1 00:00:00,240 --> 00:00:04,557 So, just to back up a bit, I've been working on AI for uh for 10 years, and 2 00:00:04,640 --> 00:00:08,397 probably the thing I've noticed most about it is is how fast it's making 3 00:00:08,480 --> 00:00:11,997 progress. Two years ago, it was at the level of a smart high school student. 4 00:00:12,080 --> 00:00:14,877 Now, it's probably at the level of a smart college student and reaching 5 00:00:14,960 --> 00:00:19,277 beyond that. And on one hand, I think there's a number of very positive things 6 00:00:19,360 --> 00:00:23,517 that are going to happen. I used to be a biologist. I think AI has exactly the 7 00:00:23,600 --> 00:00:27,837 kind of skills that are needed to cure important diseases like cancer and 8 00:00:27,920 --> 00:00:30,477 Alzheimer's to provide cheaper energy 9 00:00:30,560 --> 00:00:33,037 many positive things but exactly those 10 00:00:33,120 --> 00:00:35,597 same kind of skills things like 11 00:00:35,680 --> 00:00:38,237 summarizing a document brainstorming 12 00:00:38,320 --> 00:00:40,317 putting together a financial report 13 00:00:40,400 --> 00:00:43,037 makes me worry a lot that entry-level 14 00:00:43,120 --> 00:00:47,277 jobs in areas like finance consulting um 15 00:00:47,360 --> 00:00:50,477 tech uh many many other areas like that 16 00:00:50,560 --> 00:00:53,277 entry level white collar work. I worry 17 00:00:53,360 --> 00:00:54,797 that those things are going to be first 18 00:00:54,880 --> 00:00:57,997 augmented but before long replaced by AI 19 00:00:58,080 --> 00:01:02,477 systems and that we we we may indeed it's hard to predict the future but we 20 00:01:02,560 --> 00:01:06,317 may indeed have a have a serious employment crisis on our hands as the 21 00:01:06,400 --> 00:01:11,437 pipeline for for these the early stage white collar work starts to uh starts to 22 00:01:11,520 --> 00:01:15,917 contract and dry up. >> What's the timeline here? 23 00:01:16,000 --> 00:01:17,997 >> Yes. So it's very hard to predict these 24 00:01:18,080 --> 00:01:23,357 things given how fast um you know given how fast AI is making progress. Um but I 25 00:01:23,440 --> 00:01:27,917 would I would not be surprised if somewhere between one and five years um 26 00:01:28,000 --> 00:01:31,837 we started to see big effects here. You know, I've heard a number of people talk 27 00:01:31,920 --> 00:01:34,077 about this in private. AI CEOs talk 28 00:01:34,160 --> 00:01:36,477 about this in private. CEOs of other 29 00:01:36,560 --> 00:01:39,277 companies talk about this in private. Um 30 00:01:39,360 --> 00:01:43,677 uh and I I really felt that uh you know the message that this is happening 31 00:01:43,760 --> 00:01:48,157 hasn't been getting out to to ordinary people, hasn't been getting out to our 32 00:01:48,240 --> 00:01:49,997 legislators, our Congress people either. 33 00:01:50,080 --> 00:01:52,397 And so I felt I needed to speak up on 34 00:01:52,480 --> 00:01:54,317 the record. I do think that this is 35 00:01:54,400 --> 00:01:57,357 something we can prevent this uh but but 36 00:01:57,440 --> 00:02:02,077 we need to act now. I don't think we can stop the AI bus. Um, you know, there are 37 00:02:02,160 --> 00:02:06,877 there are six or seven companies just in the US working in this air working in 38 00:02:06,960 --> 00:02:10,877 this area. I just run one of them. Even if our company stopped doing what it was 39 00:02:10,960 --> 00:02:14,557 doing today, all the other companies would would continue. Even if all six 40 00:02:14,640 --> 00:02:18,317 companies started, then China would beat us. I think that's a big and important 41 00:02:18,400 --> 00:02:22,397 threat. So, we can't stop the bus. But I do think we may have an opportunity to 42 00:02:22,480 --> 00:02:26,637 steer it. And and I think you know we need to get congress people, 43 00:02:26,720 --> 00:02:30,717 legislators, the public to to think about this. Now one of the first steps 44 00:02:30,800 --> 00:02:34,237 we're taking is just measuring the effects. Enthropic has put out something 45 00:02:34,320 --> 00:02:38,957 that we call our economic index. And using the economic index, we try and 46 00:02:39,040 --> 00:02:42,637 track the rate at which these things are happening. You know, at some point we 47 00:02:42,720 --> 00:02:46,557 have to go beyond measuring this to actually taking action to trying to 48 00:02:46,640 --> 00:02:51,677 build our AI systems in a way that augments rather than replaces. But that 49 00:02:51,760 --> 00:02:55,037 won't be a long-term solution either. We need to think about what what the 50 00:02:55,120 --> 00:02:58,157 government is going to do. And you know, there's a wide range of actions that 51 00:02:58,240 --> 00:03:02,557 that the government uh uh the government could take. And you know, it's it's not 52 00:03:02,640 --> 00:03:06,317 not my place to decide which of those are which of those are correct. But but 53 00:03:06,400 --> 00:03:09,517 I think the first step is people need to think about this and start taking it 54 00:03:09,600 --> 00:03:12,157 very seriously. >> Yeah. And you're talking about AI 55 00:03:12,240 --> 00:03:15,197 possibly wiping out all entrylevel white 56 00:03:15,280 --> 00:03:17,917 collar jobs and spiking unemployment to 57 00:03:18,000 --> 00:03:20,957 10 to 20%. So dive into the mitigation 58 00:03:21,040 --> 00:03:25,277 of this a little bit more. How could we mitigate the worst possible scenario 59 00:03:25,360 --> 00:03:28,877 here? >> Yeah. So it's hard to know the exact 60 00:03:28,960 --> 00:03:32,077 numbers. I mean, you know, I don't have a crystal ball. I can't I can't predict 61 00:03:32,160 --> 00:03:35,997 the future. But what I will say is I think what AI can do, you know, there 62 00:03:36,080 --> 00:03:40,077 have been these technological changes in the past, but I think what's different 63 00:03:40,160 --> 00:03:42,877 about AI is it's broader, it's deeper, 64 00:03:42,960 --> 00:03:47,277 and it's moving faster than than previous uh such technologies. And so in 65 00:03:47,360 --> 00:03:51,757 terms of mitigations, you know, I think I think one is just educating people in 66 00:03:51,840 --> 00:03:55,517 order in order to you in order to use AI. There will always be people who are 67 00:03:55,600 --> 00:03:57,917 who are who are using AI and helping our 68 00:03:58,000 --> 00:04:00,637 workers to adapt faster I think I think 69 00:04:00,720 --> 00:04:03,197 is an important move. A second move is 70 00:04:03,280 --> 00:04:08,077 that we may want we may want government to you know to to to kind of to kind of 71 00:04:08,160 --> 00:04:12,157 find a way to level the economic playing field and you know this may be a 72 00:04:12,240 --> 00:04:16,317 controversial proposal but you know something like taxing AI companies like 73 00:04:16,400 --> 00:04:18,957 us we we may need to get >> and that's a very interesting message 74 00:04:19,040 --> 00:04:21,517 coming from you who runs an AI company. 75 00:04:21,600 --> 00:04:24,957 Uh but you're doing a public service announcement for all of us uh in terms 76 00:04:25,040 --> 00:04:28,480 of this future concern. andio, thank you.