Tech Equity: Breaking Barriers in Pay, Healthcare and Psychology – Tech.Strong.Women. EP 30

Hi, everybody. Thanks for joining us for another episode of Techstrong Women, where we feature amazing women doing amazing things in tech. I'm Jody Ashley, executive producer here at Techstrong.

I'm here with creator and CEO of Deploy Hub. Before I introduce today's guest, I wanna give you a quick update about what's happening here at Textron. Be sure to register for Textron Con 2024.

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tv for great shows and interviews. Okay, Tracy, what's on your mind today? Uh, gender Equality and pay.

So there was an article sent to me via email. Um, I didn't discover this, I was shocked by it though. Uh, company by the name of Design Rush did some, um, uh, gender gap pay analysis based on government records and other critical information.

So it looks like it's pretty real, let's just say it that way. And most women stop getting paid by November 20th nationwide because of that gender gap. So that means that men are still continuing to be paid, and that's how much more that they are making, um, than women, which is horrendous.

And what really annoyed me at, at the most was that there are, um, I'm just gonna call 'em out, North Carolina, Utah, and California, three primary areas where there's good investment, uh, and tech startups. They were on the top 10 of the worst, uh, cases. Uh, if you look at the case of North Carolina, Utah, and California, they're around 75% of, uh, they're paying women, 75% of what men make, which mean ladies, if you work in one of those states, you don't get paid for the last quarter, not November 20th, but the full last quarter of the year.

So the last three months, you're not getting paid. The guys are, this is like really bad. It's, we, it is time that this stuff is being called out and women need to start complaining about it, and we should be, it should be the opposite.

Women are such hard workers and so dedicated that we should be seeing women in tech in particular, being encouraged to get into this industry and being paid, um, at least five or 10% better than the men, in my opinion. Uh, so speak up. Let's, we need to use our voice on this one.

It's not right. It really is not right. And kudos to some of the, the states who are at almost a hundred percent South Dakota, Idaho, and Connecticut are the top three.

Now that may be, um, because the pay in those states are lower anyway, and so it's more averaged. But in states like California where there is so much investment and so much money, it's horrible to think that women are making about 79% of what men do in California, especially when they're always bragging about, you know, how liberal and how diverse they are. You know, it's terrible.

It's really terrible. So that's what my bugaboo is today. Well, that is a good bugaboo.

Thank you for, uh, for bringing that up and, and talking about it. Um, I'm really excited to introduce our guest today. She is a fellow Coloradan and um, her name is Shannon Mason.

Hi Shannon. Thanks for being with us today. Tell us a little bit about yourself.

Hi, Jody, nice to be here. And hi Tracy. And what a bugaboo and even more aggravating when we also factor in, um, those folks that are from diverse populations, because I think it's like, then we're losing like a quarter and a half, or sometimes even a half year.

Um, it, it's a pain. Um, it's a pain we need to solve and definitely, um, something that I'm passionate about, which is why I keep receipts. Um, you know, you gotta shout, you shout, shout your successes from the, from the rooftops and, and definitely take credit, uh, where you've been doing good work.

Um, but that's not what you asked me, Jody. You asked me a little bit about me. Um, so yes, I'm, I'm here in Colorado.

Uh, love it. Beautiful state. Can't cross over the border and move here, which I did two decades ago without loving being outside.

Um, but, um, in my not outside activities, I run strategy for Tempo Software, which is, um, product portfolio, um, managed by, uh, pe. So we can potentially get into that today, what that looks like. Uh, and in focus specifically on expanding where we're going, both from our GTM perspective and then also from a product lines perspective.

Um, in my previous lives, uh, I've taught pre-K in kindergarten, my background's in child developmental psychology and applied social neuroscience. Um, ran a product for a little company here that's a little bit of a startup darling that went public and then got bought by ca called Rally Software. Uh, worked at GitHub as well too.

So, um, been very deeply involved in the Colorado Tech scene, um, since moving here. But there is this weird wild varied life that existed before that, um, which includes traveling, um, while I was working at the United Nations and a bunch of other things. So, stoked to talk about whatever we're gonna talk about today, because I know we can talk about a lot of different things.

Um, but, uh, but yeah, nice to see you all. Well, when we look at your, your resume, you are a rockstar in the technology business, and I hope to goodness that you get paid more than you're felt like you're the man that you work with, Because I think you deserve it. You, you have a very interesting background and you've done some really, I mean, you've been playing hard, uh, you know, hardball, uh, in the tech, in the tech, uh, business for some time.

And it's not easy to do that when you're in a male dominated world. So kudos to you, especially, you know, we have a similar, we, we have some similar background. Um, I have done business with ca and I continue to do business with Broadcom in a little company that we created 1995 called Open Make Software.

Uh, and they still resell our, our software to this day after all these years. So I always liked ca I always did Definitely good, a good place, great learning experience for me is the spot where I got to move into product leadership and, um, a really fast learning and what that looks like, especially in a publicly traded environment, which is totally different from vc, um, even different from pe. Um, and so that was, that was a fun, a fun time that I, that I had there.

And RA was especially unique place to be, um, and a unique time to be there as well too. So I owe a lot, a lot of my learning from the tech side to, to that time. Yeah, I remember the ca world after Rally got bought and it was huge.

It was like, oh my goodness, all the rally people are here. They showed up. So, you know, the, um, the thing about it is, is that it's not that you've just been in those roles, you've been in high level positions in those roles, uh, give us some insights on how it, how you worked your way up, that, that, um, the ladder, uh, you know, you, you, you've achieved some really high level successes in your career.

What is your secret? Um, uh, I'm, I'm always looking to learn. Um, so, and, and I will probably bring up quite a bit of, of, of the time that I spent at Rally.

'cause it was a good, a good chunk of time that I, I was there and I got to do a lot of different things. Usually every couple of years there was something new and interesting that I could, could do. Um, the, the big thing for me is, um, I really believe in organizations that have that mentality of get the right people on the bus and they'll find their seat, and then as the bus gets bigger, um, you might need to be changing seats.

And so even with folks that I work with now, um, especially if they're looking for new jobs, we're looking to transition or to find something new even within the organization that they're working within, it's a, that question that I like to ask, even ask myself is, um, you know, where's the u-shaped hole in the organization? Go find it and fill that hole. Um, and then if there's anybody in the organization that ever taps you and says, Hey, I think you might be good at this, rather than having that reaction that's like, oh, but that's not what I do, or that's not what I've been thinking I should do, is to go chase that thread.

So, um, a lot of my background has been around chasing different interesting threads, like, oh, that's interesting. I'd like to go learn more about that. Oh gosh, now it's my job.

Um, even here at Tempo, when I started, I was looking at our diversification path. So, um, a lot of the work that we do is in the Atlassian ecosystem and supporting organizations with, um, different applications to enhance and supercharge their use of Jira. Um, and so I was kind of interested in that, but I was focused on a completely different area.

And I think within four months I ended up, um, becoming our CPO and then taking over our entire product direction, product vision, and our m and a strategy. And then in the summer, um, my boss Mark, um, that's another key thing, right? You gotta have great leadership around you that, that sees your potential as well, and supports you in those moments when you're like, I dunno if I can do this.

He tapped me and said, Hey, I know you're concerned about product every single day, but I'd love for you to wake up and be concerned about everything in the business. Um, and you kind of are in product in general. But, you know, that even took a moment for me to be like, okay, is this an interesting thing?

Well, every single time someone said, Hey, why don't you go explore that? It's never been a bad thing. It's always been a learning experience.

And so I I dove right in. Um, and the benefit Of that. So it sounds like mentors have been important then.

It sounds like you've had some mentors that, that you've worked with and listened to. Yeah, Yeah, absolutely. Absolutely.

Um, great, uh, women mentors for sure. Um, uh, you know, the ones that you can bring back a, a job offer and say, Hey, can you tear this down with me and help me put my bullets together so I can come back with a counter? Um, I've had great, uh, leaders that have also become mentors after working for them to just kind of help me on my career path and my career trajectory.

Um, and then finding just folks that believe in, I, I call it the lowercase p potential, right? So people that see like there's the root of something or the seed of something, or if I give it a little bit of watering, a little bit of nurturing, it's gonna grow. Um, that's been a, that's been a big part.

So yeah. Can't, can't say enough about having good folks around you. Um, for sure.

And it's so important to be able to pivot and find the u shape. It's, that's a really good analogy, but pivoting all the time, especially in technology, 'cause it's changing so much, right? So if we've put ourselves in one area, we're probably gonna kind of flatten out.

But if we continue to look for the, the pivot and the u-shape, it allows us to jump right. And Find out what's new. Yeah.

Yeah. See what else is out there, what else is, what else is possible. Yeah.

And I think the big benefit to reading as well, like just being that continuous kind of consumption of information, at least for me, I do a ton of reading, um, every single month. Um, it's a joke in my household that my pleasure reading is not nonfic or is not fiction, it's nonfiction. Like, you know, so it's like, what pleasure reading are you doing right now?

And I pull out this big tome on like, the psychology of planning and organizations, and people are like, that's, that's not pleasure reading. Like, well, for me it's just delightful. That is an awesome superpower to have.

It really is. I have to admit, I do, I do read a lot of technical stuff, but it's usually not in books. Um, I do like, I do like my historical fiction.

I find it fascinating, especially around systems. And I think that that's an amazing topic that's starting to happen and I'm so excited about it. But beyond that, you say things, you know, you like to, what, what are you looking at now?

So if I realize that you've been in portfolio management and did you get into portfolio management at ca? Yep. Uh, via rally, you know, as, as we started to see agile practices change within organizations, it became clear that this was going to be something that wouldn't be contained within engineering, within product development.

Um, and so that sent us down the path of seeing how do you start doing this at some level of scale. Uh, and then obviously all the things that bloomed and blossomed around that. So, but that was, that's where I got into it.

Um, before, before moving out here to Colorado, I, I taught kindergarten and pre-K um, I worked at a, a hedge fund, um, during the height of the best time to work at a hedge fund in New York City, which was 2007 to 2010 almost. Um, so it's been, it's been varied, but yeah, when I moved out here is when I got into tech solidly. Um, I had always been interested.

And then rally is where I started to really embark upon what does it look like to do modern portfolio management. And that's been a passion of mine ever since. 'cause so much of it is about human psychology.

So I wanna talk about portfolio management and security. Is there a connection and explain to us what it is. So, um, security in what way, Tracy?

'cause we could go probably a zillion different ways. I would say software security and security within your portfolio. Yeah.

Yeah. Um, you know, it's interesting in a, in a past life, um, I had some security products. And then also at GitLab, a big component of secure securing your code before deployment was, um, doing scans and everything was a big part of what we focused our customers on.

Um, for me, the, the ability to have the faith that you're deploying code that you know, has no secrets that people can't be able to exploit is a huge value add. I'm a self-proclaimed SaaS a*****e, so I'm all in on the cloud. Like, it's, it's where, its where the future Is.

That's amazing. And, and part of their distance there, right, is that people are always like, oh, it's not secure. Oh, I don't know.

Oh, oh, this, oh that, oh the other. And I'm coming from environments where I know that's the security that we were providing, both from an infrastructure standpoint and then even from a deployment standpoint, was so high because we had to provide that traceability. We had to do those audits, we had to get inspected all the time.

I had such a, a high level of faith in what we're giving our customers and what we continue to give our customers at tempo. Um, but for me it runs all the way back to, um, you know, in a business, if you're managing a portfolio, let's say you're a rockstar, video games, one of the things that's really key is that people can't hack into your, your games. Um, 'cause the moment they hack into it, you're actually losing your ability to generate revenue.

We could probably debate whether or not micro transactions should or should not be a thing, but you know, every single transaction that happens, every person who buys the game, who gets committed to playing the game, who plays the game in the way that it was intended to play, those are folks that are gonna come back. They're gonna be repeat customers. And so for me, it runs the gamut of those small things that we think about just in terms of how are we doing in managing our code all the way through to whether or not the products that we're putting out to market, uh, are of the high security that we expect.

Um, and especially for me being really kind of embracing cloud native in a traditional way that we define it, um, that's been just part of, part of my existence in developing software. So, um, important across all facets for me, Tracy, um, from each line, from scanning all the way through to deploy and post. So I have this general belief that, um, chaos engineering, which really focused in on SREs and the ability to bring a system back up after it's been mm-hmm.

Some bad thing happened, right? Yep. Can be applied beyond just production support.

And the more that I'm involved in the open source security world and just supply chain security for software in enterprises, what we are, what we consume, the packages that we consume, that we don't know about it, the more I feel that we are at a place that we can't code scan our way out of this problem, I really don't believe we can test our way out of the problem either. Which brings me to threat models, machine learning, and artificial intelligence, because I believe that if we have the right data, if we have the data, then we can start doing accurate predictions. And now in the DevOps world, unlike other industries, we don't have a lot of centralized data.

That's one of my, um, passionate things because if we did machine learning and even potentially generating, um, uh, pipelines and, you know, pushing 'em out with a pull request so teams can say, oh, there is a better pipeline. We should look at it and see if we should use it. Right?

I think that's a better way to go. Mm-Hmm. I see Anything in portfolio management that is similar.

And is there a direction for portfolio management to start using AI and machine learning and generative ai? Oh yeah, for sure. Um, and I like the, I like the chaos alignment too as well, right?

It's, it's all the tools that we can use at our disposal to make everything better. Um, in portfolio management specifically. And I like that we're just calling it portfolio management.

We haven't given a qualifier, which is, which right now it's in the, the space is in a little bit of a, a shift. Um, one of the things that for me has been a long time, I know frustration is, um, you know, I'm one of those folks where if someone said, Hey, we're gonna give you an embeddable chip, we want you to beta test it, uh, the benefit of it is that you don't need to carry around your wallet ever again. And I can just walk through the airport and people can scan me and I'd do it right.

Um, and so I think for me, when the promise of big data emerged, and I call it the promise, because it was like, for a few years, it was just big data, big data, big data. Like you're gonna have decision, you know, data-driven decision making in your organization, all choices will be the right choices. And then you add the human psychology component in there and it kind of mucks the whole thing up.

But with portfolio management, one of the things that I feel we're on the cusp of, and it's something that we're exploring here at Tempo, is we have similar amounts of data on how organizations choose select structure, the way that they want to align their product portfolios, how those product portfolios then get de comped into the actual tactical work that happens. Who's aligned to that work, how long it takes. Um, when we start to see things veer a little bit off course, what are the different components that have actually led to that, that challenge that we might see?

So one of the, the hopes that I have and and we're something that we're doggedly pursuing at Tempo is can we observe just the natural network effect inside of an organization, pull a lot of that data that we already have historical stuff, move beyond just regression analysis with it and actually start to build predictive models that tell people, Hey, things are starting to go off track. We've seen this pattern before. Here's a way or three different other ways that you might be able to get out of this particular path that you're on.

And here's the impact to the overarching strategy. It's up to you to have a discussion about whether or not this shift in the window of opportunity or the change to the strategy is tolerable. But we're not gonna make you do the work about thinking about how the work's gonna get done, because we already know enough information to give you that first starting point.

I feel like a lot of our lives are focused on what I've called for a while now, like work about the work, right? Like, let's get together and let's plan and let's plan and plan and plan and plan. Even though planning is a continuous activity.

There's enough sense information, sense data that we have enough coincidental indicators to tell us whether or not we're on similar tracks and paths in what we know just from longitudinal psychology, psychological data and organizational planning is that works tend to follow similar paths over and over again. It's kind of pushing them out of that path to look at different potential opportunity. That tends to be a challenge.

That's where I see, um, AI and really good models being able to help portfolio management, um, make better decisions about what it is you wanna put inside of your plan so that you can hit those windows of opportunity. And, you know, every tool, you know, we get, as a smaller company, we always get people, I I get people all the time, you know, emailing me of inve potential investors and whatnot, and they always ask, are you an AI company? And it, it, I don't even respond, honestly.

It is be it because if, if we're, that'd be like asking somebody, you know, back in the, I guess would've been the early nineties, is do you use DB two? You have a relational database? Yep.

Uh, because AI is just another technology that we all can benefit from. Every single software project in the world can look at their new relationship with data. Yes.

Now some, now some industries are really pushing it legal. Um, legal is legal's a perfect example because there's so much already data online medical, which I know that you have some interest in. Um, yeah.

So what do you think are some of the industries who have really started really benefiting from the new technology that we can now put into software that we call artificial intelligence? Which by the way, has been around for quite some time A while for Years and years and years. It's like when mRNA came out and people were like, this is brand new.

And it's like, no, it's been under, under investigation for decades upon decades, right? These really new innovative things take so much time to build. Um, you touched Tracy on, on the medical side.

That's something that's really important to me. And I think it's one of the areas that we're already seeing some really good traction. Um, and it's not that the human ability to recognize patterns, to see that something is occurring or to see that something's happening is, is it's not great.

It's just like, I, I think of, you know, our context that we're moving into as like, what's it like to have a helper who can kind of double check my assumptions and then also provide that, um, that third party perspective that you oftentimes don't get. Um, so you're, you're seeing things, you know, with like doing scans where, um, you know, because we've got good models built up around certain things, certain esia that might be seen around tumors that we're able then to make better and more accurate diagnoses. Um, that's something that's really exciting to me.

Um, another area that I'm really passionate about personally around everybody that might be making a visit to the doctor because they've got some strange, strange thing occurring in their body, um, and then all of a sudden it turns out they've got maybe an autoimmune disease and the realities of, of that look like people going 15, sometimes 20 years to get a diagnosis for something. And I really believe that there's going to be this power of bringing together sets of data from the crowd that help us find patterns that are repeatable across people that help to get us to diagnosis a lot faster. Um, and that saves, you know, not just people's time health, their quality of life, but it also has in the long term, a pretty good savings from just, you know, healthcare and all of those expenses.

So, so I'm really excited about the medical applications, uh, of AI in addition to the, the portfolio based ones that, um, fill my work life. But in my free time, you know, being able to get somebody to a lupus diagnosis in half the time or maybe in, you know, two months because we've got repeatable data that we can pull on, we see different patterns across the network of, of impact that folks have is something that I believe we're gonna see and we're gonna achieve and we're on the path to it because there's a lot of folks doing very interesting work in this particular area. Well, it also seems like, it also seems like the way that, um, different providers are blending care together.

Like Kaiser always did this, right? You went to your Kaiser doctor, and when my parents did that when they were alive and all their doctors had access to everything. Yeah.

Everybody used to make fun of Kaiser, like, oh, Kaiser. But the idea that no matter what doctor we took them in, in, in their old age, they could see their whole chart. And you're seeing that more and more where your providers are interacting and everything's in one place.

And I would imagine that is a critical thing for, to, to apply the ai. You need all that in data in one place. You need your regular doctor and maybe you have to go get a colonoscopy or your mammogram, but all that information is in one place, and then they can apply things that see those patterns, right?

Yeah. I think there, you start to then get the, the possibilities of having the crowd of data that comes in. So right, right now I've been talking about just like, how do we get people to, um, a diagnoses faster, but if you're inputting also the things that are helping you feel better on a regular basis, we might have better paths towards treatment in addition to medicines, especially since, you know, anything that has to do with the body as a holistic thing, even though we like to think about it in terms of its little components.

So Mm-hmm. There's a lot of hope that I have in that particular area that it will lead to better treatments, um, better programs, better palliative care for folks. Uh, and I think that's the part that gets me excited about ai, not the part that's kind of gloom and doom, or it's just like, oh, the, you know, the bots are coming to take our jobs.

It's like, well, I am the same way. I I I look at the technology and the excitement of the technology side and you know, there's something that Jody said, electronic health records has been an issue for quite some time in the us Oh yeah. Because of the security and the privacy issues.

But it hasn't been in India. India has had a electronic health records for quite some time, and they are already starting to do quite a bit of work in this area because they have a bigger pool of data. Wow.

Now, unfortunately, it doesn't necessarily benefit people in the United States because people in India have a lot. There's culturally there's a lot of difference. Physically, there's a lot of difference.

So it's inter, I mean, AI has a, has a regional Yeah. A regional problem. Right.

Even, you know, sometimes when I, I sometimes I'll cheat and I'll wanna submit something, a talk, and I'll use chat GBT to get me started. And I often think, you know, this is a US perspective, right? Mm-Hmm, yep.

And it might even be a male perspective. Yes. Yeah.

Yes. But the, but having, having the ability, I think that the reason why electronic health records was important in India was because they had a billion people to serve. Right?

They had to have something cohesive. Right. They had to, and the, even though we have a lot of great doctors in the US and everybody has comes from good intent.

When you go in to see a doctor, they only have 15 minutes to spend with you. Right. And They spend so much of their time just entering the inflammation too.

Like I Had, my eyes were swelling up not too long ago. And so I went in, I was like, what's wrong with my eyes? And they gave me, they gave me prednisone, they gave me, uh, Benadryl, they told me I was allergic to something.

And it never stopped until I started looking at myself. Mm-Hmm. And I actually asked chat, GPT, what is the main cause of the ice swelling and what did it say?

Dehydration. Oh my goodness. And I had just come off of a really bad cold, uh, where I was taking a lot of, uh, you know, stuff to drive me out, like Mucinex and everything I can think of, and I got severely dehydrated, but they couldn't figure that out in the 15 minutes.

Right. Because I, the, the records were not there. Yeah.

So, and this, I think trace you're hit on something that I, that I hope for and, and is a core belief that I have around, we'll just say the big AI umbrella is, is kind of having that, um, the, the copilot with you. I mean, literally to f not figuratively, but just literally, right. Copilot and GitHub's.

Pretty interesting, interesting technology that they've introduced. Um, so that like, you know, in that particular scenario, the doctors oftentimes are thinking about which codes do I need to enter? Just the way that a, you know, a program manager or program director at a large bank is thinking about, oh, do I have enough humans to get this work done?

But if we can apply a little bit of, of, of logic to it via machine learning, via these models, and actually free up time to do the job that we are actually hired to do, or the job that we want to do, um, that's my hope, right? So that we can spend less time in the, the busy work, right? And, and actually say like, oh, you know, Tracy, you were sick for the last few weeks.

How are you feeling right now? You know, how's definitely increase the hydration here? Not thinking about it like, is that code 2, 2 1, I gotta make sure I code this correctly or else we don't get paid.

You know, those sorts of things. That's my hope, at least I, you can tell me. So I'm seeing this, I'm seeing this, you guys, I am, I was a professional athlete in my younger days, and my body has taken a beating.

So I spend a lot of time at my orthopedic surgeon's office, and they have started using all this, the whole office. They have, um, an AI tool similar to Alexa. Hopefully she won't bounce up here.

She's in here with me. And when I go into my visits for my shoulder, my wrist, my ankle, and my knee, depending on the doctor, they, they tell you they're starting it. So the minute you walk in the office, the tool starts recording.

The doctor doesn't take notes, nobody. It's totally focused. And then when I get done, I get a transcript via email of the conversation so that if I forget some exercise he told me to do, or some, you know, maybe supplement he thought maybe would help me or whatever, I can go back and reference it.

And so it's happening and it's really cool, but it's very small. But it's, you know, to me, when I, when they, they started a new office nearby and the, my first visit, I was like, this is crazy. 'cause their whole focus is on, you know, and then they dictate right into the end, you know, he dictates his notes, machine takes the dictation, and then we're done.

So it's pretty cool. And would be really cool if, I mean, there's still places they're writing on paper, you know, or they're that mean, they're not even using an iPad or a computer. It's crazy that the differences.

So it is nice to see that it's happening, think, adapting, Dictation. I mean, then the doctor, we could just talk to you and it could dictate the notes right. Immediately.

I mean, That's brilliant. That's what he does. And, and it, there's no attention.

Like the whole conversation is recorded, so no, nothing gets missed. They can look at it later. Their PAs and their assistants will see it goes in your chart.

It's pretty cool. Yeah. That's awesome.

Teachers now. Yeah. Yeah.

Okay. So I wanna know, we, this has come up a bunch, your psychology background. It sounds like you use it all the time.

And I bet teaching, you know, kindergartners probably helps too, should be perfectly honest. Some of these grownups we work with, Oh, it comes, it comes in more handy than I thought. You know, people are just like, I'll get it precious if you use that anymore.

I'm like, oh no, I, I don't use that anymore. But the psychology I use almost every day. And, um, and sometimes, you know, you'll be in calls with people and you'll, you'll recognize that they've gotten triggered or something's occurring for them Yeah.

In their body. So did You, did you study it in college? Or where did you start with that?

Yeah, I, you know, I, um, I got interested in brains. Um, my mom had, uh, an aneurysm, a brain aneurysm, and had a major brain surgery. And interesting things started to happen after that.

Like, um, she had something called Goreman syndrome for a little while, which is like a, like an a like a intense desire to cook really good food, which was awesome. It was really awesome. Um, but also at the same time, you're sitting there and you're like, this is, this is really strange.

Um, and so Who are you and what have you done with my mother? My Mom? Yeah.

Um, and so like that kind of kicked off this interest, um, as a young kid around like, what, what's going on up there? There's so much more that we, we don't understand. Um, I think it was the first time where I had like an awareness that like, oh, there's this thing up here that controls way more than I think I know.

Um, and that set me down a path. I had always been really interested in, um, early childhood development because the brain grows so quickly between the ages of, you know, in utero all the way through to about 30, there's some of these big growth spurts. And I say about 30 because men tend to have a bi, a late stage, big growth spurt.

And those things become applicable. So, um, for example, I remember working with, um, with, uh, with a company down in Texas, and they had given this, this gent right outta college. Like he was fresh outta college, like this really big decision, like big responsibility.

And, you know, some of the older folks on the team were like, we don't know why he made this choice. And I was just like, well, you know, that whole prefrontal functioning is not fully developed just yet, so make the best decision you could with a developmental level and capacity that he had at the time. Um, and so I think that helps a lot because you're just sitting there and you're like, okay, like we're fallible.

We're gonna make mistakes. Um, we're at different stages, all of us. Um, and having that play into how I think about, uh, even just, you know, my job, uh, 'cause a lot of my job is trying to look into the crystal ball and figure out a good way path.

Um, and then also with portfolio management, a lot of times that's what we're trying to do is help organizations figure out the good path. Um, and so much of our, our past experiences, our psychology actually plays in and factors into how we make choices. And then you throw 30 people in a room and you ask 'em to make a choice together, and you've got all the social dynamics.

Um, but yeah, it started from, from from my mom. She was the inspiration. And then I was really interested in our early childhood childhood development.

And I stopped honestly around 12, 13, so like really focusing on younger folks, because 1213 is when people learn manipulation and like, they get good at it. Like kids are pretty good at manipulation. But around the teen years is when like, people get really good at it, like, oh, it's here and I can do this, and that will be a different outcome.

And honestly, I just, I didn't have the patience. Oh, it's a, it's definitely a spiritual gift that isn't it? Oh, that's Pretty.

So, you know, there's a, there was an article I read recently on, on the topic, and I think that that it, there's been many articles on it, but the topic, and I'm gonna go back to AI and how people trust ai. I read recently that robots, um, get, uh, people get more angry and blame robots faster than they would a human. Which, so if, if Kara has an accident, humans have accidents all the time.

But if a car has an accident that was being self-driven, there's a lot of blame and a lot of focus, uh, on the, on, on the technology. Why I don't think we've, I don't think we've crossed over into full personification yet, right? So when we're, when we're talking to, talking to maybe chat GPTI would venture that most folks aren't saying like, Hey, what's up?

How are you? I've got this set of questions, you know, like, can, can you gimme, can you gimme a first, uh, first direction on how to potentially solve for this challenge that I'm running into when I'm writing code? You know, we're just like, oh, it's a machine.

I'm gonna treat it like a machine. Um, and, and when we look at people, I mean, even one of the consequences of all of us working from home for so long and being in the little boxes was that we, we didn't have that person to person connection. Like, there's actually something that happens when you see a physical person that you work with in flesh and blood.

It, it creates more empathy for them. And I don't think we've figured out how to create empathy with what we've been taught is a machine just yet. Um, although I may be on that category of people at, Hey, how are you chat, you PT you got for you today?

Um, but we haven't crossed that personification level, but we know it's possible because people name their cars. So it's, it's just right around the corner. Yes, they do, they they do name their cars.

But that kind of makes sense to me. You know, you gotta personify something, um, before you have empathy. So yes, I, I get that.

So you could be more empathetic to somebody who made the mistake that made you crash your car than you can if a robot made the same mistake and crashed your car. It's the same problem, the same mistake, but it's a human as opposed to a robot. Yep.

Yeah. And we, we have the expectation, right, that these are, these are, um, completely infallible. Um, I remember some of the initial legislation that came out, I think in the eu was if you're using some sort of even predictive model, um, this was way back, I think maybe 20 12, 20 13, around there.

Um, if you're using some sort of predictive model and that model has a negative outcome on a business, you could be held liable for the consequences of, of that. And so what that turned into was this resistance and this lack of trust. Um, but I also think that elevates, elevates ai, big umbrella AI into this level of status that it hasn't yet achieved, which is like, it's taking the lead versus running alongside of, of us.

And I still see it as running alongside of us currently. I hope it stays running alongside of us. I'm more of, I'm more in the, oh my God, is it going to take over the world?

There's too, I want to take over Congress. I mean, Probably do a better job. Exactly.

I think AI would be really good just to run Congress right now, Back to the, back to how we started the conversation, right? With, with like equity and pay and everything. Like it does, like, there's, there's no opinion there.

I mean, although there are opinions in AI because of the way that's coded and bias, but that's humans, right? Humans are ascribing that opinion to it. And we can get the tech kind of opinion less world.

I mean, the thing that I'd love to see, and I remember seeing this over the summer where people were like, oh man, I was really hoping that I would be able to make the art and that the AI would take the, you know, the tedium of work. And I still kind of hold out hope. But that requires us to have a complete systemic review of society.

And, and that's a people problem. That's, that's not tech, that's, that's people. Um, but yeah, I, I'm hoping for the day where, you know, the bots are running the things that we don't wanna do so that we can actually spend time and community with each other.

'cause that's, I mean, like ho hope, that's what we're put on earth for. Well, and that's, well, that would be, we know it's not gonna replace humans because we still need that human element. We need the supervision of humans.

We need the element of being engaged in it. So yeah, I mean, I, I don't think it'll take, take us over. I think we just need to keep it in, its in its place and not let it become, you know, abused, which we're seeing that happen in, in areas, you know.

But Yeah, in politics, it's gonna get abused. Big time in politics. We're gonna see it big time this year.

It's unfortunate, but that's the case. So everybody has to be very, we're All gonna get a taste of AI abuse, but up until November, yeah, Vigilant, be vigilant. So Shannon, you are a bookworm as you have, you've self-professed that.

Um, leave us with the a, a a book that we should read. Absolutely. Great.

One trace. All right. Um, I Just finished a book, so I'm looking for one.

I've I've got one for you, Tracy. Good, good. Um, and, and again, kinda keeping with the theme of, I, I don't read particularly exciting books, so, um, but this one I find, uh, really wonderful.

It's when I come back to all the time I quote it, it gave me the, I think the song, the song of the, the Mariner's Lament or something like that from an old play, which is go make yourself a plan and be a guiding light, then make yourself another plan for neither will Go. Right? Um, which is life, um, where I Still live by Yeah.

Seriously, to all of my product teams that I've worked with, like, hey, this is our guiding principle. We have one plan that we make other plans because, um, there, there we are with, with the, the model of ai. Anyways, um, a great, great book, one that I love, one that I come back to quite regularly is Dietrich Thorn's, uh, the Logic of Failure.

And it's all about the human tendency to know a pattern that you've experienced over and over and over again and how hard it is to take new information in and change your pattern based off of that new information. So it's full of great examples. I mean, going all the way back to Chernobyl, um, that's how the, the book starts.

And, um, you can imagine you're watching the Chernobyl mini series and me pulling that book out and sitting down with my partner and being like, it was even worse than what we're seeing here. Like, they, they had so many different points of information that were coming in that were telling 'em that something was off track, but um, they had a historical pattern of knowing this kind of flaky test that was occurring, essentially. They're like, oh, it's just the flaky test.

And, uh, Dorner provides tons and tons of examples like that. And the thing that I love about that book in particular, um, aside from, it's just full of wonderful quote quotes that you can throw at people when they're exhibiting behaviors that are, that are antithetical the good patterns moving forward. But the thing that, um, the thing that I love about it is he gives you also some tips about how to work outside of that, how to get out of that pattern, how to trick yourself into thinking a little bit differently.

Um, and he really focuses on, and for me as an, as an agile, through and through, um, making sure that all the ritualistic ceremonies that you have as part of your life are part of your business world. That they're not there just to kind of keep you sedate. That they're there actually to find triggers and signals to make different decisions.

Um, and once you kind of grasp that part of the book, it's just like, okay, like nothing is actually as it seems, and we should always be asking the question of what data here is telling us to move in a different direction? Well, maybe It'll help me stay on my diet. No, That sounds like an amazing read.

Thank you so much for, for that. Well, you know what, that's a, a great stopping point for us here today, um, Shannon, and we just really appreciate having you. This was, this was a great conversation.

Um, thank you so much for being here. Uh, Tracy, as always, my partner in crime, it's always good to see your face. Um, everybody just tune in to Text Strong tv and um, we'll have another episode of Text Strong Women up for you soon.

Thanks so much for being with us today. Bye everyone. Thank you.