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.

Welcome back. We're here to continue our

conversation with Athena Peppes, founder of Athena Peppes

Consulting and Beacon Thought Leadership. Ethics is such a

huge topic that exists in that you mentioned that earlier with

they can is it going to take away people's jobs? Is it going

to various other things as well? All right, there's already

questions. You mentioned the new regulation around AI, like

questions though, that 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 that, is that an area that

you're seeing is that becoming kind of heightened problem? Is

that, like, I mean, short, short it's going to slow us down a

little bit. But what, sure, what are you seeing in the market

around the 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 has always had 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

they had no liability to pay the money back. Now that did not go

down well, no, no, but they just that was their, their kind of

argument. But there's all sorts of kind of illegal implications

around that.

Do you know the outcome of the case? Did they

get laughed out of court?

Yes, they did.

Yeah, yeah. 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 are 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 that for companies to figure out the

second ones around bias. So I use, 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 they're biased, and I I'm sure they're getting better,

or at least, I hope. But I was writing a piece around the

economics of 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.

Dall-E. I used Dall-E, but straight away gave

me a man with white hair, obviously, you know, like middle

aged white man. I was like, Okay. And then, because I've had

this experience before, I just thought, I wonder what would

happen if I swapped the profession so I could, I you can

prompt it to try and get different things and say, Oh,

give me more diverse and everything. But I was like, what

if I just swapped the word economist for nurse, and

straight away, gave me a woman. So of course, they are because

they're, they're, they're trained on information that

we've created, and we all come with our own biases. But how do

we do we have a responsibility, as you know, as an organization,

to not perpetuate those biases as well, if you're using those

tools, then there's the the data privacy issues that we've

touched on as well. How do you get around that deep fakes that

would that's the fourth one, and I think that's something that's

particularly concerned 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, but there we go.

But that's not to say that it will it all will be,

but you, you know 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, this conversation in

person. We put greater value on this than on something that was

just artificially generated. 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 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, 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 that technology better.

On that point, I was curious about that last

point, and I suppose it's really hot topic for for anyone

involved in in a growth role, whether that's, you know,

marketing, sales, consultancy, whatever that may be, a customer

success. When you think about that, that job piece, not naming

names. If we think about CEO that lasts of 10 years in

software as surface 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 backs. It's like quite aggressive. 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, we actually know common

guys, that you got to not worry too much about growth, and

actually you got to 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, it's quite diverse. I would say, I

think you're right that if we looked at the past, say, for

instance, when smartphones and social media kind of became

commonplace, there was a lot of issues around, 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 it's there's a feeling that, oh, this is

becoming a lot bigger in terms of the impact on jobs. I don't

know if that, if you can generalize about how CEOs are

are seeing this. I think the the CEO of Klarna, 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, there's always the

economic incentive of the thing. There's an IPO coming up and,

yes, good. So there's issues like that.

Is it a language pattern that creates fear in the

current sort of market of job and point 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 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, going to retire? 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, this view of

because there's a there's a point at which AI is already,

I'm picking on AI there, obviously other, but AI is, 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 manufacturing,

for example, that was probably sort of slower, maybe more

expensive 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 gonna, you know, the

example that you shared there, Athena, that you know, well, 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, you know, the next generations are

going on, and the enabler of, okay, we're making sure that

we're training in 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 and I think that's probably the bit that concerns

me, sorry, is the pace is probably different, to say,

previous transformations.

Yeah, and I think you know, the things you touched

on as well about the border perspective, right? So it helps

to think, to think of this from a macro economic perspective.

CEOs, I think, would generally think about it in the context of

the organization, but the issues that come up, like you

mentioned, around education, the future and how do we plan for

our economy? Companies, 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? So in the economics

field, there's a huge debate around the impact of this on 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's not good enough

predictor of what's coming in the future. So does that need an

AI model to just work? Yeah, but 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 think, to help them think

through these kind of questions that that might come up. So it's

yeah, it's a it's a huge topic. I just feel that the 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 as a citizen, as

well.

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 so really kind of political but if I look

at the corporations 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 consent I maybe have this, 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

supported, and that's why I asked the question around kind

of policy makers and their role in this, I think there's a

really important part to play there.

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 without what it means for jobs? And

arguably, they have, so they have doubled the role to play,

in the sense of both balancing that as the public sector, but

also in terms of the policy makers within that, doing, you

know, thinking about that for the whole economy.

I'm really curious, and we've talked about AI, I'd

say that is in 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 is going about now? What's the next

thing? Do you have a 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 into the 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 you know, whole teams focusing

on how organizations can deliver on those goals. So something

similar is happening with with AI. I think what people worry

about a lot individuals, is 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 question possibly.

So 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 you know, 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 that 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 comments.

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.

Seize the day?

Yeah, I am 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.