Why AI Efficiency Collides With Sustainability Promises

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Let me welcome both of you to the podcast.
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Pleasure to be here.
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Great to be here today.
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Well, look, let's begin by explaining what the actual tension and difficulty is between when simultaneously using AI platforms and trying to implement social corporate real corporate building and ESD.
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What is the what's the problem there?
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Well, it's multi-layered to start with that.
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First of all, I think we have to step back a second and define what would mean by ESG, because the issue with using that term like DEI is there's no universally accepted definition of what those terms mean.
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But in the context of AI, there's certainly the environmental cost that is well known, but there's social costs and sustainability costs that I don't think are as widely discussed in terms of how it affects the employee base.
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There's been a lot of senior management rhetoric about using AI for efficiency.
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And those messages are directed at the investment community.
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It's Wall Street speak.
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The problem is employees hear that and they think, oh my God, I'm going to be replaced by a computer algorithm.
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So there's a disconnect in terms of understanding what these terms mean.
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And again, I'm I'm not saying organizations shouldn't be efficient and strive for efficiency.
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But if you're talking about, you know, the cost to people and your workforce, and we've seen some companies backtrack and alter their rhetoric now that no, they want AI to be a partner with humans.
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But you know, you do have people like Goldman Sachs, CEO in the UK, a couple weeks ago, who talked publicly about lowering lower-valued human capacity and replacing that with AI, which he then, of course, had to walk back.
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So from a communications point of view, it's who are you talking to?
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And understand you may be talking to one audience, like a Wall Street audience, but it's gonna go viral in two seconds, and you're gonna expose that message to audiences that you didn't intend to.
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Well, they're gonna have something to say about it.
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So I'll I'll stop there and let Heather chime in.
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I would take a more sort of simplified approach to it, think Greg did, and say if we think about ESG, we're talking about environment social governance, the three peg the three legs of the stool.
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If you just take them one by one, when you talk about this tension between AI and increased efficiency versus ESG ESG goals, for example.
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Well, on the one hand, you say you want to increase efficiency with AI, but in order to implement AI, AI is one of the worst technological inventions in terms of hurting mother nature, right?
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So the amount of water, the amount of energy on the grid, the amount of silver and nickel and precious resources that are used even to building the components that go into the computers.
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So right there there's a tension off the bat.
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Like you say you're you're an ESG-friendly company, but then you're using a technology that is extremely harmful to climate.
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And then if you take the social, and I think that's where Greg really, really honed in on.
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If you take the social piece of it, you're saying, oh, we're an organization that puts people first.
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But now you're not putting people first because now you're talking about implementing efficiencies and chatbots and AIs and LLMs that actually eliminate tasks.
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And and as as Greg just referenced, the Goldman Sachs report that demonstrates that there's an inordinate number of those of those kind of simplified or managerial or basic accounting, those kinds of tasks that are going to be that are currently held by women.
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So you're disproportionately hurting women's jobs.
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And that's a problem.
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And then if you just go to the G, which is governance, which we don't talk enough about, now we get into the profit versus purpose.
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And you're saying, Oh, we're an ESG, we're a people first, we're a purpose-driven company.
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All of our corporate culture is purpose-driven, except you're implementing technology that's about profit first.
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So I think that if you just take it through like that very simply, AI tends to be at odds with all of the climate pet pledges, with all the corporate culture pledges, and with all the fair governance pledges that organizations, small and large, from Main Street to Wall Street, have been making for the last 20 years.
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Well, it does sound like a mass a m you know massive problem here.
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So how have people become to come you know come to grips with it?
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What are corporations doing when they are presented with this kind of information that, you know, AI is going to help you this way, but it's going to maybe damage you know some of your staff in another?
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How are they coming to grips with that?
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Yeah, that's a great question.
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To a degree, I'm not sure they have yet.
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I don't think that a lot of them haven't figured it out yet.
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They're either talking about efficiency or they're talking about we're a people-first company.
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Well, how do you reconcile those two with adding AI into the workforce?
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And I don't want to create an impression that AI is the boogeyman.
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It's you know the latest innovative technology, but if you look at the history of humanity, there's always been disruptive technology going back to the printing press.
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And disruptive technology, by its very nature, eliminates some levels of employment and creates new ones that nobody ever thought of before.
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So, you know, it it holds to the pattern of technological innovation.
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However, this is a leap, this is a leap we haven't seen before.
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Where I think I personally think the promise of AI and the threats of AI are both overblown, and the truth right now is somewhere in the middle.
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But I think too many organizations are getting caught up in the hype.
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And and one interesting thing I've observed is they went all in on AI, and all of a sudden, and they're spending, you know, Peter, they're spending billions of dollars every year.
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And now boards are starting to say, well, wait a minute, what's our ROI on this?
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And senior management can't really answer that yet.
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You know, you can you can claim greater efficiency, but where's the data?
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So so we're starting to see businesses, I won't say jump off the bandwagon, but maybe pull the reins a little bit and say, well, we're spending all this money, and what are we getting out of it?
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And nobody's really been able to answer that yet.
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Well, you know, as I stood here listening to it because obviously uh that that was not something that was on my radar screen, but as I'm listening to you now talk about yes, people are you know crazy and going out of their way to adopt AI to do AP companies.
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But they have not recognized CSR as well.
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So how are you?
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AI perhaps helping you do what you want to do, but if the impact on some of your other issues and programs is is being impacted in a negative way.
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How are they how is it coming to their attention?
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Is it coming to their attention?
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And has anybody started to make any efforts to come to grips with it?
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Well, I think as Greg pointed out, I think the reality is that what's happened is the AI models and the AI efficiency have come out of, you know, think about it left hand, right hand, not talking to each other.
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Where the AI and is coming out of tech, it's this the chief technology officer, it is the business growth officer, and it is over sort of in the profit center, not the purpose center of an organization.
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Where you have the people who are developing corporate culture and corporate values in completely different departments.
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So ultimately the reconciliation is the CEO's responsibility and the board of directors' responsibility for large organizations.
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But if you're talking about a small family-owned operation or a mid-sized business, then you know that's going to be whoever the managing partners and the owners are to sit down.
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I I think the problem, the disconnect is it's it's sort of this unintentional consequence, right?
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Of always chase chasing efficiency without thinking about the long-term consequences of what that efficiency might do.
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To answer your question about like who is talking about it, well, Greg and I just wrote a book about it, raising social capital.
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But beyond that, you know, we're we are more and more being asked to do podcasts like this or to go around and give talks.
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And as we're doing that, what we're finding is the answer is just not a lot of people.
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Because everybody for all the talk about integration and all of the ways that, you know, organizations want to move into modern spaces of flat governance, they still are very siloed.
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And the larger the organization, the more siloed.
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So I actually think smaller businesses are better at addressing this because the larger organizations are so siloed that they're really not thinking it through.
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And so and so it's not it's a problem that has emerged and we're calling attention to it, you're calling attention to it, but we need more people to sound the alarm so that the executive leadership teams and the managing partners and the family-owned businesses will actually sit around the table and figure it out.
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You know, what what grabbed my attention there is when you talked about parts of an organization being salad.
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I recall when I was in the Clinton administration, I was actually just about education.
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And what we just go down there was that you have to do it.
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Perhaps in some way can work together if we sit down and and uh talk about this thing and explore ways of uh working efficiently and doing both if possible.
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Yeah, I think it need it calls for a new model, Peter.
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The traditional capitalistic model of profit.
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And then don't misunderstand, I'm not against profit, but so many businesses are driven by the profit motive.
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Absolutely.
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And and that's okay.
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That's why you're in business to make a profit.
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But and again, this is nothing new, but the human cost kind of gets second billing, and you hope, in answer to your earlier question, you would hope the communications people are acting in the tradition a traditional role of being the conscious of their organizations, are bringing this to senior management's attention.
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The good news is we're starting to see C C COs at that at those tables.
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You know, there was a recent report, I'd have to go back and find it, but you know, CCOs are increasingly reporting directly to the CEO having more influence.
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So it's a matter of balancing risk and influence.
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But to your point, senior leaders are trained in business schools.
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Right.
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And they're not trained to come up through the communication side.
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So their motive is financial, which is fine.
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But they're not trained in stepping back to say, well, wait a minute, what does this mean for our workforce?
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What does this mean for our long-term business model?
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You know, and a lot of this hype, of course, is being pushed by the AI labs.
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They're in business to make money too.
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So I think a lot of leadership is getting caught up in the hype without stepping back and saying, well, wait a minute, what is the long-term impact of all this stuff?
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Because AI is evolving so fast that the AI you use this year is going to be needed to replace in six months.
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Right.
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And, you know, where's that money coming from?
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And has a trickle-down effect to societal impacts.
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Well, if AI starts replacing human beings, okay, that means less taxes are being paid into the system, which means there's less money for the government to do things.
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It's great to, in the utopian view of well, the AI will free up people to do other creative things.
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Okay, great.
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And who's paying who's paying the taxes into all that stuff?
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You know, so so this has a lot of ripple effects that I don't think are being widely discussed at all.
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A lot of it's being driven by Wall Street, frankly.
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Well, that that was probably the next question I was going to be asking if you guys have uh thought about actually going to Wall Street and talking to some of the heavy hitters up there about this uh conundrum, if you will.
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Yeah, we've talked to family offices, we've talked to private equity, we've talked to investment bankers, when we were interviewing people for our book, trying to understand one of the interesting things sort of that we were able to uncover in the world of ESG is that a lot of this, I don't want to use the term made up, but a lot of this is sort of self-governance.
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Let's let's say that.
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A lot of it's self-governance.
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So when we talk about, when we ask real serious questions like, well, how are you accounting for the environmental impact?
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How are you determining what your ESG scores are in your investment portfolio based on what companies are doing?
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A lot of those answers are, you know, self-governed.
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Like they've created their own sort of system for this.
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So outside of proper government relate regulation, and as you know, ESG is very contentious in the US for regulation, and AI regulation is very contentious.
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So sort of in this gray foggy area, there's not a lot of clarity.
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And without clarity, it gives room for organizations to, for instance, count all of the pluses they're doing to get carbon credits or to have a carbon neutral supply chain or manufacturing plant, but without counting all the deficits or the negatives of the AI that they're using, because that's a different company.
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That's that's the AI company causing that problem, not them.
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They're just licensing the product.
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And so this is a larger ecosystem.
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If you take any one organization and they're just account, you know, they're just kind of doing it in an accounting practice style of good and bad, they get to claim all the good on the social, on the climate and social governance pieces without having to own any of the bad on the AI piece outside of the human cost.
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This is problematic, but this is also something that people in policy spaces are arguing about, people in Wall Street are pro arguing about, and because the ecosystem, and as Greg said, the ripple effects are so large, it's going to take years, if not decades, to come to some kind of level of clarity.
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I don't foresee clarity in this space happening in the next decade, which means self-governance, authenticity, legitimacy is going to be owned by the people who are the most transparent and about what they're doing.
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The organizations that are the most forthcoming and transparent and willing to have these discussions will win the trust of the people because it's not going to come top down anytime soon.
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It's basically analogous, Peter, to industries regulating themselves.
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And we know so we know what happens when industries do self-regulation.
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So it's it, you know, the analogy is is very much the same.
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And I I absolutely agree with Heather.
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It's not going to be addressed anytime soon.
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The problem is because it won't be addressed anytime soon, and the technology is advancing so far, we're reaching the reflection point, which we're gonna hit before we start having these broad conversations.
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And by that time it may be too late.
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Yeah, I it reminds me of we're gonna have a situ not I'm not that I can predict the future, but you know, I think we're all old enough to remember when when the EPA was doing all the toxic cleanup work in the 70s and the 80s from all the unregulated or self-regulated uh manufacturing in America pre-EPA days.
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I I think we're looking at that.
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We're looking at a situation where we're gonna hit the tipping point.
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We've already hit the tipping point, actually.
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And there's gonna be mass adoption, and then there's gonna be unintended consequences, and we're going to once again be playing defense and cleanup and be in crisis mode as opposed to being forward thinking and taking our time.
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And part of the reason they won't take their time, can't take their time on the AI side, is because this is a glob this is sort of a global quest for AI domination now.
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So it's well beyond Main Street America.
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And we've sort of lost agency in this battle to the major multinationals and to defense contractors and all of the larger and you know, the governmental entities that all see this as a global battle for who owns, you know, who is the global dominant country for AI.
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And so it's it's really beyond us in a lot of ways.
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So we have to control what we can control, especially if we're small businesses.
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And we have to be transparent and honest and forthcoming and thoughtful.
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Yeah, and to Heather's point, this is not just a domestic issue.
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I mean, you're the EU has pulled back on their AU AI regulations.
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So this goes beyond U.S.
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borders.
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This is this, as Heather said, this is a global issue.
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And you've got, if you believe the headlines, you've got the two major competitors, which is us and China, you know, and in any competition, there's only one winner eventually.
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Uh I don't know what's going to happen.
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I'm not sure I want to be around when it's all done.
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So Well, you know, one of the things I I I I do notice, and obviously when um these AI companies uh come up with something new, that's a huge explosion of of uh information and uh rush to the stock market to buy some stocks.
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Nvidia, I think, sets some sort of a record based on uh when they uh went public, uh, how many people bought the stock.
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And it's well and continue to go on.
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Right.
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Well, Anthropic's gonna go public, Elon Musk, his AI is gonna go public.
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And you're right, these valuations are just you know astronomical.
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Just speaking personally, I would never invest in an AI lab.
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I might invest in somebody who's in the infrastructure of AI labs, but I wouldn't put my own money in an AI lab, and maybe you know, five years from now I'll come to regret that statement financially, but you know I it's just, you know, again, I I was just reading, I was telling somebody earlier, I was just reading an article over the weekend about some AI lab is experimenting with AI in medicine to the point where the vision is to replace human doctors with AI.
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Personally, I'm not real comfortable with that.
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I'm I'm sure a lot of other people aren't gonna be very comfortable either.
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And I don't think a lot of people would be very comfortable with taking the human out of the loop because what their tests so far have shown that medical diagnoses using AI are three three-quarters of the time wrong.
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You know, again, AI has some wonderful uses, but talking to a human doctor and talking to an algorithm are totally different things.
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You know, just another quick curiosity.
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I just wonder if you two of you had thought about maybe doing an op-ed piece in the Wall Street Journal on this.
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We have talked about not recently, but we have talked about it.
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Yeah, we've talked about it, or maybe doing something for Harvard Business Review, but we haven't submitted it yet.
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But that's a that's a really good if you vote for us to do that, maybe we should rethink that.
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Yeah, maybe maybe it's time to revisit it.
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Maybe it's time to revisit it.
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I I think if I were going back to the question you brought up earlier, Peter, if I was counseling small to mid-size agencies or small to mid-size businesses that were asking about should we use AI?
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I would say two things to consider.
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And I would say, yes, you can implement it cheaper.
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But and Greg kind of alluded to this earlier, but this is gonna remind me of the streaming or the promise of cable.
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I don't know.
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Do you guys remember when cable was eight dollars and an HBO came out and cable came out and uh they said, Oh, this is gonna be the greatest invention ever in television, and you're gonna be able to watch all these channels that are not public, and you have all this stuff for eight dollars.
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Well, I don't know about you, but it's not eight dollars anymore in my budget.
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And then they did the same thing when they did streaming, streaming is a great alternative.
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To television because you don't have to have ads, you pay a fee and it's ad-free.
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But now it's it's broken, everybody has their own streaming service.
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And so if you want to watch you have to you have to subscribe to like six different services to watch all your favorite shows that you used to just be able to turn on the TV and watch.
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And then also on top of that, you know, you have ads, and even if you're paying.
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So what we have seen in the past in media spaces is the promise, it's almost like a loss leader.
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They draw you in, they bring you in on some kind of like a cheap plan.
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This idea that I can belong to Claude for you know or Chat GPT or something and use their tools to run a PR agency, for example, you know, on a hope and a prayer and a string budget, that that works at first.
00:23:21.280 --> 00:23:39.920
But if you want to grow in scale, and then you're going to need human ingenuity and creativity, and you're going to need to really think through what happens when you become over-reliant on technology and then you can't afford to afford the new subscription price.
00:23:39.920 --> 00:23:41.840
That's one thing I would tell people to think about.
00:23:41.840 --> 00:23:50.000
The other thing I would tell people to think about is there's a huge boomerang effect culturally with young people in the digital world.
00:23:50.000 --> 00:23:53.520
We're we're noticing Gen Z is in droves.
00:23:53.520 --> 00:24:02.240
They're getting off dating apps, they're getting off of video games, they're craving deeply human connection because they've been raised without it.
00:24:02.240 --> 00:24:07.759
And there's a prediction that the that people want to deal with people.
00:24:07.759 --> 00:24:14.000
They're tired of calling and pressing one and and waiting on hold and chatting with chat box and customer service.
00:24:14.000 --> 00:24:27.200
And so I think the agency or the small business that learns how to implement AI in a way that truly does increase efficiency but does not replace humanity is going to be the winner.
00:24:27.200 --> 00:24:30.240
And that's what I mean when I say control what you can control.
00:24:30.240 --> 00:24:44.640
But don't get so caught up in it, like Greg is saying, that that you run with it and you build this big agency or this this main street business that's totally dependent on technology where the subscription triples and quadruples and you can't even keep up with the cost.
00:24:44.640 --> 00:24:51.200
Or where people feel completely disconnected from your business because there's no human element to your business anymore.
00:24:52.000 --> 00:24:54.800
Or your technology gets hacked or hijacked.
00:24:54.800 --> 00:25:01.759
You know, I I sometimes get teased by younger counterparts because I like to pay in cash, and when they laugh at me, I say, Yeah, but you can't hack cash.
00:25:01.759 --> 00:25:02.480
Okay.
00:25:02.480 --> 00:25:07.840
You know, we're all old enough to remember when PCs came into the workspace, into the work environment.
00:25:07.840 --> 00:25:11.920
And I can remember the early promise, oh, this is gonna, you know, we're gonna cut down on paper use.
00:25:11.920 --> 00:25:14.240
Well now, you know, we use paper more than ever.
00:25:14.240 --> 00:25:17.520
You know, because you print everything.
00:25:17.520 --> 00:25:25.680
You know, you print emails, you print, you know, it's because nobody wants to read, and your human eye doesn't like large blocks of copy on a screen.
00:25:25.680 --> 00:25:27.520
So people print stuff out.
00:25:27.520 --> 00:25:30.800
So, no, it didn't live to up to the promise at all.
00:25:30.800 --> 00:25:39.280
In fact, the opposite was you know, it it's both fascinating to watch and also a little scary, but I don't think anybody has an answer yet.
00:25:39.680 --> 00:25:58.480
Well, look, you know, one of the things uh uh that came to my mind as I listen to you, because I think maybe when I talk to you, Greg, and several other college professors, one of the biggest complaints that they have about students is that they can't stand up and speak on you know to uh folks that are so busy with the computers or phones, being able to communicate with people.
00:25:58.480 --> 00:26:08.160
But they also want to find out when they go to a company what social things are you doing to help the community or the environment, those are sort of things that they care about.
00:26:08.160 --> 00:26:16.800
So if uh you know I can handle the stuff that you want me to do in terms of uh your computer and AI.
00:26:16.800 --> 00:26:20.960
But what are you doing totally to help the world of the community and so forth?
00:26:20.960 --> 00:26:25.440
That seems to be a could be a complexity somewhere in this discussion.
00:26:26.240 --> 00:26:29.520
Yeah, well, I can only speak for the students I teach.
00:26:29.520 --> 00:26:31.200
They're not on the phones in my classes.
00:26:31.440 --> 00:26:31.920
Oh, okay.
00:26:32.160 --> 00:26:33.120
I don't want them.
00:26:33.120 --> 00:26:44.560
But I also will say that my observation is that the these gent you know, last few years or so, ten years of college students, they are engaged in the community.
00:26:44.560 --> 00:26:48.800
Again, I can't speak for all college students, but the ones I interact with, they are engaged in the community.
00:26:48.800 --> 00:26:51.440
They want to be engaged in the communities.
00:26:51.440 --> 00:26:57.040
They want to, you know, they've been told their whole lives you can be the one to make a difference.
00:26:57.040 --> 00:27:06.240
Okay, they want, they've bought into that and they're actively engaged in trying to make a difference in their communities, however that's defined.
00:27:06.240 --> 00:27:12.320
You know, I think there's this fallacy that, oh, the digital generation, they're fluent in AI and everything.
00:27:12.320 --> 00:27:14.880
Well, the fact is, no, they're not.
00:27:14.880 --> 00:27:17.440
I don't have to teach them how to prompt.
00:27:17.440 --> 00:27:18.320
They know that.
00:27:18.320 --> 00:27:19.360
They could teach me.
00:27:19.360 --> 00:27:27.600
I need to teach them how to think and decide if the prompt is the right thing to do, or if you're gonna use a prompt, what are you asking?
00:27:27.600 --> 00:27:31.280
You know, and and help them refine the question.
00:27:31.280 --> 00:27:35.360
And there's it's certainly in education, there's certain things that AI is great at.
00:27:35.360 --> 00:27:36.400
I've I've used it.
00:27:36.400 --> 00:27:41.520
I've been I've been following ChatGP or AI before ChatGTP became a thing.
00:27:41.520 --> 00:27:46.800
So I've been observing this for a long time because again, it's nothing new, it's been around a long time.
00:27:46.800 --> 00:27:50.800
It just came into the public consciousness, you know, four or five years ago.
00:27:50.800 --> 00:28:04.480
But one interesting exercise I do, Peter, is I have an assignment for my undergrads where they are required to use AI within certain parameters for an assignment, and then they have to do a reflection piece on how they felt about it.
00:28:04.480 --> 00:28:07.600
And overwhelmingly, they don't like it.
00:28:07.600 --> 00:28:14.880
It takes too much time, it's not original, I have to go back, you know, it's I could have done this quicker and better myself.
00:28:14.880 --> 00:28:17.280
And my point of view is good.
00:28:17.280 --> 00:28:18.400
I'm glad.
00:28:18.400 --> 00:28:20.240
That's exactly what I want to hear.
00:28:20.640 --> 00:28:27.040
Well, you know, what that says to me is that sometimes people have to experience things to fully understand how they work or how they don't work.
00:28:27.200 --> 00:28:28.640
And no question.
00:28:28.640 --> 00:28:29.759
I think that's human nature.
00:28:29.759 --> 00:28:30.320
Right.
00:28:30.640 --> 00:28:38.400
So, you know, I'm not surprised to to hear that sort of thing because, you know, when it's being described to you, people only talk about the good side of it.
00:28:38.400 --> 00:28:46.080
But if you dig a little deeper, there's something that maybe you did not know, and and once you hear it, you you don't want to go any further.
00:28:46.640 --> 00:29:03.680
I I think it's really important to understand and really reflect on for our generation and and the one above us who are pretty much still running a lot of these organizations, to reflect on the sociocultural sort of consequences of what we've done.
00:29:03.680 --> 00:29:08.800
We've spent twenty-five years raising this current generation that's coming into the workforce.
00:29:08.800 --> 00:29:12.400
Millennials to some degree, and and Gen Z for sure.
00:29:12.400 --> 00:29:18.400
We spent twenty-five years basically scaring them about the end of the world.
00:29:18.400 --> 00:29:21.200
You know, climate from a climate perspective.
00:29:21.200 --> 00:29:44.400
There's been political argument and you know, after political argument and the UN SDG goals and everything where where they came and we told them not not not us three, but as a society, the elders in society tell told the younger generation solve this problem, solve this problem, solve this problem.
00:29:44.400 --> 00:29:49.600
And then they all became basically warriors for climate.
00:29:49.600 --> 00:29:52.720
So, yes, they want the world to be a better place.
00:29:52.720 --> 00:29:55.280
We said, be social change agents, go do this.
00:29:55.280 --> 00:29:59.120
We also said go get a degree and and and do all these things.
00:29:59.120 --> 00:30:10.640
This young group of people feels betrayed and tricked because they did everything we asked collectively in our gener uh older generations of them.
00:30:10.640 --> 00:30:19.440
They went to school, they got good grades, they learned about the climate, they they go pick up trash, they recycle, they don't use plastic straws, they do all the things.
00:30:19.440 --> 00:30:37.440
And then this thing called AI comes in as like, oh, it can do it faster, smarter, quicker, for cheaper, and but by the way, it uses three times the amount of electricity and water, and we have to like tear up Mother Earth for the rare minerals to make it run.
00:30:37.440 --> 00:30:39.680
But don't, but don't worry.
00:30:39.680 --> 00:30:43.360
And there's and and it's gonna take your job.
00:30:43.360 --> 00:30:52.320
So, like the sociocultural effect of what we've done to a generation, there's gonna be generational trauma from this.
00:30:52.320 --> 00:30:59.440
So it's really not like it's a much deeper the sociologists and are gonna be looking at this for for the next fifty years.
00:30:59.440 --> 00:31:10.160
It's a much deeper question of corporate values, of whether it's a family-owned business, a main street business, or a Wall Street business, of what are we doing here, folks?
00:31:10.160 --> 00:31:12.640
Do we care about the climate?
00:31:12.640 --> 00:31:19.759
Or was that really not it was did we only care about the climate until we found the next big invention that's gonna make people a lot of money?
00:31:19.759 --> 00:31:31.120
And do we care about sort of this existential crisis we've created in young people, or are we just gonna call them, you know, fragile snowflakes and tell them to get over it and move on?
00:31:31.120 --> 00:31:42.880
And so like I don't mean to be super vigilant or anti-organization because I I myself am a business owner, but I'm also a parent of two Gen Z kids.
00:31:42.880 --> 00:31:47.120
And I'm also a professor who's listened to hundreds, if not thousands.
00:31:47.120 --> 00:31:52.240
Between Greg and I, we've we've had thousands of students in the last 25, 30 years of teaching.
00:31:52.240 --> 00:31:56.080
And we hear, we hear their concerns and we hear their worries.
00:31:56.080 --> 00:32:13.920
And so I think that what we wanted to do when we wrote our book was kind of just, you know, it's I guess it's the equivalent of my grandmother grabbing me by the ear and kind of like pull pull these organizations back to the table and say, Hey, let's take a look at what you're doing here.
00:32:13.920 --> 00:32:15.840
This is not all about dollars and cents.
00:32:15.840 --> 00:32:20.160
There there are a lot of effects in the ecosystem.
00:32:20.160 --> 00:32:24.080
There's a lot of ripples going on and they need to be discussed.
00:32:24.080 --> 00:32:41.600
And it it it is not as simple as how do we make a PR agency run smoother, or how do we do PR for a firm that's trying to talk about social advocacy on one hand, but on the other hand, they're using all the swat water supply in a small town and people's electric bills have tripled.
00:32:41.600 --> 00:32:46.160
Like those are problems that really deserve real conversations.
00:32:46.160 --> 00:32:53.040
And I hope I hope the elected leaders and and the folks sitting in boardrooms start having those conversations.
00:32:53.360 --> 00:32:57.759
Yeah, what one of the one interview I did that talks about this on a global scale.
00:32:57.759 --> 00:33:25.200
I interviewed somebody in the UK, works for a global insurance company, and she pointed to a fact that a company can have their carbon neutral targets, you know, set for 2030, and making really good progress and being very open and transparent about it, and they're right on target, and then for perfectly legitimate reasons, they make an acquisition that makes business sense, but since they're carbon neutral target that back five, six years.
00:33:25.200 --> 00:33:26.880
So how do you explain that?
00:33:26.880 --> 00:33:31.600
And that's again where you know we're talking profit first.
00:33:31.600 --> 00:33:34.000
And again, we're not anti-profit.
00:33:34.000 --> 00:33:37.200
I think what Heather and I are saying with this book is you can be both.
00:33:37.200 --> 00:33:45.920
You can and in fact, there's research out there that shows that companies who do both tend to be more profitable long term.
00:33:45.920 --> 00:33:49.040
So there is a dollar and cents to this.
00:33:49.040 --> 00:33:50.400
Improved reputation.
00:33:50.400 --> 00:33:55.360
There's it's been quantified in dollars and cents what reputation means.
00:33:55.360 --> 00:34:03.520
So I think and so much of what we look at from the Western canon is the global north or the far east.
00:34:03.520 --> 00:34:06.480
Well, nobody's really talking about the global south either.
00:34:06.480 --> 00:34:10.559
You know, and that you know, that's a whole nother conversation around the issue.
00:34:10.559 --> 00:34:13.440
So, you know, you could do a whole podcast just on that.
00:34:13.440 --> 00:34:16.639
So this really is a global issue.
00:34:16.639 --> 00:34:25.759
You hope, being the world's leading economy, that the US will try and maybe take a lead in this, but I don't see that happening anytime soon.
00:34:26.239 --> 00:34:27.280
Well, let me say this much.
00:34:27.280 --> 00:34:37.679
I mean, I had no idea that the you know you know the the structure that the you know we just talked about the competition, if you will, between AI and uh ESD and uh TSD.
00:34:37.679 --> 00:34:43.199
But uh you know that's something I think that the people are paying attention to.
00:34:43.199 --> 00:35:08.079
So somebody around the world is gonna pay attention to it uh and you know maybe take some action in some somewhat wave form of action.
00:35:08.719 --> 00:35:15.679
So this is Yeah, and I don't want to paint again too broad a brush because there are organizations, companies who are doing this.
00:35:15.679 --> 00:35:18.960
You know, there are some really good players in this field.
00:35:18.960 --> 00:35:20.079
It's just not enough.
00:35:20.639 --> 00:35:31.199
Well slowly but surely, you know, sometimes uh the people to see what the what the actual benefits are or the downsides are some things takes a little longer than you would expect.
00:35:31.199 --> 00:35:36.159
But uh, you know, sometimes uh uh this might be just one of those.
00:35:36.159 --> 00:35:42.480
And so this is uh something that you know still got past me, uh but I'm glad you guys decided to bring it here.
00:35:42.480 --> 00:35:50.239
I I certainly appreciate having an opportunity to get involved in it uh from this point of view and also to uh uh share it with other people around the world.
00:35:50.639 --> 00:35:51.839
Well, it's it's our pleasure.
00:35:51.839 --> 00:35:54.639
I mean we are we are on a campaign on this stuff.
00:35:54.639 --> 00:36:04.159
I mean Heather and I are are are really No, we're and I don't mean that in a public I mean, yes, in a in a in a form of public relations campaign.
00:36:04.159 --> 00:36:17.119
Obviously, we're trying to get publicity for the book, but but the much deeper than that is we care deeply about this issue, and what we found when we started thinking about writing a book is who else is out there talking about this?
00:36:17.119 --> 00:36:20.079
And what we found is not really very many people.
00:36:20.079 --> 00:36:24.159
You know, there are there are people who write books on ESG, and it's the E.
00:36:24.159 --> 00:36:25.519
Another book is on the S.
00:36:25.519 --> 00:36:28.000
Almost nobody's talking about the G part.
00:36:28.000 --> 00:36:33.839
But it's as to use Heather's term, it's very siloed, and what we want to do with this book is like it's almost a primer.
00:36:33.839 --> 00:36:46.639
And it's like, well, wait a minute, let's step back and look at this issue holistically, because it's a lot more than just environmental damage, which I'm not trying to diminish, but this issue is much bigger than that.
00:36:46.639 --> 00:36:47.839
Yeah.
00:36:48.319 --> 00:36:56.639
Well, you know, that that's another angle that I think people need to fully understand, too, if they've got that sort of negative impact on the environment, that people need to hear about it.
00:36:56.639 --> 00:36:57.759
So that's another reason.
00:36:58.079 --> 00:37:01.599
I thought maybe we need to write two columns, two off-ads for the Wall Street Journal.
00:37:02.239 --> 00:37:06.879
Yeah, we I mean, you know, or or get our own Substack going.
00:37:06.879 --> 00:37:14.799
But the reality is just that these are gonna be we're not putting the genie back in the bottle, right?
00:37:14.799 --> 00:37:17.359
So AI's not going anywhere.
00:37:17.359 --> 00:37:30.799
So now we're in a situation of since it's here and it does have a good business use case for a lot of organizations, how do we sort of manage it ethically?
00:37:30.799 --> 00:37:33.920
Right.
00:37:33.920 --> 00:37:38.400
Or before it gets how do we manage it ethically and how do we align?
00:37:38.400 --> 00:37:51.359
I mean, you know, it's a there's a huge misalignment and there's a big, big misalignment between between what organizations say they value and how they're behaving in this space.
00:37:51.359 --> 00:38:13.440
So how do we help organization and I and here's the interesting thing about that, I don't even realize I don't think they realize how misaligned they are because as I said earlier, the left hand doesn't talk to the right hand, the the business you know, the chief technology officer and the growth officers or the people in FA are not talking to the comms team and the PR and the CSR people.
00:38:13.440 --> 00:38:18.319
And so they're just kind of going about their own work without even connecting the dots.
00:38:18.319 --> 00:38:20.400
And so I don't think it's intentional.
00:38:20.400 --> 00:38:23.599
I don't think they're trying to hide anything from the public.
00:38:23.599 --> 00:38:26.960
I just don't think enough thought has been given to the problem.
00:38:27.359 --> 00:38:27.679
Right.
00:38:27.679 --> 00:38:30.719
They I don't think they're even aware there are dots to connect.
00:38:31.039 --> 00:38:31.440
Correct.
00:38:31.759 --> 00:38:47.039
Well, you know, the other thing that came to mind when you were mentioning this is that, you know, maybe you guys should be down at the Chamber of Commerce and talking to uh those folks, uh, you know, because these businesses are the ones that uh have some some say in uh how these things are going to be finally resolved.
00:38:47.679 --> 00:38:48.000
Yeah.
00:38:48.000 --> 00:38:50.559
Well we we I don't know if you know anybody at the U.S.
00:38:50.559 --> 00:38:52.159
Chamber of Commerce, Peter, we'd love to.
00:38:52.480 --> 00:39:03.519
Well uh or the business roundtable too, because the business roundtable puts out that report every year talking about their ESG accomplishments and their DEI accomplishments.
00:39:03.519 --> 00:39:09.599
And meanwhile, those same organizations, a lot of those are banks that are funding the AI growth.
00:39:09.599 --> 00:39:13.440
So it's kind of wild.
00:39:13.839 --> 00:39:16.639
Yeah, talking out of both sides of the mouth at the same time.
00:39:16.719 --> 00:39:27.119
So well, it seems like I mean you guys have a real I mean, this is a major issue that uh obviously needs uh uh far more uh uh exposure and at some very, very high level.
00:39:27.119 --> 00:39:32.559
You know one thing now that I think about because I did work in Congress for a number of years.
00:39:32.559 --> 00:39:42.000
You might want to talk to your senators from uh presentation to Congress like this.
00:39:42.000 --> 00:40:16.159
Uh let me say that uh people are locally uh people to respond to me, but people who are honestly that people have called them based based on some of what they were talking about on this podcast.
00:40:16.159 --> 00:40:25.440
So if I can help you with this, please please let me know and what I am because I'm gonna move forward on making sure that this goes uh we'll get on the air.
00:40:26.960 --> 00:40:30.079
We're happy to have the ability to share it with your audience.
00:40:30.079 --> 00:40:36.079
So thank you for and thank you for raising it and realizing what a concern it is and raising it to the attention of your audience.
00:40:36.480 --> 00:40:43.920
So one of the purposes of this uh of the time when I put this podcast together is what I want to get out of this podcast by putting it together.
00:40:43.920 --> 00:40:48.239
So that I can use that in my everyday work.
00:40:48.239 --> 00:40:59.839
Well, when I hear about this conflict of AI and EST and so forth, people need to hear about the response.
00:40:59.839 --> 00:41:10.879
So let me say that.