The Growth Workshop Podcast
Episode 11, Part 2 - Fears & Foresight of AI Adoption with Athena Peppes
Mon, 16 Dec 2024
Athena delves into the ethical challenges surrounding AI adoption, outlining 5 crucial areas for consideration: accountability, bias, data privacy, deep fakes, and job impacts. She emphasises the importance of critical thinking when using AI tools and discusses the potential effects on employment, citing examples like Klarna's significant job cuts due to AI efficiencies. Peppes also explores the broader economic implications of AI adoption, highlighting the need for balanced decision-making that considers both growth opportunities and societal impacts, while stressing the importance of understanding and adapting to these technologies at individual and organisational levels.
Hello and welcome to the Growth Workshop Podcast with your hosts, me, Matt Best and Jonny Adams. In this podcast, we'll be sharing insights from our combined 30 plus years experience and hearing from other industry leaders to get their thoughts and perspectives on what growth looks like in modern business.
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We're here to continue our conversation with Athena Pepe's, founder of Athena Pepe's Consulting and Beacon Thought Leadership. Ethics is such a huge topic that exists in that. You mentioned earlier, is it going to take away people's jobs? Is it going to...
various other things as well right there's already questions you mentioned the new regulation around um ai like questions over the ethics that sit behind that you know putting out videos that have got people's faces when they weren't actually there representing something that they wouldn't necessarily believe in or support is that what's your perspective and take on that is is that is that an area that you're seeing is that becoming kind of heightened problem is that like i'm going to short it's going to slow us down a little bit but what's your what are you seeing in the market around
that ethics challenge.
Yeah, I'd say it's a huge issue, as you say, and there's like so much to think about. I think it can also feel, my thing is always how to simplify stuff, right? And because it can feel like, where do I start? I always have in my mind kind of five things to structure a conversation around this and to help
think through different issues the first is around accountability who is accountable for the information that your AI enabled bot gives now this might seem like a straightforward question but there was an interesting case earlier in the year of Air Canada that basically argued that the bot which had given mistaken information to one of the customers that was trying to get information around bereavement fees they argued that the bot was responsible and
And they had no liability to pay the money back. Now, that did not go down well. That was their kind of argument. But there's all sorts of kind of legal implications around that.
Do you know the outcome of the case? Did they all see you get laughed out of court?
Yes, they did. Become a bit more human. Yeah, exactly. They did. But then you can get into a little bit more detailed questions of like, well, is it the executives that kind of approved that? Is there any responsibility with the team that designed it? What about if it was supplied from a third party? So there's like so much complexity there, right, for companies to figure out.
The second one's around bias. So I use these tools quite a lot because I personally think they help my productivity immensely. They save me so much time. And I just love experimenting with different things. But this is the importance of critical thinking always is I can see that they're biased and I'm sure they're getting better or at least I hope.
But I was writing a piece around the economics of AI and I wanted an image of an economist pondering the future of productivity.
So where did you go to find the image? That's the question.
Dali. I used Dali, but straight away he gave me a man with white hair. Obviously, you know, like middle-aged white man. I was like, OK. And then because I've had this experience before, I just thought, I wonder what would happen if I stopped the profession. So I could, you can prompt it to try and get different things and say, oh, give me more diverse and everything.
But it's like, what if I just put the word economist for nurse and straight away gave me a woman? So of course they are because they're trained on information that we've created and we all come with our own biases, right? But how do we have a responsibility as an organization to not perpetuate those biases as well if you're using those tools?
Then there's the data privacy issues that we've touched on as well. How do you get around that? Deepfakes, that's the fourth one. And I think that's something that's particularly concerning because there's so much synthetic media at the moment and the quality of it is amazing. One that might interest you is, have you seen the Google LM tool that now creates podcasts from articles?
No, I heard about that, but there we go.
But that's not to say that it all will be, but that also makes you think about your own job. How can you use it to do your job differently, perhaps? Or perhaps as humans, we value the fact that that was, that we all got together here and had this conversation in person. We put a greater value on this than on something that was just artificially generated. Yeah.
And then the fifth one is around jobs. And I think that's a huge one because it sometimes gets not mentioned very much in the light of like productivity benefits, which there are many. But I think it's better not to hide away from the conversation and to think about what would that mean for the impact on your people? Will that mean job losses? And if it does, how do you handle that?
What's your responsibility to upskill your people and help them understand the technology better? Yeah.
Not on that point. I was curious about that last point. And I suppose it's a really hot topic for anyone involved in a growth role, whether that's, you know, marketing, sales, consultancy, whatever that may be, customer success. When you think about that job piece, not naming names, if we think about a CEO, the last sort of 10 years in software has surfaced has been growth at all costs.
So they would pretty much do anything to get to where they need to get to, especially their VC bags. It's like quite aggressive. Right. Do you think that a CEO and those types of C-suite actually will continue to think about growth at all costs at the absence of job losses at maybe sort of, may I say, middle to lower tier?
Or do you think that actually there's going to be some of that ethical sort of input where actually, you know, common guys that you've got to not worry too much about growth and actually go think about the society and the people within your function? Do you have a theme or a trend that people are talking about? Or maybe it's a bit too early. I'm not too sure.
Yeah, it's quite diverse, I would say. I think you're right that if we look to the past, say, for instance, when smartphones and social media kind of became commonplace, there was a lot of issues around that. Maybe not necessarily on jobs, but kind of parallel issues that we could learn from.
And what we saw is that we were very slow, our institutions were very slow to adopt to those kind of issues and help people. Automation would be one example of that, right? Loads of jobs got automated. I think now there's a lot, the kind of jobs that will be affected are not just manual jobs, but also manual routine jobs, but also knowledge workers.
And perhaps that's why we are seeing much more of a discussion because there's a feeling that, oh, this is becoming a lot bigger in terms of the impact on jobs. I don't know if you can generalize about how CEOs are
are seeing this i think the the ceo of um clarna the payments company said that they they got rid of 1200 jobs because genitive i was helping their marketing and sales teams do things so much faster and he said actually that they can that they'll only be able to function with 2000 people i think as opposed to perhaps nearly double that now or something like that
But there's always the economic incentive of the thing. There's an IPO coming up.
Yes, of course.
So there's issues like that.
Is it a language pattern that creates fear in the current sort of market of job employment where, you know, job cuts or is it, you know, are people being redeployed well enough? You know, it has to come in one hand that I get the efficiency model because I'm trying to sit there if I was a CEO and think, well, I've got the pressure of the board, I've got the pressure of investors. Do you know what?
I'm five years away from exiting and going to retire. Yeah. Would I go for it? You know, would I would I cut headcount and use some type of really because that's what everyone's telling me is that AI is going to solve my efficiency problems. I don't know. I've been noodling on that one. And I guess that I don't know which way people would turn.
I sort of gear towards this view of, because there's a point at which AI is already, I'm picking on AI, there are obviously other, but AI is already helping in finding efficiencies that makes people more productive, that can result in more growth. But I think to your point is, well, that growth at all cost, where does that sort of
kick in and start to become a problem or where does it become just, are we just going to find this natural equilibrium? And it just becomes a, Hey, look, there's going to be a sort of reassignment. I think my biggest concern is the pace.
So with other transformational changes, we think about in other industries in the past, you sort of automation in, in manufacturing, for example, that was probably sort of slower, maybe more expensive, but, than say AI could be, where it's so, everything's in the palm of your hand much, much faster.
That means an organization could tomorrow say, we're going to, you know, the example that you shared there, Athena, that, you know, we can cut 2000 jobs kind of almost overnight. And I think it's the pace of that, that might be the thing that hurts us because behind all of that, you've got the knock-on effect to education and to the journey that our
you know, the next generations are going on and the enabler of, okay, are we making sure that we're training them the right thing? You know, how much is AI prevalent in education in schools at the moment? Or is it just being left down to kids just learning through the way that they learn?
And I think that's probably the bit that concerns me slightly is the pace is probably different to say previous transformations. Yeah.
Yeah, and I think, you know, the things you touched on as well about the broader perspective, right? So it helps to think of this from a macroeconomic perspective. CEOs, I think, would generally think about it in the context of their organization, but the issues that come up, like you mentioned around education in the future and how do we plan for our economies, those are much bigger issues.
And it's not as commonplace to find CEOs that might have that vision. Arguably, some of that might come from us, right? What expectations do we have from these organizations about their responsibility to actually create jobs? Yeah. So in the economics field, there's a huge debate around the impact of this on jobs. I'm not sure there's a conclusion yet.
There's a bigger argument because most of the ways that they would estimate what the impact would be is based on previous waves. of change, and perhaps the data there is not a good enough predictor of what's coming in the future.
Does that need an AI model to just work?
Well, you see the kind of challenge with doing that. There might be new jobs being created, right? There definitely will be. There are loads of philosophers now being hired by big companies to help them think through these kind of questions that might come up. So it's, yeah, it's a huge topic.
I just feel that as individuals, the more we understand the technology, the more we use it, the more we learn about it, the more prepared you are to influence that change as well, whether as a consumer, you know, as an employee, as a citizen as well. Yeah.
it's connecting those things, isn't it? And I think that's going to be the challenge. And we're in danger of kind of diving into something really kind of political. But if I look at the corporation's response to, you know, climate action planning and that kind of thing, it's not been all that proactive, right? It's very much, okay, I'm forced to now do this.
And I guess the concern I maybe have is my personal opinion is that if we have that same approach to some of this, you know, some of the kind of technology and it's not, And that's why I asked the question around kind of policymakers and their role in this. I think there's a really important part to play there.
No, absolutely. And again, they have the same actual trade-off that the C-suite executives have, right? Because arguably there's a huge case to be made for how you use AI in the public sector, which definitely needs improvements in terms of efficiency and services that need to be provided to people. So the opportunity there is huge.
But then how do you kind of balance that with what it means for jobs? And arguably they have, so they have double the role to play in the sense of both balancing that as the public sector, but also in terms of the policymakers within that doing, you know, thinking about that for the whole economy.
I'm really curious. And we've talked about AI, I say that as a general term, not today, but in every space that I can even think of. And what's beyond AI? And I know you think about that and talk about that a lot. But, you know, even past all of this, what's the next thing? Do you have an indication or a hypothesis around that? Is that a fair question to ask?
Well, I think for one thing, I think the whole topic of artificial intelligence definitely has more room. There's a lot of discussion around this being hype and so on. And of course, there's always a little bit of hype when something new comes into the forefront, right? So there is, but the opportunity is definitely there. It's huge. You see some companies appointing chief AI officers now.
into the C-suite board. So in the same way that in the past, if we look at the topic of sustainability, used to be one person doing what was called CSR back then that no one used to take seriously to now someone, whole teams focusing on how organizations can deliver on those goals. So something similar is happening with AI.
I think what people worry about a lot, individuals, is this idea of general artificial intelligence. So this technology being able to completely replicate what we are as humans. But there's just so much that needs to happen for us to get there that I think we won't be around ourselves to discuss that.
I don't need to fear anything. I can feel quite confident that we're going to be okay.
Yeah, but I think it's kind of find that balance as an individual, as a leader, as a team member, whoever you might be, whatever role or hat you might be wearing. What's next is finding that balance between making the most of the growth opportunity that is definitely there. The stuff that these technologies can do, they can just create new content in seconds. We know this.
But how can you make sure that you do that in a way that's forward thinking enough that you don't get caught out by some of the risks or challenges, other issues around that?
I think that's a fantastic place to, yeah, a fantastic kind of final thought, Athena. Thank you so much for sharing that. And I think we had a couple of other conversations recently on the podcast about the importance of that patience. And it feels that we actually need to be a bit patient. We might even need to kind of slow down that decision-making process and be a bit more considered perhaps.
But with that North Star goal of, right, well, what could this do to us to help maximize growth for us personally and also for our businesses?
Yeah, I mean, I think I take your last point. I'm going to capture the opportunity, you know, and thank you for shooting today. Yeah, I feel a bit more calm in the circumstances. So thank you so much for sharing some great insights today.
Yeah, it's been a pleasure to be here. Thank you.
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