not enough knowledge you're just going (00:06:59) to find pockets that go very well and (00:07:01) pockets that go very poorly. As a (00:07:03) generalization like again if you go back (00:07:06) to this somewhat n unsuccessful salopy I (00:07:09) had about the underlying architecture. (00:07:11) One way to look at at the unfairness of (00:07:14) AI is it pentests meaning it it (00:07:17) loadbears on things. So societies that (00:07:19) can and organizations and companies that (00:07:22) can bear that load have a huge (00:07:24) advantage. The problem is if you can't (00:07:27) if you've been pretending you're bearing (00:07:28) a load you're not it collapses and (00:07:31) that's where you have to start. And so (00:07:33) if you go around and just say okay what (00:07:36) societies and micro cultures are going (00:07:38) to be loadbearing here I think you would (00:07:40) find that parts of the developing world (00:07:43) certain communities in that are going to (00:07:45) do very well you you do need a realistic (00:07:48) assessment of the loadbearing (00:07:50) >> and there there's a certain honesty that (00:07:53) is painful for all of us in in in this (00:07:56) technology large language models however (00:07:59) implemented in software it you just (00:08:02) cannot not obuscate what can bear the (00:08:04) load and what can't. And then political (00:08:06) structures are built to do just that. (00:08:09) >> Like, yeah, I can't fix anything, but I (00:08:11) can give you some line that you (00:08:13) want to hear that's going to make you (00:08:15) not care about how bad your life is and (00:08:17) how much worse it's going to be (00:08:18) tomorrow. (00:08:19) >> I can give you that for free. (00:08:21) >> And those that that stuff uh is um (00:08:26) that is harder to get away with in this (00:08:29) culture. And you know, I I still view (00:08:31) myself as a card carrying progressive. (00:08:34) And I think it's the single most (00:08:36) important thing a progressive could do (00:08:38) is go around and say, "Yeah, but the (00:08:40) revolution that's coming is going to (00:08:42) expose the actual market value of what (00:08:44) you're doing, whether we want it or (00:08:46) not." Like it's like, I don't even want (00:08:48) to know the market value of some of this (00:08:49) stuff. But it is over and over a (00:08:52) relative rapid period of time. So next (00:08:54) three years you're just going to get (00:08:56) market value honesty in all sorts of (00:08:59) character and communities and micro (00:09:01) communities and the best thing you can (00:09:03) do if you are in a community whether (00:09:06) that is a large community like Germany (00:09:08) or a large community larger like America (00:09:11) is and you really care for the people (00:09:13) you're representing is to say yeah but (00:09:16) let's (00:09:18) we have to kind of look closely at what (00:09:20) what load we can bear. (00:09:23) Thank you, Alex. (00:09:24) >> Thank you, everyone.