The Identity Crisis of AI and Who Are We When Work Changes w/ Karen Lam

Full Episode Transcript

This is the full recorded conversation from The Human Protocol Podcast, published by The Human Protocol Group. © 2026 The Human Protocol Group. Please link to and attribute the original episode when referencing this conversation.

speaker-0 (00:00.11)
A lot of the noise around AI, at least the ones that hit the headlines and the ones that become viral, are very negative.

speaker-1 (00:07.092)
AI is not just changing what you do, it is changing in some cases what you're worth. If your identity is tied to your work, what happens when the work disappears?

speaker-0 (00:18.774)
A lot of what AI is really making the biggest impact on is essentially the administrative labor.

speaker-1 (00:25.088)
It's just crazy to think that gender and age and whatever, it has an impact on how people perceive you or someone's use of AI.

speaker-0 (00:36.642)
Build that future. Build a direction of how we use the tools best and what we should be using the tools for.

speaker-1 (00:42.626)
or

speaker-1 (00:47.264)
AI is not just changing what you do. It is changing, in some cases, what you're worth. If your identity is tied to your work, what happens when the work disappears? Welcome to The Human Protocol, the podcast about staying human while building the future. I am your host, Michael Salomon. Today's conversation is not about AI tools in a way, it's not about technology. For the most part, it is about something deeper.

It is about what happens when AI is really disrupting, not the work, but our identity. Who gets to feel competent, who gets to feel relevant and who gets to feel safe using what's coming next. And here's what happens next, right? Two people may have access, can have access to the same AI tools and they may walk away with completely different outcomes. Not because of the skill, but because of perception.

power and permission. With us today, I'm very excited to welcome a friend, a dear friend of us, which is Karen. Karen, Karen Lam, welcome to The Human Protocol.

speaker-0 (01:54.786)
Thank you, Michael. So glad to have this conversation today.

speaker-1 (01:59.062)
Yes. Yes. Thanks for taking the time and sticking with us. I know we have had some challenges to make this happen, but I'm happy that we finally were able to get it done. All right, Karen, I'm very excited about having this conversation with you. We briefly talk about these topics that we're going to be covering today. I know that's something that you're very passionate about as I am, but before we get into the business of the day.

I would like you to tell us a little bit who Karen is, where you have been, and what are the things that are at the top of your mind lately.

speaker-0 (02:34.038)
Yeah, for sure. So, Karen, I'm the director of customer support at Top Hat, where we spark better teaching and learning across the world. But ultimately the part that I'm really, really passionate about is really getting involved with AI. So today I'm like, I love the conversation, the direction that we're looking into.

Also at Top Hat, I'm the chair, the co-chair for Women in Tech employee resource group. So the entire conversation just around identity is really super meaningful to me. So we got really excited for our conversation today.

speaker-1 (03:08.918)
Awesome. Thank you for that. I appreciate you going over all that with you. And yes, as we mentioned, AI is not only changing work, but it's also changing our identity. And when we discuss that, when we talk about one of the questions that we had is when we talk about identity crisis, right? Especially in times of AI, what it's actually breaking inside of people.

What is it this identity crisis that we want people to think about?

speaker-0 (03:41.486)
Ooh. So, you know, because I've had a lot of time to think about this question, because Michael, when we first started having the conversation, is like, identity is such an important part of just figuring out who we are. But also what occurred to me very recently is that the whole concept of AI in itself is a lot like the Promethean myth, right? So Prometheus, you know, stole fire from the gods and brought it, brought it to humans. You know, that

In itself is a story about our personal human curiosity, what we gained once we achieved, had fire available to us. But then AI is very similar in that way. And what makes it so interesting and so topical and difficult for individuals to really grasp is that technology now, it's almost like these companies have taken the fire from the gods, but that fire was from us, right? That meaning, that moment is from us.

And so that's where the identity crisis comes out, right? That application of effort, that application of being able to think critically, even though very human emotions, very individualistic, it's also something that we feel like was taken away. And I know I can't speak for everybody, but I do get that. That's where that sense of anxiety is coming from.

speaker-1 (05:04.084)
And when you say it's been taken away, it's because we think AI, it's kind of removing a lot of what we humans historically, we went through to find meaning and purpose and find who we are. Like for example, the work we have been used to and finding meaning and purpose and those tasks that are being taken away sometimes by AI. Is that what can create this type of identity crisis from your point of view?

speaker-0 (05:31.67)
Yeah, for sure. I mean, we tend to equate effort to the work that we do, the effort that we put in and not really to the outcomes that we achieve. And that's where AI makes that shift. I mean, I remember earlier, a while ago, Mike, when we first had a conversation, I was talking about how, you know, my, my parents were, you know, immigrants and they moved to Canada and the whole mindset of instilling the values of, you know, hard work gets you where you are today. And that's really the same thing with AI.

you know, suddenly coming into the picture, all of that mindset shift, all of those lessons our parents might've taught us, our parents' parents might've taught us that passed down from generations to generations, all of a sudden the narrative has entirely changed. And then what are we? What does that look like? That's the conversation, right?

speaker-1 (06:20.562)
Exactly. What are we? Right? What is it that we are when things that we have been used to sometimes for decades suddenly disappear? What is life when you don't recognize your day to day, your daily tasks, your routine? Right? It's like right now when you're talking, I've been thinking inside your words and it's like a relationship.

Right? When you are, when you have a relationship that is a long relationship and you spend decades with someone and out of the sudden that disappear for whatever reason, it's hard question what is live right now without that person, because that's what life has been for you. And you saying those words right now about your parents made me think about really our lives is changing.

speaker-0 (07:07.382)
Yeah, completely. Definitely shifting the way that we have to think about the work that we do all of a sudden, especially depending on how much you've incorporated efficiencies into your workflow. But to be fair, this isn't really just a shift in AI. When we think about any implementation of technology, whether it was, you know, the internet, whether it was the implementation of time zones, even the fact that we've introduced something new means that we have to shift the way we operate. And I think very disorienting.

Especially when we think of internet and AI, these are now becoming more readily available globally, more accessible to individuals. And that also means democratizing access. And I think one of the things that we really wanted to talk about today was also like why there might be differences in, you know, the types of things that individuals use AI to assist with, but also on the other hand, why some might just, you know, decide, Hey, this isn't for me for whatever that reason might be.

speaker-1 (08:05.196)
Yep, absolutely. And yes, that's part of the topics that we're definitely going to be covering today. And, and one thing about identity that I would like to ask you about Karen, why do you think this AI has hit people identity harder than other technologies changes that we have been through in the past? What's different from your point of view about AI from other technology?

speaker-0 (08:32.853)
Yeah, that's a great question. I think to a certain extent, it's also how the information has been portrayed in media. So definitely, I mean, I can't speak for the entire historical context of the world. I haven't been around the earth this long, despite the gray hair. But having said that though, I'd say right now, especially now, was in the last two, two to three years, a lot of the noise around AI, at least the ones that hit the headlines and the ones that become viral.

are very negative in nature. The conversation truly is being controlled in this umbrella. Our society is really just focusing primarily on the negative pieces of AI. That's what makes the headlines. That's what starts many of the conversation. And I think because of that, that's where our shift, our anxiety and our fears start, you know, coming to the surface. If we start thinking of that, like within that context of the negative headlines and stuff, just imagine if we were in a world.

where we started having more positive headlines about, you know, AI, you know, if AI not saying that it can, but if they had the ability to cure cancer, if it was able to, you know, figure out what, like how to handle world hunger and issues with our oil crisis and such. We wouldn't be having the same types of conversations we are having today. In a way, it's kind of interesting, you know, that we can certainly look at it from a very critical lens, but there's also

Yeah, in my mind, because of the very negative focus we have, that's why the conversations that we're having today and also what others are focused on is really what is making that shift, that anxiety, that fear that's coming to place.

speaker-1 (10:16.076)
You know, in a way people monetize people profit from bad news, from fear mongering, right? So it's that's back to your point. Yes. The majority of what we hear today, it's about end of the world type of predictions instead of focusing on what I call AI for good, which is those applications of AI that are not being discussed a lot lately.

which is, you know, trying to researchers and scientists trying to find a cure for cancer and using AI for that, for example. And, and that's what people put the focus on. Right. With that being said, I think this conversation today also speaks to a very important topics and, questions about who we are as humans. And especially in times that we have been so reliant on

on the internet, on social media, and on tasks to identify who we are. And we have generational changes and differences. And I think for some generations, maybe harder to adjust than others. Because when your work is daily task and the tasks disappear, you start questioning, am I being efficient?

speaker-0 (11:36.79)
Yes. Or am I being valuable? Yeah. Yeah. And that's actually interesting, right? Because when we think about skills, and again, when we talk about media, the studies that have been done have been primarily focused around first things I have been reading, to be fair, it's not the entire universe. But for articles that I've been looking at that I find super fascinating and interesting is how there's

speaker-1 (11:39.278)
And my

speaker-0 (12:00.162)
definitely a gender disparity between the individuals who use AI for their work. And a great example is with engineering. So female engineers tend to use AI significantly less than the average and the average being, you know, their male counterparts or anyone who identifies as male. Where that becomes super interesting is if we start looking deeper, a lot of that is that there's a bit of a, what's the best word for it? Sort of like a penalty, a penalty that's applied for the use of AI. mean, we even see it a lot.

Even unrelated to engineering, but like on LinkedIn, for example, or anyone who likes to post publicly about their content, often there are comments or commentary about whether AI was used to help assist, not necessarily write the entire content, but assist in the writing. And people get very, very upset if there isn't notation of AI being used.

speaker-1 (12:52.856)
From your point of view, do you see value on this claiming for people if we have used AI or not?

speaker-0 (13:00.994)
Yeah. So I think it really depends on the context. So the reason I say that is if you're posting publicly, it becomes very useful to have a notation, whether AI was used to generate the content or not. If we have thoughts and strong feelings about intellectual property. So if these thoughts belong to you and you alone, then if you write them and, you know, post them or write them in a notebook or such.

It is considered your work. is copyrighted, but if AI is helping to assist that, I don't know that that's a tricky one because AI is trained and on a variety of different texts. don't really know who the source of that information, where that comes from. If we're talking about the work that we do within a company and showing if AI was used for the work or not, I actually would hesitate against having that, you know, surfaced. And the reason for that is.

I think that adds to the conversation we're talking about, about the penalty that happens where women, for example, are disproportionately hesitant to use AI for a variety of reasons. Some of that could be because of their perception of AI, maybe in some cases not being accurate. So they prefer not to use it within their workflow, but also the sense of their ability to do the work that's in front of them.

And if we take the concept or the role of an engineer, it's a very highly technical role, a role that primarily and historically has been very male dominated. So for a woman to use AI and to have it noted in their work makes it incredibly, well, very transparent, makes it incredibly difficult because otherwise when a male counterpart uses AI and it is noted, the impressions or the

feedback that they may receive depending on who is reviewing the work could be very different. I don't remember the exact study where this came from, but this was actually something that was looked at. And I found it super fascinating that automatically because of the way we think within narratives, because of the way we've been socialized automatically based off of not only gender, but also age, age as well. It has a significant impact or can have a significant impact on how perceptions of AI use within the workforce.

speaker-0 (15:21.377)
is impacted.

speaker-1 (15:22.964)
It's just crazy to think that gender and age and whatever, it has an impact on how people perceive you, right? Or someone's use of AI. mean, credibility shouldn't be attached to anyone's gender or someone else with, you know, of older age or whatever, just because they are saying that they're using AI as part of their work. We know everybody should be using AI. We all, for the most part.

are using AI to help us with our daily task. But yeah, when you mentioned to me that study, was like, wow, how is that even possible in 2026? mean, why? What is it behind that? That anyone could think that a woman's worth is less than a man's, than a counterpart using AI as same as she is. That doesn't make a lot of sense to me.

speaker-0 (16:18.358)
No, it definitely doesn't make any sense whatsoever. And yet that is what we are seeing. Also, I mean, to take it a step further, we think of outside of work or even the fact that conversations that we might see in the universe now. can't say for certain because I know LinkedIn has their own algorithm and such, but I will say that the majority of what I see on my LinkedIn feed doesn't necessarily happen to be conversations about AI coming from women. I've mostly been seeing a lot of

Men in my feet talking about how they're using AI, talking about how that work is coming through. But it would be much more democratizing the field. More women were posting about it. I'm sure there are women posting about it. And I do see some show up in my thread, but I would say it's at least based off of what I'm seeing, not as frequent. And that could be true for some and it could be untrue for others depending on your network and how that looks like. But that also means.

to a certain extent, or at least how I'm interpreting it is that woman because, and I can also speak for myself as well, like that level of comfort. Like I don't necessarily feel comfortable posting about a learning until I have satisfaction that I've understood every single piece of it. So that's something that's personal to me. It just happens to be, also identify as a woman, but as a male counterpart, perhaps the posting is more frequent and the sharings and learnings are more frequent simply because

There's a combination of increased risk tolerance. So, you know, don't feel like there's any perception gap or anything that's applied to that particular gender. But I would also say there's that invisible labor and work as well. I would love to spend hours and hours tinkering around in, in, know, different AI tools and such. And I do like on my own time, late into the evening, but I also have a child to take care of. So there's also like that invisible labor that's attached to it as well where.

Again, because of the way our society is structured. And of course it's different for every family, but I would say that there's proportionate or at least more time that can be applied to tinker around with tools to actually work through a lot of the use cases. If you don't have other, you know, invisible labor or work that's applied to, you know, your normal day to day.

speaker-1 (18:30.262)
Yeah, it's so many different and important topics, especially this last one, the invisible labor, of course, the time that you dedicate to any specific task will be, it will be dependent on your available time to, you know, to dedicate to that. But we are not here telling these stories or talking about this, saying that this is the way things are. This is what we are seeing. This is what you're seeing. This is what...

The algorithms, especially from LinkedIn, allow us to see, right? And we see a disproportion. Yes, we see that. I see that too. But I also cannot make a judgment or can say for certain that this is because one specific reason. And you touch on many different ones. One, it may be the algorithms. It may be that the content, it's the majority of the content about AI is being posted by men. It may be that many of this content really doesn't go through very vigorous

research and making sure that this is accurate, right? Many of these men don't have the invincible labor, right? As we were discussing right now, they may have more time, but I'm also seeing that the majority of them, at least from what I can see from the limited time that I spend on LinkedIn, it's also coming from men. And I would like to see that more women speak up as well to see that kind of getting to a level, you know, between

between both that we can say we have from both voices, because those are extremely important.

speaker-0 (20:04.962)
Yeah. Especially senior women as well. Cause I would definitely say if you're in a position of leadership and authority, that also has an impact on what your individual contributors and what other individuals in your organization who can look to you to see if you're using AI and if you're having success with it, or you're very vulnerable and are publicly sharing any of your failures that actually also helps, you know, shift that focus, identity being our core theme today.

to really say, hey, you know, maybe it's not so bad. Maybe, maybe I should try it out.

speaker-1 (20:39.886)
Yeah, absolutely. Totally agree with you on that. And Karen, people trust you, trust me, trust us based on what we contribute, right? Based on what you put out there, based on what you work on, what your experience tells people about you in your workplace is a similar story. It's your contributions.

Tell the story about who Karen is, who Michael is, who we are, right? Based on projects and things that we deliver. So as we are having this conversation today, it makes me think about what will happen about regarding people trusting us when contribution really becomes unclear. Right? We are talking about

AI eventually taking away some of the things that historically we have contributed to. And because of those contributions, people gain experience, people get trusted. Have you thought about it in this particular way?

speaker-0 (21:59.82)
Yeah, no, that's a good question. think even with the concept of, because we had just talked about invisible labor, I think that's one thing to really think about and dig into. And the reason I say that is because a lot of what AI is current state really making the biggest impact on is essentially the administrative labor. Labor that, you know, historically has been very female-centric and that's work that, you know, whether it's

Organizing, know, like an event, booking some, so booking something in your calendar, making a laundry list or a grocery list or what have you. Those individual tasks are definitely things that AI is wonderful in, but that also means that when you think about, you know, our personal identity, right? You know, how trustworthy is Michael, how trustworthy is Karen and such. This is where if we are using AI and yes, if it is shaving off some of that administrative labor that's there.

It also means that we can, like many have said, you know, build up and, and, and have more room for that strategic conversation, strategic thinking, things that we don't necessarily, even at this point in time, probably not the best choice, but regardless, we can then offload the administrative labor to AI and then focus on the things that matter to us. And maybe that is how we build meeting. Maybe that is how we continue to further ourselves and build, you know, further trust, further.

further options that others can see and others can, you know, understand and we can have conversations about, because ultimately, if we continue to just really focus on AI good, AI bad, AI can do this, AI shouldn't do this, which I think is still important, but for the most part, we're thinking of it from an identity perspective. This is where it gets exciting because we can just figure out what new meaning we can derive from the new work we can be doing today instead of being bogged down in all the other stuff that

Maybe, maybe it did give you joy, but that joy can now be moved over to something else that can give you even more and return more back to you.

speaker-1 (24:07.97)
Yeah, totally agree on that. And, and I'm hoping also that it help us kind of, you know, decrease the gap and the perception gaps between what men and women can do, right? Based on the task that they have been used to do in the past or not. Cause you know, hopefully we get to a point that AI can help us, you know, all of us to do many other different jobs.

Yeah, for sure. And to help us with the skills that we may not have and even with jobs that historically were men or women in a way, but helping both to really do everything and not feel that gap between genders and as we have seen in the past, as you were saying.

speaker-0 (24:58.314)
Yeah, for sure. And also just the whole fact of like diversity of thought, right? So the more both genders use AI, the better we can then, you know, build that future, build a direction of how we use the tools best and what we should be using the tools for. When we also think of democratizing access, making things easier, figuring out how we can go further with the use of AI. I was talking to Sarah Kim and NeNe lately, very recently. So another one of our...

support community. But one of the things she had mentioned, which I thought was really fun was she's been using AI to essentially put together a lot of her talk, like speaking opportunities, her proposals that previously it wasn't uncommon for those to be, you know, rejected for whatever reason. But now with the help of AI, they're a lot more polished. They're, you know, in a state where she's actually getting much more, like a higher acceptance rate for speaking opportunities. And that's a wonderful usage of democratizing access.

When I think of the education space, international students who might be using AI for their college applications, having the ability to do that and to get into a school, you have the grades for it, but maybe previously the college essay wasn't really up to snuff. Now you have the ability to do that. And so I think there's wonderful use cases where many of us can figure it out.

And when it comes to identity piece, again, just trying to bring it full circle, it's really then again, just adjusting that mindset, which funny enough, I would say that for those who have been taught, you know, generations over generation about, you know, hard work and focus on hard work. And now we have to start shifting our mindset to outcomes. would say the younger generation, what's really interesting there is that I feel like.

Again, this is more an opinion. wouldn't say it's fact. I haven't found any research on it specifically, but I would say that the younger generation is more like, I'll use AI, but I just won't tell anybody I'm using it. and maybe, you know, depending on the setting, sometimes whether it's academic integrity or otherwise, like that would make sense. But in general, it's not necessarily a very open conversation about it. Why? Hard to say. Some of it could just be because of,

speaker-0 (27:19.726)
who they're watching and they're not as open about the usage of AI. think like in general, if we were theoretically, if we were all very open about usage, if we were all talking and having conversations about what we are doing and not doing with AI, which I know the support community has been very open about that. And I'm sure other industries perhaps as much, but yeah, we just need that level of openness and care in order to really drive forward what that future is going to look like.

speaker-1 (27:48.14)
Yeah, I agree. I think we should remove any perception issue that may exist when people, you know, actually accept that they're using or this claim that they put a disclaimer that they're using AI. It should not be seen as anything negative. I know where you're coming from, where I'm coming from. We have the same vision that this technology and this tool should augment our capabilities. And if we are using the way we should be using...

It should be our co-pilot, right? It should add additional power and capacity to the outputs that we are able to produce, right? With our limited time. I really don't think why people may feel one way or the other, but it's, it's going to depend on, on what people are doing, what are the type of culture that they are part of, right? And generations to generations may differ as well.

But since you're just talking about this, makes me think about when talking about the adoption issue, right? At the workplace. And I know you have seen, I have talked to many people and it's also different flavors that I'm getting. There are some organizations that they are more open to others about the adoption, but just curious, how do you see this adoption issue at the workplace? The acceptance of it.

speaker-0 (29:12.854)
Okay. I mean, like, again, like you had mentioned, it does vary organization to organization. And I think where, especially when we talk about headlines again, especially when we think about the headlines that have come out and how it's very negative in terms of the impact, there's obviously an element or a very strong change management that needs to happen if you are implementing AI in the organization, simply because of, again, all the negative press that's out there about, you know, job loss and certain jobs disproportionately being impacted by AI versus others.

But truly when we think about adoption, it's not enough to say, Hey, you know, opened up, you know, chat GPT or I've opened up, know, essentially like your LLM chat interface of choice and, type in, please reword this sentence for me. I want to make sure it looks good for whomever it is I'm sending it over to. It has to be more than that. Right. And the reason I say how that definition of adoption to simply opening up that interface and using it is not enough.

It's not take us further and doesn't really indicate what AI can be most valuable for. That's really just scratching the surface or using it like a glorified search engine. Where we can really take it further and where adoption really needs to be focused on is what can we do to implement or integrate AI into our workflow? And I think that's truly what organizations need to focus on. And of course, every organization has differences in

the way they choose to monitor because truly it is monitoring or, to, you know, implement push out, roll out any sort of AI strategy that is there. The other piece as well, like it is a cultural or it needs to be a cultural initiative. It's not enough to say, Hey everybody, we now have, you know, this software now available in our workspace, go and use it. While, you know, it's great that it's available again, depending on how often.

the individuals in the workplace have used AI in their own personal life would also depend on how well they are also leveraging it within their day to day as well. So very much, you know, if AI is going into an organization, we certainly need to focus on not only change management, like what tips, like how to teach and enable those to use it effectively because we come, you know, from the, department of support.

speaker-0 (31:39.006)
And because a lot of customer facing interactions, the entire customer experience world has been highly impacted by AI, both in the job space, but just in general, just the fact that there's so many ideas that are coming out there. feel like outside of product development or engineering teams, these are probably the two biggest departments, maybe a bit of finance as well, like the third department. wait, wait, nope. There's marketing too. So.

Of the four that I'm talking about right now, I think those are the biggest ones that definitely are being impacted by AI. And when I say impacted, I don't necessarily mean in a negative way. It's just, there's a lot of movement, a lot of opportunities that can come out of, out of that space. But ultimately we can look at something in either a positive or negative way. Ultimately it's again, based off of how you identify yourself, how you choose to look at the world is how you're going to make it out the other side. I say there's any right or wrong.

But I prefer the more optimistic route because it's something I feel easier to live with.

speaker-1 (32:40.918)
And when you focus on the negative, we're never going to get a positive outcome. So why spending time and energy just focusing on things that may go wrong when you don't know if that's going to get you to a better place. I'm totally on board with you, but that's also part of what cultures are for, right? That's the type of culture that you build. And a long time ago, someone told me that culture is really, is what people hide, not what they say.

And it makes me think for the conversation that we're having today, how do you think we can build a culture where people really don't have to hide, especially in times of AI usage and adoption? I'm curious to hear from you. What are your thoughts on that?

speaker-0 (33:29.792)
Yeah, I would say definitely the one piece I always bring forward a lot is experimentation. It's very important for not only individual contributors, but especially leaders to make sure that they're again, like open and vulnerable about what they're doing and using AI for. I would say on an ongoing basis, when I meet with my team, I mention about something I had an idea about and what I tried out, what I used to prompt, you know, in our workspace, like.

what that looks like and then how it didn't work. then having those conversations is helpful, not only because it shows, you know, a leader doesn't necessarily get it right every single time, but it's also important too, because, you know, there could be a new idea. Maybe somebody else could see, Hey, have you tried this or have you, have you tried something else? So it's really having that active conversation, making experimentation a part of the workflow that it's normal and natural in discussions.

I think definitely, especially with teams that are busy, could be challenging less so about, you know, the fact it's like a leader could be very open to the idea of experimentation, but because of capacity, there just isn't the opportunity to do it. But I would argue at that stage, maybe the options are. Implement something that you don't necessarily have to build because there are plenty of tools out there who can also in some cases do the same job that you actually wanted to build out.

Let that do its work for now. So you can then focus on other things to help enable your team or to, you know, help bring in the diversity of thought, because ultimately the individuals who can solve the best problems are the ones that are closest to the work. They might not always have the tools to do like to solve those problems, but they know what those problems are. They know it from every single angle possible. And it's especially as a leader, it's your job to come in there and to figure out how to unblock them.

And if that means, you know, bringing in an engineer from, you know, the team, or if it means, you know, advocating for budget to just get something pre-built, could be anything else. Like that is on, on you as a leader to figure that out. But ultimately if we're open about the conversations that we're having, if you make that safe space for everybody to be in, then I think the, the identity crisis to a certain extent will still.

speaker-0 (35:51.49)
be there because the mind shift itself is staggering, right? It's huge, but at least we'll get closer for it to feel like it's improving.

speaker-1 (36:04.012)
Yeah. We are human beings. know that we, as a creature, as a human being species, we are reluctant to adapt to changes, right? It takes time. But first is baby steps, like in everything. And especially in times of AI, and we're talking about AI identity and culture, how you change cultures is really by allowing people to not be afraid of trying, right? Of experimentation. You know, the other day I was at a conference.

someone was giving a speech about innovation, but he was talking about innovation in a way that I never thought about. When we think about innovation, usually we think innovation is really the fanciest and, know, shiny thing. Something brand new and something that no one thought about it. But what the speaker was saying is innovation is actually boring. It's actually a lot of boring work.

speaker-0 (36:48.814)
something brand new.

speaker-1 (37:01.484)
you know, working behind the scenes, making things work in a better way. And it makes me think that sometimes we just try to focus on really trying to accomplish the thing that is going to be in the headlines or in the news when really innovation and experimentation is what really improve things, improve products, improve processes. And it's baby steps, things behind the scenes that no one knows that is happening. And eventually,

our customers and people, you know, appreciating the service or enjoying the service or product that we are offering are experiencing those changes. And that's how you build a better culture as well. It's giving people a safe space to try and not being afraid of trying new things. And I love that part of experimentation and it reminds me of that speaker talking about innovation, which I found it fascinating.

from that angle. Yeah.

speaker-0 (38:01.42)
Yeah, for sure. mean, there's a, there's a lot of theories, like even though we think about Toyota, right? The assembly line method or even McDonald's, the whole reason that those particular brands and labels have been so successful over the year is because they became meticulously very hyper-focused on getting it right over and over again in a way that became efficient in a way that it became innovation because it was hyper-focused on a specific process.

speaker-1 (38:31.232)
And that didn't happen overnight, right?

speaker-0 (38:33.656)
Definitely not.

speaker-1 (38:35.634)
decades, sometimes even centuries, improving, trying to make things better. Now, Karen, we have been talking about experimentation, right? What are the things that we should focus to make sure that we can experiment things in a way that is safe? Because depending on what we are trying, there are things that are maybe riskier than others, especially in times of AI.

We have heard the stories about chatbots that are really getting customer out of the door instead of helping.

speaker-0 (39:12.128)
Yep. Yep.

speaker-1 (39:14.764)
Here's your thoughts on that.

speaker-0 (39:16.48)
Yeah, for sure. I mean, every company will definitely have different guardrails that are in place. Ultimately, I would say you have a sandbox environment, you know, something that's low risk. That's the best place to do your testing. The other, the other piece as well is to put all your ideas in one place and then start figuring out which one that you feel is less riskiest to try out. you know, risk of course is, vary based off of the industry that you're in. But in my mind, internal use cases, which I would say

Most people would be aligned with internal use cases tend to be less riskier than external, their customer facing. So if there's a way you can build or iterate on one piece that might be for, you know, internal customers, so employees at your company, then maybe if that's successful at that point, you can turn it to be outwardly facing. But yeah, definitely sandbox environments, any task or elements that, you that you deem as low risk and risk again, would depend on your industry on and your risk tolerance because

Some people like to put it out there and test in production. And I will say that based off of my past experience, when I used to do a lot of website updates, testing and production was great, but it was also very nerve wracking. yeah, definitely, you know, especially if you have a customer facing tool, you probably don't want to do that testing in production. It also means that if you truly are like don't have a sandbox space or don't have any other options, but to put something in production.

Then I would say, if you are, you know, in that space and have to do that, then see if there's something you can do to make the audience size quite a bit smaller. like maybe only if this task or workflow, yeah, exactly. Would only, you know, happen on this type of information. And again, a very small slipper, very small stack.

speaker-1 (41:07.916)
Yeah, those are very valid points because I think sometimes people think AI or hear AI, artificial intelligence. Yeah, that doesn't mean that it's ready for production. All right. The intelligence part of it doesn't mean it's ready. It's a lot of work happening behind the scenes to make it work, to make it safe. And I don't think everybody or every organization is taking the same risk when they're using AI. There are best practices for leveraging AI, for implementing, for deploying AI.

Everything that Karen said right now should be best practice, right? You need to try to test it first before you put it in front of your customer. So those should be, you know, no brainers. Best practices for all of us, not only about AI, but really about any technology that we're planning to deploy in a way. So Karen, everything that we have talked today about inequality makes me think about, okay, I'm not saying that

The world is an equal opportunity place right now. We know we have suffered from inequalities for centuries, right? This is not new. But are we accidentally, you know, creating a new type of inequality when we're talking about leveraging AI for our daily lives or our jobs in our future?

speaker-0 (42:31.852)
Hmm. I guess, Michael, it would really depend again, like many things. It depends on perception and the spin that you put on it. So is the question more that do we risk pigeonholing ourselves if we use AI or is your question different from that?

speaker-1 (42:46.636)
Yeah, from, if we are creating a new type of inequality in how people may perceive us, especially those using versus those not using the type of opportunities that may be available from both groups. Talking about general, right?

speaker-0 (43:05.762)
God. Yeah. I mean, I think like anything, there is an element of potential risks there. we think back to the study I mentioned previously about, you know, the different genders, the, and the usage of AI and engineering, other studies that have been out there as well that take into account managers who use AI and the rating, the performance of their individual contributors as positive or

negative, like the outcomes of what came through. Interestingly enough, for managers who weren't using AI in their day to day, even if the output was exactly the same for, you know, the AI output and the human output, they were more likely to negatively attribute the AI output as, or I guess human assisted AI output to be inefficient or rather not up to performance enough.

Whereas a manager who had or was using AI actively had equal, either equal or sometimes even more positive sentiment about the outcomes that had, you know, been derived from, from the, from the employee. So I think in some environments, there could be the risk again, based off perception of bringing forward your usage of AI, but in environments, especially when senior leadership.

Is not only encouraging the usage, but actually is using it themselves and understand how and what AI can be used for. That's where the conversation becomes much more open. The perception of performance becomes so much more valuable. And I think even the shift in identity becomes so much easier simply because there isn't that penalty for using AI and there isn't necessarily as much.

you know, gender disparity, you know, in, the gap of AI usage. I do want to make sure like, it's not even a matter of like females using AI, males using AI and who uses it more, who uses it less. The whole concept is really that if you're not using AI today, it's not even about falling behind or, you know, you know, the fear of missing out, which you, which you may, of course, but it's not even about that. It's about.

speaker-0 (45:27.628)
We already know historically, like over the last few years, like the data that AI is trained on is incredibly biased. And I know there's work that's being done to try to, you know, reduce a lot of the bias that's inherent in the training models, but the bias is there. And one of the biggest ways to defeat bias is to essentially, you know, add data to it, right? So the idea is if there's, you know, that a very male centric bias that

Again, part of the conversation that's out there, then we need diversity of thought. need females, we need different ages. And even, know, even if you don't subscribe to a gender, we just need more data in these models to train it appropriately. And then at that point, like my personal opinion is I feel there would be a lot more comfort in the usage of AI simply because it now is closer to the way we expect certain outcomes to be.

speaker-1 (46:28.11)
After hearing you, just hoping, because there is a very important role right now in the whole AI world that is the AI ethicist. Those are the ones that are making sure that these LLMs and the outputs and what they are producing is as ethical as possible, Less bias. So this is very important role that is not discussed a lot. Companies, you

building these AI systems and applications, this role is supposed to be the one teaching and reviewing and making sure that less and less bias is found on with every single version that they put out there. I would like to think that they are hiring good people with, you know, that type of thinking as you do, as you have that are making sure that the

We are trying to do everything we can to remove bias from these LLM systems. So Karen, we are about to get into the final section of our conversation. It's one question for multiple groups. So it's, I'm going to start with the first group, but it's going to be kind of the same question for different types of groups. And, and I go through that with every single guest just to see what you think about that. so the question is.

for the first part of it is to regular individuals, human beings. How do you think, man, and what would be your piece of advice so we can continue to evolve as humans without losing ourselves in the middle?

speaker-0 (48:10.254)
I think that is certainly true because evolution has happened for a really long time. The challenge will be that as humans, because we are completely unpredictable, every single individual will have their own path. But again, we would have to figure out what that path is going to be. It's not going to be the same for everyone. And it shouldn't, because that's the beauty of humanity. It can't be the same for everybody.

speaker-1 (48:35.722)
It should not be, right? If not, we would turn ourselves into another robot and we don't want that to happen.

Karen, to companies, right? What do you think must be true culturally before AI actually work for your people?

speaker-0 (48:54.382)
Yeah, for companies, it would definitely need to be essentially a culture shift openness to diversity of thought is probably the biggest one. But in order to achieve that, that requires really at the highest level, the concept of building that space for everybody at the company. So again, be vulnerable with your learnings, make sure that you're having conversations with your people. And that's really the.

best way I would say to get AI implemented accurately. Because if you're not having those open and honest conversations, there's going to be fear, there's going to be resentment, there's going to be, I would say, inadequate adoption. And again, I know I mentioned earlier, it depends on what your definition of adoption is, but definitely without that open culture, you're going to run into roadblocks.

speaker-1 (49:49.166)
All right, thank you. Your piece of advice to AI leaders. These are people designing and building AI systems. What would you like to tell those companies working on AI today?

speaker-0 (50:01.75)
Yeah, again, open conversations, share the ideas that you have, things that you're working on, of course, within the constraints of anything that may be proprietary. humans are interesting and also AI is proof of this. There are no new ideas technically coming from AI because it's a trained model. It's pulling information that has already existed in the universe. Now I'm not saying that

There are no new ideas in the world ever. Like that's a different philosophical conversation. But if you want diversity within your conversations, if you want individuals at your company to really be able to take your, whether it's a support department or whatever it is further and have a positive impact on revenue, it's really going to come down to again, having that open conversation.

And to ensure that there are various voices that are part of it. So as a leader, make it safe for those to come forward, to share your learnings, share your learnings to the rest of the universe and to the community. We are a very giving and learning culture. I would like to say, especially in the support space, let's continue to do that. And, and definitely if you are in a senior position and you have the ability to do so. Make your voice heard. And I don't mean that in a way that.

females or leaders aren't making their voice heard, but it's more that the thoughts and the ideas need to be out there. you know, individuals within the support community or otherwise will be able to support and amplify that information. But you have to take the first step to share what you know. And I truly believe that, you know, the community will help bring those ideas forward.

speaker-1 (51:48.182)
Yeah, so I always say sharing is caring, right? And that should continue to be for sure. And last but not least, Karen, your piece of advice to governments and policymakers, what would you like the focus to be at that level?

speaker-0 (52:02.51)
Yeah, continue, definitely continue working with anyone who needs to really hear it. So what I mean by that is there's again, like what we talked very briefly about like bias within AI models. We need governments to put in the appropriate guardrails to make sure that our data is ethically used and also, you know, appropriately like leverage for whatever that looks like.

course there's environmental impact, which we will not get into about AI usage and such, but there's definitely thought that needs to go in on how we're using AI, how those models are operating. But also if we are looking at the headlines, if we are looking at what is out there from the negative lens, then we need to figure out a way to ensure that the individuals that are out there who are looking for opportunities are not left out in the dark. Like I've been mentioning in this entire conversation,

where it's important. Our identity is really put together based off of a lot of it is diversity of thought. And so if those individual pieces are not coming forward, then we definitely need policies in place. We definitely need guardrails in order to ensure that everything's being used ethically. And I think that's really the most important part.

speaker-1 (53:22.932)
Absolutely. Thank you for that, Karen. And Karen, my friend, one more time, thank you for being with us today and for taking the time to be part of this amazing conversation. I appreciate you.

speaker-0 (53:34.21)
Yeah, for sure. Love it. Thank you.

speaker-1 (53:37.292)
Thank you. And if this episode made you uncomfortable, that is good. This is not a tool conversation and it's the truth about, you know, about what it will happen to us. And share this with someone that is leading a team building systems or maybe questioning their place in all of this, right? As we all are. Follow the human protocol because the code may change, but our humanity, it always going to be the constant. Thank you all and see you next week. Bye bye.