Episode 11, Part 2 - Fears & Foresight of AI Adoption with Athena Peppes
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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. We'll cover all aspects of leadership, sales, account development and customer success, alongside other critical elements required to build an effective growth engine for your business. This podcast is aimed at leaders from exec all the way down to line managers. Welcome back. 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?
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