Not Replaced, But Enhanced - The Role of AI in Product Management

Speaker A: Hello, uh, welcome to our podcast, where, if you've been watching, you understand that what we do here is talk about how product management can be made practical. Theory's great, but how do we make product management practical for product managers and for the people they work with? So that's what we're, that's what we talk about every time. And today we decided we would start the conversation about AI and its impact on product. We think this is probably a lot of conversations and probably conversations, uh, with others as well as us, but we wanted to start the conversation and we want to talk a little bit about should we be afraid of it? Should we be afraid of AI? Should we be afraid for our jobs? All of the. Do I need to get a new career? All of that noise. So what do you think, Marilyn?

Speaker B: I think this is going to be, this is going to be a fascinating conversation and to your point, it's going to be a multi episode, uh, conversation because I think there's so many directions and so many conversations in this space.

Speaker A: Totally. So, you know, I think as we start to look at this topic, I think what comes up for me is how much. Over the last 12 months, for sure, I've started hearing from my clients and from people in the industry like, this is, this is terrifying. This is it. We're all going to lose our jobs. It can replace product managers, you know, And I also hear engineers saying the same thing, like, oh, I got to find a new career. And I'm like, do you. So is that what we're doing? Because I'm not going to do that. Right? So, um, I mean, same thing for coaches, right? People are like, oh, it's going to replace coaching, is it? Right. So, so I think, Marilyn, the first question I would say is, is it?

Speaker B: If you read the news, the answer is yes, because company is going to like fire 10,000 people and replace them with AI. Um, I do think this is an example of, um, the bigger than the thing. And when you get down to it practically, um, I don't, I don't like, I don't think so. Um, yeah, I don't think so. I think, I mean, AI right now. So it's, um, I think it's only understood by pockets. I think it's widely used. Um, it's widely used for, I don't know, kind of fun things. Unless I think there's two sides of it.

Speaker A: Right.

Speaker B: And I think we've had this conversation a couple times. I think there's like, what do legitimate companies want to do with this? And how can it help unlock what we do on a day to day day? And how does it help, um, how does it help companies and consumers, um, be more effective? And then there is the dark side of everything, uh, including tech, which is how, how do bad actors leverage these tools, um, to do very naughty things? And uh, I think there's a conversation in both directions, but, but we'll talk about it in practical terms first. Um, no, uh, I don't think it's going to replace anybody's job.

Speaker A: What do you think?

Speaker B: Whew. Keep going.

Speaker A: So I guess, you know, when we think about, I think you're absolutely right. There are different directions this can go. I think there's probably a whole podcast about sort of ethics in product management and how it shows up and when you should be like, I'm not going to do that. And when you can, you know, lean in on things. Um, but when we think about how can we use this as a tool instead of being afraid of it, what, what comes to your mind in terms of those, those things?

Speaker B: So I think that um, man, there's so like, I'm gonna laugh because we're gonna talk about frameworks again because I like recently people keep putting frameworks under my nose about how to evaluate where to like leverage AI and like, um, I actually think that, that when you think about it in as like, let's say that I'm a person and I want to be more effective.

Speaker A: Right?

Speaker B: Um, this is like actually having a really smart friend that just kind of hangs out with you all the time that you can talk to about stuff. And it's like, I would say that you shouldn't use it. Like Google search, like, don't be like where's the nearest car wash?

Speaker A: Right?

Speaker B: But try to have a deep conversation with, with the product and then um, give it enough context that it understands who you are, what you're coming from, like where you're coming from, why you're asking some of the questions. And it really does start to become at um, least a sounding board to help you like flow, flesh out your ideas or ideate or you know, think about things from a perspective that you wouldn't have naturally thought about something. Um, so as a person, I think that's, I mean that's how I try to use it. How about you?

Speaker A: Same. I mean, I think they're often what I, what I, the way I'm using it is I'll think like, hey, I wanna, I wanna work on this sort of strategy. I have this thing that I wanna unpack a bit. Here's. Here are my bullet points. Here's my. Here who. Here's who I am. Here's the player I am in this context. Here's what I'm trying to get to, and here are my ideas. Help me. Yeah, right. Like, help me either flesh these out, tell me if they're not. If they don't, if there's something that you think I'm missing, or give me new ones. Right. Like, and really learning how to have that conversation so that it can actually swoop in and be like, oh, hey, yeah, you're on the right track. And there are links here. Like, what you said here actually links to this other thing you said that maybe you didn't see. Right. And I think that can be really helpful because it's the thing we do. Um, if you write, if you, you know, if you're building documents, if you're building roadmaps, you will see those things over time, but having access to those connections faster. Yeah, I love that.

Speaker B: Yeah, right. I also, like, I love the fact that you're, like, product managers do a lot of stuff. Like, there's a large portion of your time that you're strategizing and you're thinking and you're consuming information and you're building a bigger picture. Um, there's a large amount of time where you're, like, writing a doc or putting together a roadmap or doing things that are more. I would say they're not value add, but they're communication tools. Right. And I love. I love the idea of using generative AI or just AI to start to automate some of those tasks, because those are not. They're not great value ads. You need them because they're part of what you need to communicate.

Speaker A: Yeah.

Speaker B: Uh, but it's not the sort of, like, it's not that. It's not the golden place to sort of like spend your human calories.

Speaker A: Right, Right. I mean, and I will even do things like, hey, I'm doing this. Here are the other two documents I've already written. Help me get there. Right. Like, help me frame how I would, you know, say this based on these other things I've done. So I can still use things that I've created out of my own, you know, mind and have it help pull the information and say, ah. Ah. Yes. You are trying to tell this story, right? Yeah. Then I can say, ah, not quite. I'm trying to tell this story. Oh, okay. Let me help you again. You know, and I think, you know, across time, I really have appreciated that element as well.

Speaker B: Yeah.

Speaker A: Um, and kind of to what you said, like, there are so many parts of being a product manager. Part of the reason why it's a hard job is that it is. You know, I always refer to it as altitude sickness. Like you're way up in the clouds looking and seeing the, uh, distance and trying to see where it's going and what's going to happen next and what's around the corner and then you're down in like blade of grassland. Like what is this actual tiny little thing that's happening and what did the team do and what are we going to do about it? And you know, and I think, I think the idea that all of the work that is in there to your point isn't value add, but there, there are places where you could say, hey, given all of this, you know, spit me out some user stories to start with. Right? Or whatever.

Speaker B: Love that.

Speaker A: Yeah.

Speaker B: Or, or like do my testing, uh, you know, as a user, as this user, do like run my test cases. Have I got them all? What else?

Speaker A: Did I miss anything? Right? Because I mean I was, I was always really good at Happy Path and a handful of terrible paths. But then I would be like, someone would say, well, what about this? And I'd be like, I didn't even. Never cross my mind. Right. Like, it would never even occurred to me that that could happen. Right. I mean, I did, I did shut down people's AMEX cards. Testing AMEX cards once. But what do you mean your AMEX card got torn up, shredded, and you have to get a new one? Sorry, you know, like, you know what I mean? Like, uh, and I think there are, there are so many tasks that it would be nice to handover. Yeah, right.

Speaker B: Yeah. Like, I'm not, um, I. So actually, thank you. You just gave me a great idea. I'm not naturally, uh, I'm not naturally. You know how there's some people that like, they, they're insecurity because they're not. They naturally think that way. They instantly think about all the abuse patterns. They instantly think of all of the security holes. That's not me. I like, I love dreaming up magical happy. If it does not have unicorns and rainbows, I probably didn' it up.

Speaker A: Not interested. Right.

Speaker B: But I do think that, that having, you know, as, you know, as a bad actor, find all the holes in this or find all of the abuse potentials, like that's a great way to use, uh, use my, like third party helper, my, my augmentation so, so, all right, we've established that people shouldn't be freaking out about their job, right? But they are afraid and the news is not helping. So let's just say that I am someone who's out there in the universe and I'm a little nervous. Um, how do I get started? What do I do?

Speaker A: Well, I mean, I think my inclination is to say the first thing you have to do is get a little education. Right? You have to understand it. Um, and maybe you don't have to become a AI product manager, right, Necessarily, but you need to be able to understand a little of the history. How did we get here? Because I mean, you know, how. Yeah, a little of the history. How did we get here? What can it do now? What do people think it's going to be able to do? How much of that's real? Right? Like all of these kinds of, you know, pieces. And um, part of the reason I say that is I think some. There are people in the world that just think it's, you know, they're like, well, how is it different than Google? And I'm all, oh, you know, how is it different than any search? And I'm like, hm, well, it's totally different. Right. And it has. Some of the foundation was laid there. Right. But what happens next is different. And I think if you don't have some knowledge of that, you have no idea how you can use it. And so it is a threat. It's. Anything that we're ignorant about makes us scared. Yeah, right.

Speaker B: Yeah. I think that you just, you said something, um, that, that I've had to reinforce, especially with some of, um, the people that I work with that aren't, that aren't so technical. Um, and that is where the fear starts. Right? Fear comes from things that you don't know. Um, search is a thing that's just. You're indexing stuff and you're going and finding stuff that you've indexed. Um, machine learning is a thing. It's been around for a really long time. Um, and that's helping you understand what could be next or predicting what's next based on the information you have. Generative AI is making up something completely new. A lot of times when I hear people talking about gen AI or OpenAI, they're actually not talking about gen AI at all. They're really talking about search or ML.

Speaker A: Right.

Speaker B: Um, and so I think knowing a little bit about the, just the basic terms and, and how, and why you would need any of those things as a product manager. And then I Think there's kind of two aspects to it. One, how do I use this, this thing to. I'm going to call it Hyper Augment myself. Y. Um, you're now going to turn yourself into the Bionic man. And I think that if you think back to like before we all had a computer or before we were all walking around with like an I, um, you didn't actually know. You didn't actually know a lot of stuff. You didn't have all of these tools at your fingertips and you couldn't find the nearest car wash wherever you are in the world. Um, I think that things like Gen AI are going to go the same way. So if you're not using them on a daily basis, um, and you're not getting that familiarity, you're kind of getting left behind a little bit. Um, and then as a product manager, how do you think about starting to use some of these things? Search ML and what I'll say is like automation of tasks and then generative AI, um, in ways that, that really help people. And so I think that, uh, I think that um, how do you. So how do you help your people in your business that may think that you're going to. You, you, Leah, are going to use Gen AI to replace them, right?

Speaker A: I mean, I think you have to have. I think we have to keep having conversations about like, exactly what you said. This is an augmentation tool. How do we use it to make us faster, more efficient, get more information, think of things that we're missing, right? Like, that's what I think is amazing. Like the ability to say, given all of this, what do you know that I don't? Right? Because it, because it will be like, how about this thing? And you're like, uh, would not have thought of that. Right? And so I think using it for that is important and helping them understand, like, I don't want to replace their heart, their creativity, their ability to think like the people we serve, their ability to think about our business. Because let's be honest, like how right now Gen AI does, isn't going to be able to say, oh, this is how this business works and every, all of its nuance. And this is where it's got pockets of, um, politics. And this is where it's got pockets of this, like all of that it can't do.

Speaker B: Yeah.

Speaker A: The ability to then be the glue to communicate, to come in and bring heart to the whole thing and say, hey, we're humans and we're having a human experience. And this is what, this is my Role and product. It can't do that.

Speaker B: Yeah.

Speaker A: So really leaning in and saying, listen, I want you to use it, I want you to learn about it and use it so that we can go faster, that we can make more money, so we can be more efficient, so that we can get things in front of our customers faster. But I'm not replacing you. Yeah, you are not those things. Right. And so sometimes I think it's piecing apart like what is the job and what are the important parts of the job and what are just the job. Because they are, they have to get done. Which I mean there's lots of product jobs that are part, part of the job is like, oh, somebody has to do that.

Speaker B: Product managers.

Speaker A: Right. But I mean to me, um, I know we talked about this before, but it's often this conversation of product owner versus product manager. Right? Yes. And that product owner is a role within product manager. Right. You, you could say there are elements of generative, generative AI that you could say, hey, could you take that role? Yeah, right on sort of. That. I'm not saying all of it. I'm not. Don't. All the product owners out there, don't lose your minds. I'm not saying that. But I'm just saying there are pieces of that that are much more task based. Like, uh, take this thing, do this thing and either machine learning or some form of AI can actually do some of that to free you up for the people side of it, the creativity side of it, the, the build side of it, the real dreaming, building, creating side.

Speaker B: I think some of the, I think one of the problems is people have really latched onto this use case of like gen AI is creative and it's gonna, it's gonna do all the art and imagination. And so people are like, oh my God, what's left? Just the automation or just like just the manual shitty tasks? It' the wrong way to be looking at it inside your business. Like how do we, how do we give machines and more of the stuff that humans don't love?

Speaker A: Right.

Speaker B: And I, you know, there's a, um, I've been talking about values, like my top values and like how do I express these things at work and how do I bring them to work? I don't know if you know this Leah, but I value having fun at work. What, what should be fun? Right. We should be able to enjoy ourselves. Why would I give the bits that bring me joy and bring others. Jo. Right To a machine?

Speaker A: Yeah. Yeah. I mean it's not that different than how I Always felt about people that were like, we're gonna hire a chief strategy officer. And I'm like, no, thank you. That's the part I like. Right. Don't take my stuff. Right. It's this. It's similar to saying like, let me take away the thing that is what you love and hand it to someone else. And it's like, I don't want you to do that.

Speaker B: Right.

Speaker A: I don't want.

Speaker B: It's not human. Like.

Speaker A: Right. I'm like, exactly. So now you're gonna throw in the whole. That part of it. Well, that makes me feel special. Right. Like, no, thanks.

Speaker B: Of course. Yeah.

Speaker A: I'll just be over here doing data entry apparently.

Speaker B: Right.

Speaker A: With my two fingers. I'm going to go back to that kind of typing.

Speaker B: Yeah.

Speaker A: But I, you know, we talked before and I'll. I mean I can be pretty open about this, but you know, when I, I worked at a travel startup and when I first joined and even still it's a really big sales organization and one of the things that when I first joined that they were doing was it was taking them a long time to build trips. These are bespoke tours. Right. And so they would go and gather all the information, sometimes from spreadsheets and sometimes from this and sometimes and build a trip. And I started saying like, let me do that part and you sell. And all of a sudden they were like, hm, interesting. Say more about that. Right. And I would say like, I'll do the technical lift and I'll hand you something that you can adapt. You can change it. You can change the pieces out. If something doesn't quite fit or doesn't make the customer happy, that's fine. But you do what you do best, which is sell and talk about destinations.

Speaker B: Yeah.

Speaker A: Right. Do the thing you love. Talk about going to Tanzania. That's what they love doing. Don't spend all the time piecing together a trip. I'll do that. Right. And in my mind I think generative AI is the same and we were using some components of that and moving in that direction. And same for me, like do the thing that brings you joy. Let the, let the machine do the thing that is like, here I hand you do something.

Speaker B: Yeah. I think that uh, I think that we've that. That sales side and I will say that customer service or contact center side is where I've seen some of the most interesting applications. When people look at it as um, like what you just did, hyper augmenting the person. So you've now taken a, ah, sales team Or a customer service team that, where you can't possibly scale because humans are part of the uh, engagement for the customer. Um, and you've basically turned them into the $6 million man. Like Bionic, like Steve Austin. Right. And you've, you've given them the ability to do far more with, without working two more hours or you know, without, without doing all of this grunt work. You've like magically put some tools at their fin. Fingertips that allow them to just do the conversational bit or like the part that, the part that's meaningful.

Speaker A: Totally. So it's interesting you said that. I just, as you were saying that I'm like, you know what that's, that is, that feels familiar. So I was my very last, the very last class in a, uh, university to have to do accounting on paper.

Speaker B: Oh, interesting.

Speaker A: Right. We had to do like tax returns and general ledger accounts and all on paper. We had to learn it that way. We. I took 1 Lotus 1 2, 3 class in my senior year. That is how old I am. You're welcome people. Um, but what I always would think about. So then, I mean, of course as soon as I was in the job market, I adopted all of the tools. I was excited because I love tech. Right. So I was like, I'll do this and I'll use this and I'll bring me the QuickBooks. Like I don't care. But I always knew that I understood how it worked.

Speaker B: Yeah.

Speaker A: And so I was, I, if, if the world, if the apocalypse happens, I can do our books. If we need to. If we begin a barter system, I will create to account two, you know, cited journal entries for the barter system. Right. Or whatever. Because I know how, I know the principle underneath it.

Speaker B: Yep.

Speaker A: I think this is somewhat similar. Like I think product managers, there are parts of the job that eventually like let's let the AI uh do it. But you need to understand why it's done and how it's done.

Speaker B: Yep.

Speaker A: And then let it do the job. Right.

Speaker B: Yeah. Otherwise it's just a mystery box. And if it goes awry, because that's just. I don't know if you know this, but tech doesn't always work. Um, so if it goes awry, you need to know that it's gone awry and you need to know how to get it back on like it is again. It is, it is hyper augmenting a person, not replacing a person. By the way, when you do the two, like when you do the two sided journal entry after the apocalypse, I'm going To come to you to figure out, like, what's the ratio of olives to bread and those sorts of things.

Speaker A: I will, I'll help. I can help with that also, by

Speaker B: the way, if whoever is in charge of everything is listening to this podcast. Taxes, like tax returns, friends, you know how much I owe. Like, the government knows, the state knows.

Speaker A: Why do I have to do this?

Speaker B: Like, why are you making me do this and then penalizing me when I'm wrong? Just tell me. I'll give you money.

Speaker A: They're like, you're wrong. Here's your penalty.

Speaker B: Exactly right.

Speaker A: I'm willing to pay. Just tell me what I know.

Speaker B: Just do it for me. You already know. Stop it.

Speaker A: No, it's so true. It's so fascinating. Yeah. So I do think there's. I think there's a whole element of that that I really want people to like. I mean, as usual, take a breath.

Speaker B: Ah, exactly Right.

Speaker A: Calm down. I used to tell my team all the time, everybody take a breath. And they would sort of laugh and I'd be like, no, no, for real, take one. And I want everybody to calm down and then come in with a little bit of open mindedness.

Speaker B: Yeah.

Speaker A: Assume the worst is about to happen.

Speaker B: Right. I would also say, you know, if I had to sort of give any sage advice. Not that I have sage advice, but if I had to give some. Um, don't wait for like, people seem to be waiting for like someone in tech to do the thing. Oh, AI is coming. The CIO will deal with it. Guys. Um, no, it's your obligation as a human in the workplace.

Speaker A: Yeah.

Speaker B: To figure out a little bit about this so that you can help yourself. Like, it's actually getting to the point where I don't actually think a lot of solutions are going to come out of.

Speaker A: Yeah.

Speaker B: Whatever. Tech or I t. I think, I think people that are doing the task, people that are doing the thing will start to adopt this technology in order to help themselves be better, faster.

Speaker A: Yeah.

Speaker B: So if, even if you're not an engineer, like, you should be like fingers in this stuff, having fun.

Speaker A: Yeah. Ask questions, redo the reading. You know, it reminds me of, you know, for all the years that engineers, you know, a lot of majority of engineers were coming out of, you know, uh, you know, um, CS degrees. Right. They were coming out of computer.

Speaker B: Computer.

Speaker A: And then all of a sudden some little, you know, 16 year old would pop into the team and you'd be like, how do you know how to do this? I remember we were at Amazon, we had a Couple guys on the team who couldn't drink. They were under 21. We were like, wait, how old are you? Oh, yeah, we can't take you to a bar. We have to go to McDonald's or, you know, whatever. It's like, we have to take you to the playroom because you're the child. What are you doing on our team? But I think it's similar. Like those kids were writing code at home because they were playing with something.

Speaker B: Yeah.

Speaker A: Uh, so that when they turned into their careers, they could be like, yeah, I can, I can out code that guy.

Speaker B: Yeah.

Speaker A: Because I've been doing it since I was eight. Right, okay.

Speaker B: Right. They came up through a different way. I think the same. I mean, this is actually probably the most exciting thing about Gen AI for me is now you can help yourself and you do not have to have come through a tech role.

Speaker A: Right. No, totally. And so I think, to your point, the idea that, you know, I've, I've always believed product managers come from everywhere. Right. So the idea that if you're in the business somewhere and in the company somewhere and you are learning these tools and go, you know what I love? I love thinking of these problems or I love this. You're on your way.

Speaker B: Yeah.

Speaker A: Um, it's practical. You've become practical. Right. Because you're using the tools to learn how to something works and then you're applying your spark, your creativity to it and saying, oh, I think I might be ready to be a product manager or I might be able to do this kind of thing now I just need to learn all the other pieces around it.

Speaker B: And then I think that, uh, interestingly enough, people can write their own GPTs relatively easily. And in my head, a well constructed GPT is a product.

Speaker A: Yeah.

Speaker B: Yeah. Um, especially if you're in a company that allows you to publish back to like a library of them. M. You're actually building products. So, so product management becomes a lot more egalitarian. AI becomes a lot more egalitarian. I actually, I actually think that these, these, these steps are game changers. And as long as we sort of go back to the practical aspects of product management, like, what problem are you trying to solve?

Speaker A: Yeah.

Speaker B: Like, why is that important to solve now? And what value does it bring? Like, like 1, 2, 3. Right.

Speaker A: Um, yeah.

Speaker B: And, and things start to become trivially easy. Right.

Speaker A: Yeah. Yeah.

Speaker B: And then we have these little assistants that tell us how to hack our own stuff. So you.

Speaker A: Exactly. Maybe I wouldn't have had to lay in bed and think, I hope Nobody hacks all of the, you know, credit cards stored at Amazon every night. If I had. And we had a whole team of hackers, right, trying to break the system. And I'm like, yeah, reasonably so. We had a whole team of people trying to break the system, making sure we had people pretending to be bad actors so that we could know how. Like, how safe is this?

Speaker B: Yeah.

Speaker A: Right now, like, let's use the bad actors tooling against them. Right? Like, let's. Let's go. I think. I mean, I think, you know, fundamentally what we're, uh, what I boil a lot of what we've sat down to is like, use it to your best benefit to be more efficient. Take the take. You know, let it. Let it give you some information that maybe you don't have. Right. But use it to make you more efficient. Let it. Let it dream with you, but also retain your spark.

Speaker B: Yeah.

Speaker A: You be the creative energy, the, you know, the. The sparky one. Right. Who can come in and be like, I got ideas. Right. Like, yeah, I think don't, like, do the part that you. I will say, like, as a coach, I often find that anyone, not just people that are dealing in kind of this exact space, but anyone who is struggling with, what do I want to do next? Or is this going to. Am I getting outpaced? They have forgotten how to tell their own story. Yeah, they don't know how to tell their own story. So they've lost that. They don't know the value. And what's, uh, uh, crazy to me is as soon as they start talking about it with me, I'm like, I can tell you what the value's been. Right. Like, it's that I can see it. They don't know what their personal values are.

Speaker B: Yeah.

Speaker A: Right. And they don't know how to put that all together to take on the next thing. And sometimes say, what do I need to go learn? And I think that's exactly what we're saying here. Like, what are you. What. What do you love? What have you done that you're proud of, that you're good at? What do you value and what do you want? And then go learn whatever piece of this that you don't know so that you can be prepared. Because if you say, oh, uh, I don't know anything about that. I've never done it, you will get blown past.

Speaker B: Yeah.

Speaker A: That. That day is coming. Right. If it's not already here. Right. Like where. If you. If they say, what do you know about AI? And you say, nothing. Okay, well, good Luck, Right.

Speaker B: I saw that on the COVID of a magazine once.

Speaker A: Right. So, like, figure out what you don't know. Like, that's. That's educating yourself, right?

Speaker B: Yeah. I love that you approach that that way. And I think it really is so a. What I heard is, no, you don't need to be afraid.

Speaker A: Right?

Speaker B: Um, now, that doesn't mean you don't need to be afraid of bad actors who are also, like, leaning in with AI and we'll talk about that in another episode. I think that I, um, think that. I think there's some really cool product, um, products that are leveraging AI But I also think there's a lot of, like, inflation in the news. So, you know this. These companies laid off a zillion people because they implemented A.I. well, like, let's be a little skeptical about that.

Speaker A: I'm pretty sure Chatbot is not a human. Just for the record, the other day, a chatbot called me by the wrong name, like, four times. And I was like, for real? You don't even know my name? I've logged in, right?

Speaker B: Yep. So my favorite. My favorite. And this was years ago, so it's totally out of date. I'm going to be one of those people that report, like, repeats an old story. But my favorite, um, my favorite really good product feature. Uh, that was a. That was a chatbot.

Speaker A: It was A.I. right.

Speaker B: Um, was on a. On an IVR system. And I can't remember the airline. I think it was British Airways. But I was. I was in, like, phone trees are my personal pet peeve. I just, like, whoever invented a phone tree should be flogged. And anybody that designs them, like, if it's more than one or two options,

Speaker A: like, leave me alone.

Speaker B: Right?

Speaker A: And especially if it's like, you can say or type what? And you say seven and it says, I didn't catch that. Seven. Me. M yelling at me, yelling at all the AI in my house. Right?

Speaker B: I was stressed. Oh, my God. Then we'll talk about voice recognition of females in a little bit, too, because that's another subject, which is a great job topic.

Speaker A: Right?

Speaker B: Bias. Bias and tech. What? I was. I was traveling. I was stuck somewhere. I was lost in a phone tree, and I was pissed. Like, I think over my body clock was on 2am I'm exhausted. I'm trying to get home. And, um, I just remember being like, holy, like, sorry, leave that part out. Um, but I think I shouted at the phone, like, several bad words in a row, and it just kind of paused. And then it went, sorry, you're having trouble. Let's get you to a person right now. I was like, that is.

Speaker A: If I had known that, I would have sworn sooner. Right?

Speaker B: That took like a really horrible, like that took a really horrible moment in my life. Some M. Product manager thought of that and I was like, genius. Like turn my whole mood around.

Speaker A: I mean if you're going to listen, it better listen. It should listen and, and try to step in. Right? Like, yeah, no, totally.

Speaker B: I think that is someone walking on the unhappy path.

Speaker A: That's amazing. I love that. It's like it probably was British Airways. They're like, do you need some, do you need something? You're like, I'm swearing at you. And they're like, oh, let's step in.

Speaker B: I wish I could remember. So like, if anybody remembers or knows or worked at this airline and remembers the use case, like, you made my freaking day.

Speaker A: Yeah, it was amazing. Feel free to let us know. We will be happy to talk to you about why you did that. That like, let us know. I think also like what. So we are going to have several conversations here because I think there is a whole thing around ethics. I think there's a, there's, you know, like the gender side, the race side, like how, you know, where, where, where do the bad actors play? Where, you know, what, who defines what good is? Like all of those things. I think there's a whole lot of conversation to be had there and um, maybe we'll find some other folks who want to join us in that conversation.

Speaker B: I would love that.

Speaker A: I would love that. Um, but I would also really like for, for people to tell us like what's your, what are you afraid of? What's your experience been? Um, and how are you, how are you handling that? How are you managing it? Like, and what else, what else are you afraid of? Because we can also, we can have a part two. If someone says we're afraid of these three things and you didn't talk about them. Okay, let's talk about it. Right?

Speaker B: Yeah. I also want to hear like, you know, how are you using it? Lee and I both gave some examples of how we're using this in our day to day lives to hyper augment ourselves. Yeah, um, I think there's a lot of opportunity that I have not even scratched. Yeah, I um, think, you know, I think there's another probably conversation, Leah, about how do we build teams, not just that work for us but in the larger organization that, that um, want to be able to adopt. How do we enable others to adopt these tools and, uh, and. And change their own jobs. Um, so what are you doing? What are you doing with AI? How are you making your life better?

Speaker A: Yeah, for sure. And if you. Like I said, if you have any comments on any of that, we would love to hear from you. Um, if you want to come talk to us, let us know what your position is and your angle, and we're. We'll discuss it. So be fun. This is.

Speaker B: I think this is.

Speaker A: Like I said, we'll go back and forth among other topics, but. But I think this one's really big. There's a lot to kind of unpack here.

Speaker B: Yep.

Speaker A: Awesome. Thanks, Marilyn.

Speaker B: Thanks, Leah. This has been awesome.

Speaker A: Sam.