Episode Transcript
[00:00:00] Good morning, everybody. Today I'd like to do sort of a philosophical podcast about employment, financial rewards, inflation and AI and try to wrap together some complicated things that are going on in the economy and maybe give you some perspectives as an HR professional or a business person or as a worker or employee. So, you know, we're in this strange period of time where we've had sustained high inflation, I mean, extremely high inflation, for a long period of time, to the point that most of us, at least here in the US and I think this is true in lots of parts of the world, are shocked every day at the price of food, the price of gas, the price of housing, the recurring revenue charges by our phone companies, our device manufacturers, our software companies, the token costs of our AI, which of course are going up, the license costs of software, the costs of going out and getting a burrito or a hamburger. And so there's this sort of weird sense that the world is shifting when there's inflation and you don't have any ground to stand on. It's a very sense of uncertainty. And that's the reason inflation causes a lot of political unrest. On the political side, of course, we're living in a world, at least here in the US where the amount of corruption and graft is constantly under debate. In fact, the New York Times published a list of the congressmen in the United States who have been trading stocks the most. And the number one congressman is a congressman from Silicon Valley, Ro Khanna, who positions himself as a Democrat trying to improve the ethics and morality of the federal government. So I'm not going to make any comments about him. I don't know him. But just to give you a sense of how confusing it is for the average person to make sense of this sense of poor standard of living, or this sense that the cost of life has gone up faster than the standards of living. You see this amongst young people who feel that they can't buy a house. You see this amongst political leaders trying to tap into the economic uncertainties that people have, all the various political reasons and, and strategies as to what might solve this. Today we found out that there was a $40 trillion debt in the United States. Not that the number matters, but it's a big number. Interest rates are going up. And, you know, I think we're on a sort of cyclical inflationary, high interest rate cycle that will probably end badly, especially given the amount of debt that's been taken out to build data centers and AI. And then, of course, we have the issue that companies have slowed down hiring, even though the unemployment rate is very low, Companies have slowed down hiring primarily because they believe and, and they've been told that AI is going to automate more and more work. So why are we hiring so many software engineers, why are we hiring so many salespeople, why are we hiring so many HR people, et cetera. And that expectation level has slowed down the hiring process in companies. And so employees are, especially young people are more concerned about their opportunities to find new roles now. There are shortages. There are places where there's massive opportunities for work. Healthcare, manufacturing, construction, plumbers, electricians. I mean, trade skills are in high demand. And that's great for people that are comfortable with that kind of work and have skills in those kinds of areas. And we're going to see more and people moving into those kinds of roles. But that's not the entire economy. That's a piece of it. In general, there's a lot more uncertainty than there is certainty. And then you add to that a flurry of data which seems scientific, but from AI companies or economists predicting that 50% of the jobs are going to disappear. Things like that, which I think are just all baloney. And you know, I've written about this a lot, but that's out there, too. So we have this sentiment of low levels of employee engagement, the low, the lowest in many, many decades, according to Gallup. Very low levels of commitment or trust, rather to employers, low levels of trust to the government, low levels of trust to the judicial system.
[00:04:13] Just because we have such bifurcation of politics and companies making a ton of money. CEO pay is as high as I've ever seen it. I just was reading some of the statistics on this. So the average worker, employee, whatever you call yourself, is feeling like, what's in it for me when everybody else, whoever that might be, is doing great and I'm not. And then there's this discussion going on about whether these various technology companies are good or bad. Now, you know, the pure economics books would say, as I took a lot of economics in colleges, a lot of you did, that it doesn't matter if a company's good or bad. If they're making a profit, they're contributing to the economy, and the economy will vote with consumer behavior whether a company's doing the right thing or the wrong thing. But, you know, a lot of this new technology we're building in AI is very, very unknown. Even the AI engineers don't know what it does. Here's something that blew my mind that, know, it's surprising to me as an engineer, all of these brilliant people that are building statistical models and testing and architecting these AI systems are also doing research to try to understand how it works. They don't know how it works. In other words, they've built something that is so complex that even the people who built it don't understand it. And the J curve stuff that just came out from Anthropic is really fascinating to look at. If you kind of browse through it. They're trying to figure out why Claude and how Claude makes decisions as to what to say and why it would do good things versus bad things. In other words, they created something and they're studying it as if they don't know how it works. I mean, that's not uncommon in other engineering disciplines. In nuclear power, the reason that Chernobyl collapsed was because people didn't know exactly what was going on in that power plant at the time. There were some mistakes they made too. And so they had to, you know, nuclear industries done a lot of analysis of what actually happens in a nuclear reactor, even though it wasn't as designed. And that's true for everything else. So we've built a technology that's affecting our lives that is non deterministic in the sense that it does things based on the data that are unique to that data. So even though you designed it to do X, under the conditions it's operating in, it does Y or Z or A or B. And we gotta study it.
[00:06:39] So that creates another set of fear and uncertainties. And then there's this strange fear of data centers. And you know, I've been involved in data centers since I worked at IBM. Data centers aren't really that scary. But when they're the size of an entire city and they take 30 gigawatts of power, this new stuff that just came out from OpenAI that Sam Altman believes he needs 30 gigawatts of power. I did the math as a mechanical engineer and I figured out that based on the current thermo dynamics of most power plants, in order for that 30 gigawatts, I think it was 30 gigawatts, it was terawatts, I forget. I think it's gigawatts of power. To be sustained thermodynamically, 44 million people in the United States have to leave their stove running 24 hours a day to create enough heat to create enough electricity to power the OpenAI needs for computer. Just that I'm trying to give you a sense of the scale of this, and this is you know, this is scary, uncertain or confusing to everyone. And then there's this other dimension that many of us are not sure how good AI is. I mean, we know AI is really good for many, many things. But it's what I call a spiky technology in the sense that it is really good at some stuff and really bad at other stuff. And you've all experienced this with your own experiences, I'm sure, with different tools. Sometimes it amazing things and sometimes it's just stupid.
[00:08:09] And that has to do with the probabilistic models that are in there and how they actually work and the fact that these AI models are starting to consume their own slop. As one journalist put it, they're like photocopies of photocopies of photocopies of photocopies. So this idea that they're getting smarter and smarter and smarter and they're going to use recursive self improvement, you know, something or someone has to train it and tell it when it's wrong. It doesn't know when it's wrong unless it gets feedback. And who is it getting feedback from?
[00:08:41] You know, it's different when the Google search, with Google search, when they came up with PageRank, they could, they could essentially decide that the more popular a website, the more frequently we will send people to it because the fact that it's popular means that it's of higher value to more people. This is a little bit different because the AI system is trying to give you an accurate answer. And we're going to talk a lot about this in the new release of Galileo. We've done some really significant engineering on this. So anyway, you add all this up and you've got this world where everybody in the working stages of their lives, including retirement people, by the way, 25 or 30% of people in the United States are unretiring at the age of 65. They're going back to work to try to make more money to catch up on them. There's the cost of living and you have this employee experience dynamic that's a little bit different from what we've seen in the past. I mean, I've been doing research on employee experience for a long time.
[00:09:33] And you know, the old Gallup thing that the most important thing is having a best friend at work and getting along with your manager and being fairly paid and, you know, inclusion and having a sense of psychological safety. I mean, there's. We have 24 dimensions to this. I think it's changing a lot. I think people for survival reasons are taking a Much more selfish view of their work experience. And they're saying, look, there's a lot of things I could be doing with my time. I could be driving for Uber, I could be trying to become an influencer, I could be working as an engineer, or I could be becoming a gym coach and training people on the exercise fitness that I'm a big fan of or whatever it may be. And if this job or this company isn't fulfilling the, my psychic needs and my financial needs, I'm going to do some other stuff.
[00:10:23] And we found out, you know, many years ago when I was at Deloitte, we did some studies and found out that something like two thirds of workers were moonlighting, or in other words, they were doing multiple jobs. I have a feeling that's even bigger now. And I haven't seen the data.
[00:10:38] And so employers are going to have to deal with this. Now, my philosophies on this from the book and all the research I've done, are that despite the discussions about AI taking over all our work, the opposite is actually true. That human beings, because of the interconnected genetic skills we have as animals, not just our rational thinking skills, are extremely powerful components in a company. A person, a nurse, a doctor, an engineer, a designer, a salesperson who's really well aligned and really well trained, who knows what you're trying to accomplish as a business, can do amazing things. Everybody can. Can do amazing things. I, I firmly believe that every human being can be a high performer in a company. That's why I'm not a favorite and fan of these bell curve things. But they don't fulfill that expectation or that vision or that dream unless they feel comfortable there and they feel supported there. And if, if pay is not keeping up with inflation month after month, year after year, and you go online and somehow find out that your CEO is making 6,000 times as much money as the average employee. One particular CEO, Elon Musk, is making several hundred thousand times higher more pay than any than his average employees. But there's a lot of disparities. Then you're going back to your office and you're thinking, maybe there's some other things I should be doing with my time. I don't know what those are, but maybe I should think about them. And every minute that somebody's doing that, they're not thinking about your company or their job.
[00:12:11] So this is a very pivotal time in employment. And going back to the book I wrote, Irresistible, and the new book, Superpowered, it's coming out in October, November, I think Those of you that are in HR and management roles should think about this stuff a little bit and kind of decide, are we giving our workers, our employees, our staff, enough time, money, benefits, opportunities, development, patience, forgiveness, value to keep them focused on what we're trying to accomplish as a group? Listen, if you're a sports team or a military unit or an athletic organization or a business or a nonprofit, whatever it is your group of people does, and companies are just a unique flavor of that, you want everybody in that team to be rowing in the same direction. I was on the crew team at Cornell. And you know, if you've ever been on a crew team, it's, it's a very rigorous, very demanding sport. But if one guy is just a little bit off, you can tip the boat over. It's that bad. To say nothing of the fact that you lose the race. So that's the way companies are. So I think we're in a world where we need to think about everybody in our companies, not only in a humanistic, nice way and, you know, friendly and all that, but really that what are we compensating them with, all of the things we can provide well enough that they're going to stay committed to our business and our mission. Now, sometimes people just don't like the business or the mission and they leave anyway or they're greedy or they have personal issues and that's it, they leave or other opportunities come along, that happens, and you just have to be comfortable with that. We have very low turnover, for example, in our company. But, but we bend over backwards to really make sure we don't hire people that don't like what we do. Because. Because we're kind of very mission driven in what we do. And in a big company it's hard to do that. But I think this debate about labor versus capital has to be much more serious. The investment community, the VC types, have started a narrative for the last couple years that the world is moving to capital and not labor, that all these big data centers and AI machines and even, even Elon was talking about this with the Economist, are, are going to reduce the need for labor. And so the existential forever balance between labor and capital is going to move more towards capital. I would debate that if I could with any of these people that it is not true. Because we're all going to have AI, we're all going to have these tools, we're all going to have the access to the power plants and all of those data centers, and it's going to be the people the innovation, the creativity, the empathy, the customer experience, the human being value add. That's going to differentiate your company. And I think you probably know this if you work in the frontline. In a frontline job, the personal relationship that that frontline worker has with a customer or a patient or an employee, or whoever the frontline person is working with is not mechanical. Chatbots are great when they work, but human beings are again, complex and they sometimes need to work with other human beings. So I wish I was in a position where I could have some big impact on this, but I think we have to pay people well. We have to take these profits and plow them back into the employees. We have to be crystal clear on our expectations and our behaviors and our mission and purpose so that people don't basically feel overpaid for what they're doing and they don't feel accountable for what their jobs are. Of course. And then we have to give people the opportunities and the need to move around in the company quickly as needs change. I mean, every company I talk to, every single one, is in the middle of a transformation of many kinds. Not just AI, but business, technology, industry, market, consumer, et cetera. So taking care of people from that standpoint, and I mean holistically, not just humanistically, is really a big deal. And I kind of feel like it's going to get worse before it gets better. I don't think we've seen the end of the AI fears. I don't think we've seen the end of the cyber breakouts. I don't think we've seen the end of the political issues. There's a lot of wars. There's probably more wars going on right now than any time I can remember. There's wars all over the place, threats of wars, political instability, et cetera. So we as employers have a great opportunity to take responsibility for the well being and productivity of our people and invest in them. And I'll promise you, from the standpoint of where I sit, if any of you like to talk to me, that when you do that holistically, using the types of frameworks that we show you guys, it will pay off. I mean, I see this all the time. We're starting a multi year massive study of frontline work. And we're going to prove to you that the business of frontline customer centric work, which most companies have a lot of, that has to do with benefits, training, value engagement, alignment, transparency, listening to the people. It isn't just building a great product or a great technology experience. I was Laughing today with somebody I work with about what it's like to go into a McDonald's. I used to work at McDonald's, a lot of you did back in the old days. I was there when they launched the egg McMuffin and it was a customer experience. You walked in, you talked to somebody behind a little counter and they went out, they got your food and somebody actually cooked it right there in front of you. Now it's so mechanized that you don't even know if there's a human being behind the little kiosk in most McDonald's. And people are standing in line just looking at the window like, where's my hamburger? Oh, it's sort of number 27. And I noticed that McDonald's numbers aren't doing so well anymore. I think even they probably need to think about this. And I don't mean to set an example of them because they're probably thinking about it anyway, but that's kind of my message is that despite the discussions, debates, political arguments, that everything's about AI, everything's about technology. I think that's not true. I think the human value, the human support, the human relationships, the human benefits and pay are going to pay off for you. You look at Costco, you look at all of the high performing companies in the most dynamic parts of the industries that you're in, like retail, for example, that pay people better are higher profit companies. And we're going to prove that to you with more data coming up. Okay, that's it for today. I hope you find this a little bit educational and somewhat inspirational. Bye for now.
