AI or Not

E005 - AI or Not - Brenna Coppola and Pamela Isom

• Season 1 • Episode 5

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Welcome to "AI or Not," the podcast where we explore the intersection of digital transformation and real-world wisdom, hosted by the accomplished Pamela Isom. With over 25 years of experience guiding leaders in corporate, public, and private sectors, Pamela, the CEO and Founder of IsAdvice & Consulting LLC, is a veteran in successfully navigating the complex realms of artificial intelligence, innovation, cyber issues, governance, data management, and ethical decision-making.

What if your data could truly reflect the diversity of human experience? In this eye-opening episode, we sit down with Brenna Coppola Milner, a seasoned account manager and data-driven solutionist, to discuss her fascinating career journey from a marketing graduate to a tech sales professional. Brenna sheds light on the pivotal role of relationship-building in sales and why starting in a business development role can be a game-changer for anyone looking to break into the tech industry. She also shares her views on the transformative potential of AI and emerging technologies, emphasizing the urgency of democratizing data to ease public fears and soothe digital anxiety among business leaders.

We then confront one of the most pressing issues in tech today: unintentional discrimination. Through compelling real-world examples, Brenna tackles the biases inherent in AI and tech development—like soap dispensers that don't recognize darker skin tones and facial recognition systems that fail people of color at airports. These anecdotes not only highlight the need for inclusive design but also underscore the critical role that diversity, equity, inclusion, and accessibility (DEI and A) play in combating these biases and preventing the spread of misinformation and disinformation.

Finally, we explore the often-overlooked concept of diverse data lineage and its impact on bias amplification in AI systems. Brenna underscores the importance of diverse teams in data processing to catch and correct errors early, particularly in high-stakes fields like healthcare. She also delves into the broader implications on mental health and workplace performance, explaining how stereotypes fueled by inaccurate data can be detrimental. Tune in for an insightful discussion on how accurate data and inclusive practices are central to driving digital transformation and creating a positive, productive work

Pamela Isom:

This podcast is for informational purposes only. Personal views and opinions expressed by our podcast guests are their own and not legal advice, neither health tax, nor professional nor official statements by their organizations. Guest views may not be those of the host views may not be those of the host.

Pamela Isom:

Hello everyone and welcome to AI or Not, the podcast where business leaders from around the globe share wisdom and insights that are needed now to address issues and guide success in your artificial intelligence and digital transformation journey. My name is Pamela Isom, I'm your podcast host and we have a very special guest with us today Brenna Coppola Milner. Brenna is an accomplished account manager. She's a data-driven solutionist. She's an advocate for diversity, equity, inclusion and accessibility. I met her in a business setting, but our relationship goes way, way past that and you'll hear more about that as we're talking today. Brenna, welcome to AI or Not. Thanks so much. You're welcome. Welcome to the show, thanks for being here and let's have you. Start by sharing your career journey, how you got to where you are and what are your interests in AI, data and your interests at large. Tell us more about yourself.

Brenna Coppola:

Yeah, sure thing. Well, thanks so much for having me, pam. I'm really excited to be a part of the discussion and then hopefully just inspire others to think about data in different ways, or even maybe think about a career path that aligns with data and the ever-evolving tech scene. I work in tech sales. I specifically sell a variety of data governance, analytics and AI solutions. I graduated college in DC, so it was a natural realm to enter federal sales, specifically being in the DMV area, and I really have grown to love it, because you play a part in enhancing different government processes and then really optimizing taxpayer dollars through modern technology, which is really cool to see.

Brenna Coppola:

Interestingly though, I graduated with a degree in marketing and I thought I never want to go into sales. I was really more along the lines of creative marketing, branding that was always my thing. But then my final semester of college, I got into a sales class that always had a wait list and my favorite professor shout out to Professor Mark Weber at Catholic University hey, mark, yeah, he's awesome, and he really changed my mind forever and influenced me to go into technology sales. So I started as a business development rep and then worked my way up through the traditional sales trajectory, going from business development to inside sales and now I'm running my own accounts to field sales rep, which is really exciting. But the tech industry in general is so versatile, and so I really encourage folks if they're thinking about breaking into tech to look at entering in a business development role, because it's an easy foot in the door and then it really allows you to transition. If you don't want to go into outside sales, you can transition into other parts of the companies, because once you're in business development, you learn the products, you learn the clientele and you really learn the company culture. So, yeah, the decision to pursue tech really changed my life and I'm definitely passionate about helping others who are interested.

Pamela Isom:

Yeah, I can attest to that, because my experience with you has been pretty exciting. We always have exciting conversations and we don't really have business development conversations, so I guess it's all about strategy, I suppose, but we end up talking just about other things. It leads to business development. Great, our conversation is a little bit different. Honestly, I think that's the way it should be. I'd like to hear more about your point of view on AI and emerging tech and how that has impacted your business now.

Brenna Coppola:

Yeah, sure thing, and I totally agree.

Brenna Coppola:

So anybody nervous about sales I'll add this in as well.

Brenna Coppola:

It's really just all relationship building, it's having conversations, and it makes it really easy to do when you're selling a product or working with clients and use cases that you're passionate about.

Brenna Coppola:

So, with that being said, I really am blessed that my career keeps me plugged into the latest advancements in data and AI. I think that keeps me optimistic about the future of AI, where I know a lot of people. They have a little bit more concerns, but a lot of times I think it is just ignorance and we really do need to democratize data, democratize information about data, information about these technologies, to make people feel a little bit more uncomfortable, or rather just more informed, to be able to make a more informed data-driven opinion. So in tech sales, it doesn't only force me to stay updated with the tech stack that I'm working with and selling, but I get to see firsthand how advanced analytics and AI make a positive impact in the public sector. Plus, I have a chance to chat and learn from industry leaders like yourself and many others that have inspired me and have taught me so much more than I could have ever learned from going through sales, training or even reading articles.

Pamela Isom:

Okay, all right, and I agree with you. I appreciate the compliment, by the way. So I hope to be and I've tried to be a good influence while tending to business, if that makes sense. Yeah, I appreciate the relationship that we have. I would like to talk a little bit about data sharing. So I have two things I want to talk about. So one I was reading this article this morning about digital anxiety and the conversation and what I read was saying something like 94% of business leaders admit to tech anxiety within their organization's senior leadership, and that's part of why we're doing this podcast.

Pamela Isom:

Everybody suffers from anxiety to some extent, but I hope you can share, based on your experiences, how you overcome the digital transformation, the disruption that comes along with it with emerging and advanced technologies like AI. So I know that AI is contributing to some of that anxiety. I know that for some, ai has been a disruptor and for others maybe not, but the show is all about the digital transformation journey, the experiences that we encounter throughout that process, so I found that interesting. One of the challenges, I think, is data sharing, where I think AI can really be valuable. So I'd like to get your perspectives there and then just take it from there. So let's start there. Tell me more.

Brenna Coppola:

Yeah, so, like you said, I think data sharing is monumental in really allaying a lot of these digital anxieties and concerns about where the future of tech and AI is going, and with that I think there's multiple layers. So in working with the public sector and the government specifically, it's important. Take COVID, for example. When COVID was happening, everybody was so anxious. Everybody was waiting for NIAID's next presentation, dr Fauci's next presentation, waiting to consume the data that he was ready to share, so we could really, in my opinion, alleviate a lot of the anxieties that we were having or at least know the best path to remedy the anxieties that we were feeling.

Brenna Coppola:

And so I just think that data sharing is so important because then people are able to make those informed decisions. And then even take AI, for example, building different machine learning models and knowing the data that is going into the model. So when you get that output that you might be so worried to make a decision based off of, if you can go back and look at the data and look at the mathematics that was applied in order to get to that specific outcome, then you can make an informed decision and really this kind of theory of HITL or human in the loop. It's a lot of concerns when people keep humans involved in the AI process with that data sharing element. So again, you can go back, you can look at the data, look at the mathematics and then determine okay, I feel comfortable based on the data set this model was trained off of, or the way this algorithm was written, I feel comfortable making a decision with the results that it produced.

Pamela Isom:

Okay, so then tell me more about the discussion we had earlier about the stethoscope.

Brenna Coppola:

That was super interesting. So I had the pleasure of participating in a trustworthy AI discussion that was led by a federal ethical AI leader and they were addressing numerous common concerns and these digital anxieties regarding AI adoption, and then I think that they really ended up providing reassurance through a simple history lesson about the stethoscope. So they concentrated on the ethical considerations of AI, they balanced its promises and perils, and then they emphasize the fact that as humans, we frequently find ourselves innovating and developing at a pace that outstrips our capacity to actually provide solutions, and I think that's where a lot of people feel that we're at with AI. But it was so neat because in this discussion they drew a parallel between the advent of AI and the introduction of the stethoscope back in 1816. So back in 1816, the stethoscope overwhelmed clinicians with more data than they could process. They were hearing things about our bodies and about our hearts that they didn't even know what to do with. They didn't want to just go ahead and say we hear all these things, they didn't know what to do with them. They're not going to present that information to the patient.

Brenna Coppola:

So that's where the human and loop, the ethical side comes in, and today AI presents us with a similar challenge. But we have, just as we dealt with a stethoscope, a natural knack for blending that human in the loop approach with moral compasses. So this inherent combination has guided us in weighing the risks and the benefits, determining when and how to harness not only the stethoscope's advancements but also those of many other groundbreaking discoveries like AI and again, computers cannot be morally responsible. Ai and again, computers cannot be morally responsible. So it's our responsibility as a human working with computers to determine when it's best to leverage the computer's superhuman processing speeds with our moral and ethic compass. That's pretty cool.

Pamela Isom:

I heard you say a lot, but you know what I take away from my own personal self and something that I also share when I'm coaching and working with clients. But what I hear and all of that is the anxiety that comes along with emerging tech, just like it did with the stethoscope can be put to rest or settled Provides. You can get some settlement to a certain extent by keeping the humans in the loop, yeah, considering the human aspect, by including human perspectives. And when we don't do that, that's when the anxiety becomes elevated. Yeah, that's what I heard you say. So I think that that's really good insights that you're sharing today and I agree with you. I agree with you like a thousand percent.

Brenna Coppola:

Oh, thanks, pam. And yet that discussion was so helpful because it reminded me and I think, everybody else that was taking part, that we have done this before. So while it feels so new, we have accomplished very similar things. I can't even imagine how the introduction of the stethoscope felt to these clinicians and patients back in 1816, but we have overcome it and we have dealt with these similar groundbreaking challenges before.

Pamela Isom:

Yeah, and strategies to keep up with the data coming up with strategies to keep up with the massive amounts of data that they're getting. It's a really good parallel, so I like the example. So we talked about some of the advantages, some of the good things about the digital transformation age and dealing with the anxiety, and you've shared some tips that we can take to help us cope which I think is really good to cope with the disruption. Tell me more about what's concerning, what concerns you the most, and I want to talk about the concerns and then what might we consider to help overcome those concerns?

Brenna Coppola:

Yeah, sure thing. So I think, personally, what I'm most concerned about and it is also a trending topic in data and AI but it's the potential biases in research and development, and so I believe it really is our human and ethical responsibility to democratize and share this research and development and really regulate the processes involved in the R&D to ensure that these innovations are created with diversity, equity, inclusion and accessibility regulations in mind.

Pamela Isom:

Do you think that we have a good understanding of things that we can do to do just that? I mean, do we have a good understanding, or are there things we should really focus on when it comes to ethics, or do you have any insights there and can you give me some examples?

Brenna Coppola:

Yeah for sure. So for example, thinking back to just early stage breast cancer, most early stage breast cancer, research was done on men, particularly white men, because most of the doctors and clinicians were white men. And so because they were testing just on that specific subset of people, subset of data, unintentional discriminations arose when they were creating treatment plans. And so similarly unintentional discriminations are still prevalent in research, development and AI, and a prime example of this issue arose with the introduction of the automatic soap dispenser.

Brenna Coppola:

So users with darker skin tones found it difficult to trigger the dispenser, and so then users with lighter skin didn't encounter that same problem. So the lighter skin users were getting the soap out of the dispenser perfectly fine, and then users with darker skin found that the soap wasn't coming out of the dispenser. So upon deeper investigation it became evident that technical concepts had failed to adequately test and design the dispenser to accommodate all skin types. So the sensor is triggered by a near infrared sensor and that's responsible for activating the soak release, and that sensor is relied on the reflection of light from users' hands. So lighter skin tones naturally reflect more light, effortlessly activating the sensor, and then users with darker skin tones their skin absorbs more light, so it frequently leads to an inadequate reflection in sensor activation. So that really highlights a necessity for stronger sensors and, more importantly, diversity, equity, inclusion and accessibility in mind during the R&D phases before rolling it out to production, in order to address the disparity.

Pamela Isom:

Yeah, that's a really good example. I didn't understand the rationale behind why that was a problem, but I can tell you that I experienced that and I still experience that today. I experienced that and I also experienced the facial recognition issues. My husband experiences the facial recognition issues more so than me and he's lighter complexion than me. It's so bizarre. So we go to the airport it usually happens at the airport we go through the line and then we have this access, whatever it's called and so we go through that one for the facial recognition and I usually can get through with no problem. But I always get random checked. I'm always flagged for random check, but my husband every time it never recognizes him and he's in the system and everything. One day he got so frustrated he's like I don't even want to use this, I'm not using this. And I talked to them and said you need to do a better job or I want a refund because these things cost a little extra to help you accelerate. And then I questioned why am I always random checked?

Brenna Coppola:

I can't even imagine the level of frustration that you both are experiencing because, like you said, you're actually paying a premium for this, which is supposed to be a benefit, at the airport, to end up with more frustrations, paying a premium for this, which is supposed to be a benefit, at the airport, to end up with more frustrations. And it leads you to think okay, when they were building this sensor technology which leverages artificial intelligence, were they testing and prototyping on a diverse set of individuals?

Pamela Isom:

Yeah, yeah, and I don't want to call out a particular vendor, because there's many of them that provide this capability, but in my case, we have different airports and we have different capabilities at the different airports and so they need to look at this. The government needs to look at an example of how that amplifies. So, because what happens is we don't think that something like that really matters. There doesn't need to be that diversity, because what does it matter in the workplace? So I just want to walk through an example of how. The example with the soap Right. So let's talk. I'm just going to walk through you, tell me what you think about this and it's OK to say not a good example, but I think it's a good example. So let's talk about data lineage. So let's use the example with the soap.

Pamela Isom:

So here's the rumor People of color don't like to wash their hands. It started right there, right, because the soap issue. So now someone sees that the rumor gets started People of color don't like to wash their hands, that's data. Advertisements then come about and they avoid hand-washing materials like soap. They avoid sharing that with certain zip codes and then the prices then start to increase unnecessarily for those products in certain zip codes yeah, talking about data lineage and then the workplace then ultimately starts to be discriminatory because of some bad data and some bad decision making, because it's something that started by a soap example, but a real example, yeah, so I wanted to show how, because sometimes people don't understand, like so what does this have to do with the workplace? It has everything to do with the workplace, because the information just went from a situation where the soap dispenser is not working properly to misinformation, to disinformation, and it carries into the workplace with decision-making based on bad data.

Brenna Coppola:

Was that a good example? I think that was a perfect example and it really does show, like you said, the data lineage and how one person, what people might think of as a minor mishap, is really a massive mishap because of the data lineage and every other consequence that it has after that and now we can see how data is amplified and how bias gets carried forward through the data into the algorithms.

Pamela Isom:

Right, yeah, okay, that's what I was trying to point out.

Brenna Coppola:

That is a perfect example and that's why, at every step, it's important to have a diverse group of people working to process the data, so like following the lineage path. When it gets to the next step again, if you only have the same subset of people evaluating that data, there is a high probability that they might not recognize anything to be wrong with it Because, again, in their personal experience, everything is going fine. So it really, I think, highlights, like you're saying, the need for DEI and A within the entire data lineage process, because if it's not caught at the first step, hopefully it can be caught at the second, third, again, before trickling down all the way.

Pamela Isom:

All right, thank you, because I'm trying to help businesses understand why this is so important, so you just helped me with that, so I appreciate that. So now I just want to know do you have any messages or any additional conversations that you want to discuss today, before we get into final messages for those that are listening to this podcast? And also, is there anything that you just want to discuss with me, anything else?

Brenna Coppola:

No, I think that we had a great discussion today. Yeah, I'm really excited to get the feedback from the listeners and hear how else we can shed light to these topics.

Pamela Isom:

Well, I do remember that you had mentioned something about AI in healthcare. Yeah, that there are healthcare implications. Is there anything else you want to add to that? Anything about AI Did?

Brenna Coppola:

I cover it enough. Yeah, I think that we did.

Pamela Isom:

Yeah, okay, so are there last minute parting words for the listeners.

Brenna Coppola:

Yeah, so thanks so much. It has been such a pleasure to have this conversation today and I really think that, again, optimism and positivity is crucial if and when we want to achieve positive outcomes. So I really encourage listeners to remain optimistic about the potential of AI, to continue researching, to continue staying informed about its developments and, most importantly, to uphold our ethical responsibilities. Again, it's vital to ensure diverse, equitable, inclusive and accessible considerations in innovation. By doing so, we can navigate the evolving landscape of technology with integrity and really truly ensure that AI serves humanity for the better.

Pamela Isom:

Getting to know the value of AI, understanding how and not just AI, but the whole data, analytics, spanned analytics at large and then understanding how that adds value to what we're doing. And take a bigger look at the AI and the technology solutions from a ethical and integrity perspective to ensure that we are addressing human rights.

Brenna Coppola:

Yep, 100%, and I think that the topic of data lineage that you brought up is an example, and I'm going to start using that in my own daily conversations because I think it's so important to see that, if this is not mitigated, how far it could go and what implications it could ultimately have.

Pamela Isom:

Yes, like a bad rumor, yeah, and by the time the rumor gets to the end, except for it has more implications, because it now has implications with health care, because the thing that I was thinking about is even from a health care perspective, with that example. So now, with the soap dispensers not being accessible, what do we do? So you can see how that even exacerbates the spreading of germs. And that's a minor, a minor example, but a big deal in the day and time of a pandemic, inconvenience is just not worth it. It's not worth it. And for businesses, boardrooms, businesses, for all of them, these types of things that we may think are small, yeah, well, it's not that important, it's just diversity, yeah it's costly, it's super costly.

Brenna Coppola:

And then I think even another layer that we didn't really touch on is that, like you said so, it's like a bad rumor being spread and that affects people's mental health and well-being because they're now feeling stereotyped and targeted from the misinformation, and rightfully so. People are going to be frustrated or maybe emotional by that, and that carries on to not being able to perform your best work in the workplace, not being able to maybe be in the best spirits or bring your best self to work or to your personal life, because you're facing the consequences of a stereotype that started, ultimately, with bad data.

Pamela Isom:

Exactly. This has been a fascinating discussion and enlightening, so I really appreciate you taking the time to participate and discuss this topic with me and join me on this broadcast, because this is the first week of recordings, so you're one of the first guests, and so I think that the information is so insightful and I hope it will be very enlightening to those that are listening, because we have to understand why this is so important. Why are we addressing this when we're talking about the digital transformation journeys? Why are we addressing this? Because this is right at the heart of digital transformation and that whole disruption that we've got to deal with. So I appreciate you being here, I appreciate you taking time to talk to me today, and I'm wishing the best for you and everything that you're doing going forward.

Brenna Coppola:

Oh, thanks Pam. Likewise it has been a pleasure. I'm so excited.