1 00:00:00,080 --> 00:00:03,680 Speaker 1: You're listening to Bloomberg BusinessWeek with Carol Messer and Tim 2 00:00:03,720 --> 00:00:05,840 Speaker 1: Stenebek on Bloomberg Radio. 3 00:00:06,080 --> 00:00:09,760 Speaker 2: A popular story that was highlighted on the Bloomberg terminal yesterday. 4 00:00:09,760 --> 00:00:12,120 Speaker 2: It was actually from Dow Jones Wall Street Journal, and 5 00:00:12,160 --> 00:00:14,800 Speaker 2: it talked about the talent war for those with experience 6 00:00:14,920 --> 00:00:17,959 Speaker 2: in artificial intelligence. So some companies here in the US, 7 00:00:17,960 --> 00:00:22,120 Speaker 2: and industries as Diversus entertainment manufacturing are check this out, 8 00:00:22,160 --> 00:00:24,520 Speaker 2: willing to pay salaries that are close to a million 9 00:00:24,600 --> 00:00:28,120 Speaker 2: dollars a year for top AI talent, according to the 10 00:00:28,200 --> 00:00:32,920 Speaker 2: journal reporting think machine learning specialist, data scientists and the like. 11 00:00:33,000 --> 00:00:38,640 Speaker 1: So kids study that AI. Kids AI degree in school, 12 00:00:38,920 --> 00:00:40,640 Speaker 1: so you can be replaced by AI. 13 00:00:41,120 --> 00:00:41,279 Speaker 3: Well. 14 00:00:41,280 --> 00:00:43,120 Speaker 1: Our next guest knows a thing or two about AI. 15 00:00:43,280 --> 00:00:46,479 Speaker 1: Brian Evergreen is the founder of the Profitable Good Company. 16 00:00:46,479 --> 00:00:48,720 Speaker 1: He advises executives from some of the biggest companies on 17 00:00:48,760 --> 00:00:51,800 Speaker 1: AI strategy. He's also worked for a century, Amazon Web 18 00:00:51,840 --> 00:00:54,760 Speaker 1: Services and Microsoftware who is the global head of Autonomous 19 00:00:54,760 --> 00:00:57,480 Speaker 1: AI co Innovation brand. Is also a guest lecturer at 20 00:00:57,480 --> 00:01:00,400 Speaker 1: Purdue University in the Kellogg School of Management, among other roles. 21 00:01:00,400 --> 00:01:02,880 Speaker 1: He's got a new book out. It's called autonomous transformation, 22 00:01:02,960 --> 00:01:06,759 Speaker 1: creating a more human future in the era of artificial intelligence. 23 00:01:06,760 --> 00:01:10,040 Speaker 1: He joins us on zoom from Washington State. Brian, how 24 00:01:10,080 --> 00:01:10,319 Speaker 1: are you. 25 00:01:11,400 --> 00:01:12,440 Speaker 4: I'm doing well. How are you? 26 00:01:12,720 --> 00:01:15,120 Speaker 1: We're doing pretty well. We're still we haven't been replaced 27 00:01:15,120 --> 00:01:18,840 Speaker 1: by AI at this point, yes yet, not yet. But 28 00:01:18,880 --> 00:01:21,760 Speaker 1: when you talk about a human future, what do you mean? 29 00:01:23,520 --> 00:01:26,080 Speaker 4: What I mean is that initially I set out with 30 00:01:26,120 --> 00:01:28,319 Speaker 4: the goal when I went through the process of researching 31 00:01:28,319 --> 00:01:29,840 Speaker 4: and writing the book, I set out with a goal 32 00:01:29,880 --> 00:01:32,840 Speaker 4: of discovering why is it that only thirteen percent of 33 00:01:32,920 --> 00:01:36,640 Speaker 4: AI initiatives make it through into production. And what I found, 34 00:01:36,760 --> 00:01:39,160 Speaker 4: what I'd hoped from my own personal background, was that 35 00:01:39,200 --> 00:01:41,560 Speaker 4: I'd be able to find a way that we could 36 00:01:41,760 --> 00:01:44,679 Speaker 4: harness the economic and societal potential of AI and these 37 00:01:44,720 --> 00:01:47,280 Speaker 4: other advanced technologies to do good in the world and 38 00:01:47,319 --> 00:01:49,760 Speaker 4: to create a more human future. And by that I 39 00:01:49,840 --> 00:01:52,640 Speaker 4: mean a future where more and more people can thrive 40 00:01:52,920 --> 00:01:56,800 Speaker 4: and have dignity in their work and have access to 41 00:01:57,120 --> 00:02:00,560 Speaker 4: opportunities to bring in create value in the world. And 42 00:02:00,840 --> 00:02:03,720 Speaker 4: what I found was that it's not that harnessing the 43 00:02:03,760 --> 00:02:06,720 Speaker 4: economic potential of AI and creating a better future are 44 00:02:06,760 --> 00:02:09,519 Speaker 4: two distinct things. Is actually the way that you get 45 00:02:09,560 --> 00:02:13,160 Speaker 4: the potential of the economic and societal potential of these 46 00:02:13,200 --> 00:02:16,200 Speaker 4: technologies starts with how you work with and treat the 47 00:02:16,240 --> 00:02:19,040 Speaker 4: people within your organizations and your ecosystems. 48 00:02:19,320 --> 00:02:23,600 Speaker 2: All right, sounds rather utopian, but it just also you 49 00:02:23,680 --> 00:02:25,880 Speaker 2: know that sometimes to get to a better place, it's 50 00:02:25,919 --> 00:02:28,280 Speaker 2: a little bit messy in the middle. Is there going 51 00:02:28,360 --> 00:02:31,200 Speaker 2: to be a massive adjustment as we get to a 52 00:02:31,240 --> 00:02:34,919 Speaker 2: world where artificial intelligence the next generation if you will, 53 00:02:35,000 --> 00:02:38,240 Speaker 2: the generative AI, really has an impact, but it's going 54 00:02:38,280 --> 00:02:40,679 Speaker 2: to be a little rough to get there and where 55 00:02:40,720 --> 00:02:42,600 Speaker 2: we all benefit potentially. 56 00:02:42,840 --> 00:02:46,040 Speaker 4: I think there will be a period of adjustment. That 57 00:02:46,080 --> 00:02:48,200 Speaker 4: I personally written about it and I speak about it 58 00:02:48,240 --> 00:02:51,200 Speaker 4: is that there's really three types of outlooks on jobs today. 59 00:02:51,440 --> 00:02:53,679 Speaker 4: There's two that are prevalent in the media today. Which 60 00:02:53,720 --> 00:02:56,720 Speaker 4: is one is job protectionism, which is that the current 61 00:02:56,720 --> 00:02:59,680 Speaker 4: class of jobs as they exists must be protected in 62 00:02:59,720 --> 00:03:02,320 Speaker 4: that set of tasks that make up those jobs at 63 00:03:02,320 --> 00:03:05,200 Speaker 4: all costs, which presents a longer term economic risk to 64 00:03:05,240 --> 00:03:07,880 Speaker 4: the organization if the rest of the market is advancing forward. 65 00:03:08,400 --> 00:03:10,160 Speaker 4: The second, on the other end of the spectrum, is 66 00:03:10,240 --> 00:03:13,200 Speaker 4: job fatalism, which is that AI is coming for all 67 00:03:13,200 --> 00:03:15,760 Speaker 4: our jobs, and you know, we might as well prepare 68 00:03:15,800 --> 00:03:19,079 Speaker 4: the way for our robot overlords. And the issue with that, 69 00:03:19,360 --> 00:03:21,760 Speaker 4: with that line of thinking is that it means that 70 00:03:21,800 --> 00:03:24,240 Speaker 4: we as a society and we as humanity have stopped 71 00:03:24,240 --> 00:03:27,079 Speaker 4: creating value. All the value that we've created can now 72 00:03:27,160 --> 00:03:30,000 Speaker 4: just be automated and there's no further work to be 73 00:03:30,040 --> 00:03:34,080 Speaker 4: done for humanity, and I also disagree with that pretty foundationally. 74 00:03:34,520 --> 00:03:37,320 Speaker 4: The one in the middle that I recommend is job pragmatism, 75 00:03:37,400 --> 00:03:39,920 Speaker 4: which is that, yes, our jobs are going to evolve. 76 00:03:39,920 --> 00:03:41,600 Speaker 4: The way that we work, the way that we create 77 00:03:41,680 --> 00:03:45,480 Speaker 4: value must evolve. We have these opportunities in these tools, 78 00:03:45,880 --> 00:03:49,040 Speaker 4: and that leaders have the opportunity from the time that 79 00:03:49,080 --> 00:03:52,560 Speaker 4: they sign a purchase order or set their technology strategy 80 00:03:52,600 --> 00:03:54,760 Speaker 4: for what they're going to do and what tasks will 81 00:03:54,760 --> 00:03:57,360 Speaker 4: be able to be automated. They usually have about six 82 00:03:57,440 --> 00:03:59,640 Speaker 4: months to if not a couple of years, before the 83 00:03:59,680 --> 00:04:02,360 Speaker 4: technologies at the point that it actually can be put 84 00:04:02,400 --> 00:04:05,680 Speaker 4: into production. So if at that same time they set 85 00:04:05,680 --> 00:04:09,760 Speaker 4: a workforce strategy and the separate product strategy with an 86 00:04:09,800 --> 00:04:14,000 Speaker 4: expansion mindset instead of a cutting cost mindset, that gives 87 00:04:14,040 --> 00:04:16,640 Speaker 4: them an opportunity to continue honoring the people and the 88 00:04:16,680 --> 00:04:20,960 Speaker 4: culture of their organization and move forward with the expertise 89 00:04:21,000 --> 00:04:23,080 Speaker 4: of those that they've hired over the years. 90 00:04:23,440 --> 00:04:27,120 Speaker 1: Does the AI run up that we've seen this year, 91 00:04:27,800 --> 00:04:30,480 Speaker 1: did that come as a surprise to you. I'm talking 92 00:04:30,560 --> 00:04:33,200 Speaker 1: about the you know what we've seen in the public 93 00:04:33,200 --> 00:04:35,359 Speaker 1: markets with companies such as Nvidia and the like. 94 00:04:37,320 --> 00:04:37,839 Speaker 2: Yes and no. 95 00:04:38,080 --> 00:04:40,359 Speaker 4: I think that I had visibility to some of the 96 00:04:40,360 --> 00:04:43,520 Speaker 4: investments that were taking place and the potential if anything, 97 00:04:43,560 --> 00:04:45,880 Speaker 4: I was I would have expected there to be more 98 00:04:45,920 --> 00:04:49,000 Speaker 4: of a runoff and more hype earlier, because there's quite 99 00:04:49,000 --> 00:04:51,680 Speaker 4: a few other AI technologies that have already reached a 100 00:04:51,680 --> 00:04:55,239 Speaker 4: point of inflection that are as capable or more capable 101 00:04:55,320 --> 00:04:59,240 Speaker 4: than the large language models like chat GPT. But for 102 00:04:59,279 --> 00:05:01,479 Speaker 4: whatever reason, I I think because of the accessibility for 103 00:05:01,560 --> 00:05:04,000 Speaker 4: people to be able to use chatch EPT or Dolly 104 00:05:04,080 --> 00:05:06,479 Speaker 4: on their phone, then I think that's a big reason 105 00:05:06,480 --> 00:05:08,120 Speaker 4: why the hype ran off the way that it did. 106 00:05:08,160 --> 00:05:10,440 Speaker 4: But there's several other I refer to it as one 107 00:05:10,480 --> 00:05:12,800 Speaker 4: piece on the chessboard. There's several other AI and even 108 00:05:12,839 --> 00:05:16,360 Speaker 4: other advanced technology pieces that haven't quite made their way 109 00:05:16,360 --> 00:05:19,320 Speaker 4: into the limelight. Even though they're as powerful or more 110 00:05:19,360 --> 00:05:21,159 Speaker 4: powerful for executives to harness today. 111 00:05:21,320 --> 00:05:23,680 Speaker 2: Brian, I do think about, you know, Tim and I 112 00:05:23,680 --> 00:05:26,640 Speaker 2: talk a lot about the aging populations, demographics, people having 113 00:05:26,720 --> 00:05:28,640 Speaker 2: less babies. Although it does feel like Earth is getting 114 00:05:28,680 --> 00:05:31,599 Speaker 2: maxed out here too in terms of resources. But it 115 00:05:31,640 --> 00:05:35,160 Speaker 2: does feel like we're going to see you know, continuation 116 00:05:35,240 --> 00:05:37,640 Speaker 2: in terms of slowdowns. And I do wonder about the 117 00:05:37,680 --> 00:05:39,760 Speaker 2: labor force of tomorrow, whether or not there's going to 118 00:05:39,800 --> 00:05:41,880 Speaker 2: be enough people. Health Care is already in a crisis 119 00:05:41,880 --> 00:05:44,919 Speaker 2: to some extent. You just see it. I see it 120 00:05:45,080 --> 00:05:46,840 Speaker 2: in places where you can just see more and more 121 00:05:46,839 --> 00:05:52,400 Speaker 2: things are being automated. So I do wonder how you 122 00:05:52,480 --> 00:05:58,400 Speaker 2: think about this? Is it akin to the world discovering 123 00:05:58,440 --> 00:06:00,479 Speaker 2: and developing the internet and all the things we do 124 00:06:00,560 --> 00:06:04,159 Speaker 2: online that's made certain things automated? Like how do you 125 00:06:04,279 --> 00:06:07,280 Speaker 2: think about this transformation? Is there a slot we can 126 00:06:07,360 --> 00:06:10,640 Speaker 2: place it in? Is it from horse to engine, you know, 127 00:06:10,720 --> 00:06:13,960 Speaker 2: buggy to car? Like how do you see it? 128 00:06:15,160 --> 00:06:17,159 Speaker 4: The way that I look at it is that we've 129 00:06:17,160 --> 00:06:20,279 Speaker 4: been talking about the next revolution of the industrial revolution 130 00:06:20,440 --> 00:06:22,719 Speaker 4: over and over again. Right now, it's industry for dot Oh, 131 00:06:22,800 --> 00:06:25,159 Speaker 4: we've discussed industry five to at zero. I think that 132 00:06:25,200 --> 00:06:27,160 Speaker 4: we're actually in a stage now where we can move 133 00:06:27,320 --> 00:06:30,160 Speaker 4: past and we can thank the industrial Revolution for laying 134 00:06:30,160 --> 00:06:32,920 Speaker 4: the foundation of our society, but move forward into a 135 00:06:33,640 --> 00:06:37,840 Speaker 4: new Renaissance or Enlightenment level era of society. And as 136 00:06:38,200 --> 00:06:40,640 Speaker 4: someone I interviewed recently on my podcast put it, she 137 00:06:40,680 --> 00:06:43,000 Speaker 4: said that we're cave painting with AI. And I think 138 00:06:43,000 --> 00:06:45,680 Speaker 4: that's a really good analogy and that there's a lot 139 00:06:45,720 --> 00:06:48,880 Speaker 4: of potential that for the way that we as humans 140 00:06:48,920 --> 00:06:51,040 Speaker 4: can maybe if anything, have a little bit of an 141 00:06:51,040 --> 00:06:54,000 Speaker 4: analog transformation and some of the things that where we 142 00:06:54,040 --> 00:06:57,080 Speaker 4: know there's been societal harm, like with screen addiction and 143 00:06:57,120 --> 00:06:59,720 Speaker 4: these things, maybe we can look at ways that technology 144 00:06:59,760 --> 00:07:02,760 Speaker 4: can augment for the areas of value creation where we 145 00:07:02,800 --> 00:07:05,760 Speaker 4: do rely on technology. Now, are there ways that with 146 00:07:05,880 --> 00:07:08,560 Speaker 4: AI can add a little bit more capability to so 147 00:07:08,560 --> 00:07:10,560 Speaker 4: that we don't need to use a screen to interface 148 00:07:10,600 --> 00:07:13,520 Speaker 4: with that and therefore don't get sucked back into scrolling 149 00:07:13,560 --> 00:07:15,880 Speaker 4: on our favorite social media platform. 150 00:07:15,800 --> 00:07:19,080 Speaker 1: Favorite ones that we love to hate. Brian paint that 151 00:07:19,120 --> 00:07:21,200 Speaker 1: picture for us of what life looks like in five 152 00:07:21,280 --> 00:07:21,960 Speaker 1: ten years. 153 00:07:23,000 --> 00:07:25,720 Speaker 4: So if my hope for what life can look like 154 00:07:25,760 --> 00:07:29,480 Speaker 4: in five to ten years is that as automation and 155 00:07:29,680 --> 00:07:33,400 Speaker 4: autonomous systems continue to proliferate and be put into production, 156 00:07:33,920 --> 00:07:37,080 Speaker 4: that humans can move up the work hierarchy toward more 157 00:07:37,120 --> 00:07:41,040 Speaker 4: creative work. And an example of this is now Chemical 158 00:07:41,080 --> 00:07:44,400 Speaker 4: did an amazing thing in their factories where humans were 159 00:07:44,560 --> 00:07:46,840 Speaker 4: they would have to drain their vats of chemicals. Humans 160 00:07:46,880 --> 00:07:50,200 Speaker 4: would suit up in their hazmats suits, go in, inspect 161 00:07:50,200 --> 00:07:53,440 Speaker 4: the inside and check for quality and check for safety 162 00:07:53,480 --> 00:07:55,600 Speaker 4: and all of that. Then they'd exit. So did slow 163 00:07:55,600 --> 00:07:59,440 Speaker 4: down production, and there is a human safety issue whenever 164 00:07:59,440 --> 00:08:01,760 Speaker 4: they every time that they had to perform that. What 165 00:08:01,800 --> 00:08:04,040 Speaker 4: they did instead is they were able to use drones 166 00:08:04,160 --> 00:08:07,440 Speaker 4: with machine learning or AID technology to be able to 167 00:08:07,480 --> 00:08:09,400 Speaker 4: just drop the drone into the vat while it's still 168 00:08:09,480 --> 00:08:12,520 Speaker 4: running and run that same security check without a human 169 00:08:12,560 --> 00:08:15,559 Speaker 4: having to ever go in and be exposed to that risk. 170 00:08:15,960 --> 00:08:17,680 Speaker 4: And so for me personally, I think in the next 171 00:08:17,720 --> 00:08:19,960 Speaker 4: five years, especially with the amount of time it takes 172 00:08:20,240 --> 00:08:23,240 Speaker 4: to adequately develop these kinds of systems, I'm guessing that 173 00:08:23,280 --> 00:08:25,880 Speaker 4: we're going to see more and more work that either 174 00:08:26,200 --> 00:08:30,040 Speaker 4: is currently not being done or is being done very inefficiently, 175 00:08:31,120 --> 00:08:33,840 Speaker 4: be automated or become autonomous. 176 00:08:33,240 --> 00:08:35,000 Speaker 2: Well, do you think you just got about forty seconds 177 00:08:35,080 --> 00:08:37,160 Speaker 2: left here? Like the folks in Hollywood, right that have 178 00:08:37,240 --> 00:08:39,120 Speaker 2: been on strike, I mean, I know they're working, and 179 00:08:39,160 --> 00:08:41,800 Speaker 2: it looks like they're making some progress potentially, But I mean, 180 00:08:42,000 --> 00:08:44,600 Speaker 2: do you think they were right to be worried? Creative types? 181 00:08:46,040 --> 00:08:49,040 Speaker 4: I think that their right to be concerned about the 182 00:08:49,320 --> 00:08:52,520 Speaker 4: misuse by executives that are trying to use AI but 183 00:08:53,200 --> 00:08:55,640 Speaker 4: to replace the work that they do. Absolutely, I think 184 00:08:55,640 --> 00:08:58,560 Speaker 4: it's a good opportunity to challenge the structure of the 185 00:08:58,559 --> 00:09:01,360 Speaker 4: way that they're being treated by these organizations, especially if 186 00:09:01,360 --> 00:09:04,560 Speaker 4: they're being treated like they're dispensable. But what I would 187 00:09:04,559 --> 00:09:08,400 Speaker 4: say is that any organization that leverages AI as to 188 00:09:08,440 --> 00:09:11,320 Speaker 4: the full extent and replaces human writing and something like 189 00:09:11,480 --> 00:09:14,200 Speaker 4: entertainment is only going to put out pulp fiction. And 190 00:09:14,240 --> 00:09:16,640 Speaker 4: I don't mean the movie. I mean like the lowest 191 00:09:16,720 --> 00:09:20,160 Speaker 4: quality of entertainment, and that humans will always be needed 192 00:09:20,200 --> 00:09:23,280 Speaker 4: to create things like you know, the movies that are 193 00:09:23,320 --> 00:09:24,960 Speaker 4: flashing across our headlines this summer. 194 00:09:25,280 --> 00:09:29,559 Speaker 1: I agree. I mean, I don't know, you can't get 195 00:09:29,920 --> 00:09:34,240 Speaker 1: maybe we'll get a body by AI exactly, I haven't 196 00:09:34,240 --> 00:09:34,480 Speaker 1: seen it. 197 00:09:34,679 --> 00:09:36,800 Speaker 3: You can redo something that's been done with AI with 198 00:09:36,920 --> 00:09:39,800 Speaker 3: some mixes and matches and some surprise elements, but it's 199 00:09:39,840 --> 00:09:41,520 Speaker 3: not going to have the same It'll be the same 200 00:09:41,520 --> 00:09:44,439 Speaker 3: as any other story arc that's already existed, probably the 201 00:09:44,559 --> 00:09:46,320 Speaker 3: average of the existing stories. 202 00:09:46,480 --> 00:09:49,319 Speaker 2: Brian Evergreen, thank you so much, really appreciate your time. 203 00:09:49,600 --> 00:09:52,840 Speaker 2: Your book is autonomous transformation, creating a more human future 204 00:09:52,840 --> 00:09:53,840 Speaker 2: in the era of AI.