Join us for an insightful LinkedIn Live session with Alec Crawford, an AI and tech integration expert. Alec will delve into the transformative power of AI in today's and tomorrow's industries.
Learn about effective AI risk management strategies, the evolving landscape of AI, and its potential applications. Discover what the next decade holds for AI-driven industry transformation and how AI analytics tools can lead to superior outcomes.
Gain insights into the changing regulatory landscape in response to AI, and develop essential leadership skills for managing tech teams. Explore the unique challenges and innovative strategies in AI implementation for startups and established firms alike.
This session is an invaluable opportunity to deepen your understanding of AI's role in business and leadership. Stay ahead in the ever-evolving world of AI and tech innovation.
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Welcome to Boomer Living Broadcast, a hub for exploring the dynamic intersection of aging, artificial intelligence, and technological evolution. I'm Hanh Brown, and with AI50, in collaboration with Microsoft Startup, Our goal is to make AI more accessible and beneficial for all. Leveraging the power of Azure, our initiative is centered on pioneering
innovations that ensure safety, respect privacy, and remain affordable. So, we're creating an AI environment specifically designed to support older adults and address the unique needs of the aging demographic. However, our journey is not just about technological aspects, It's fundamentally about people who are dedicated to developing AI solutions that are
not only secure and easy to use, but also genuinely improve the day to day lives of our senior community members. So every week we engage in meaningful dialogues with leading experts. and groundbreaking innovators delving into the ways AI is revolutionizing the realm of aging and senior care. So whether you're a healthcare professional, caregiver, senior
living developer, operator, or someone interested in the confluence of aging, health, and technological innovation, well this platform is your go to resource for insights, experiences, and participating in a compassionate movement. So join us. And this journey towards a better connected and empathetic world in the realm of the aging population.
So let's get started. So today's topic is sailing the AI horizon, where we will explore the pivotal aspects of artificial intelligence. We'll delve into AI risk management. Technological progress, the future landscape of AI, advancements in the next decade, AI around investments, leveraging AI tools and success, and the impact on regulatory practices,
leadership in AI driven environments, and business challenges in the AI context, and the importance of continuous learning in this rapidly evolving field. Ciao. Our guest is Alec Crawford, he's a distinguished AI author, speaker, and the CEO of Artificial Intelligence Risk, focusing on cybersecurity and AI centric risk.
With a decade at Lord Abbott, and experience at the major firms like Ziff Brothers Investments and Goldman Sachs. Alex's expertise spans risk management and suitable, or sustainable, investments. He's also an advisor at Ecolomix and a partner at Our Peak Management. So, known for his contributions in the AI community and his insightful blog, Alec brings a wealth of knowledge
and experience to today's discussion. So Alec, welcome to the show.
Thank you, Hanh. It's so great to be here. Thank you for having me.
Yeah, well, thank you. Thank you for being here, sharing your journey, your experience with AI and shedding light what's on the horizon. So could you share with us an interesting fact or some detail about yourself? Professionally or personally that you'd like the audience to know?
Sure. Yeah. One, one fun fact, um, is, uh, is I went to Harvard as an undergrad and, uh, I was taking a lot of courses in computer science and electrical engineering and math. And I got a phone call literally two weeks before I was going to graduate. And it was the registrar.
And they said, well, You've got enough credits. You could, you get to choose what your diploma is going to say. You can choose applied math or electrical engineering or computer science. Wow. And it was the first year that they, that Harvard allowed you to choose computer science on your diploma.
So I picked that. So I was literally the first person from Harvard to graduate with a degree in computer science. So that was kind of fun.
Yeah. Well, I'm honored to have you on a guest as a guest today. Well, thank you. All right. Well, let's, let's start by exploring the evolution of AI in the industry. Now, how have you seen the landscape of your industry evolve with technological advancement?
Yeah, I think that's a, that's a great question. And I think if you, we need to start back even before AI and think about just data and data science. So And when thinking people think about investing who are professional investors, and they think back to the eighties and where was all the data coming from, what really came on the scene there was the
Bloomberg terminal and really named after former New York mayor, Mike Bloomberg. Uh, and that really reshaped the industry in terms of. Gaining information required for investing into the hands of, of, uh, the investors. Uh, and, and now it's happening. So really democratizing that to some degree, right? And, and that to some degree
also is what AI is doing. It's, it's really democratizing, uh, a lot of things. In other words. Before, if you thought, oh wow, I could never write, uh, you know, a 10 page paper. Well, now with the help of ChatGPT or BARD, it's not that hard to do. Uh, so that's a great example
of, uh, Of democratization. Now of course that's the power of AI. You've also got the peril of AI. We've constantly got people talking about how AI can be used to hack and exploit and uh, do better phishing emails and things like that. So obviously we're all going to have to be a lot more careful over the next few years in terms of um, scrutiny
of things and protecting ourselves from Uh, cyber attacks and phishing emails and things along those lines.
Mm hmm. I agree. Just like any. Power comes with responsibility and proceed with caution, but also recognize it's, it, it acts more like an augmentation to your day-to-day routines, you know, simplifying tasks and enhancing the overall experience more like a companion.
So if you look at it from that perspective, it's. It's transformative. You know, it's like having a digital twin.
Exactly. Exactly. I think what's interesting now is, uh, uh, different companies are starting to build it into their products. So it's almost like in some cases you can't avoid it. So I noticed when I was typing an email the other day, But now it's trying to complete my sentences in the email, which
wasn't happening even two weeks ago. Right? So it's, it's at a state now where it's not like you have to ask for it. It's starting to show up whether you want it to or not.
Yeah. And you know what, as business owners, here's the thing. You might want to choose to be a part of the conversation and shape its evolution instead of staying back and then wonder, you know, this just happened to me. And also consumers are very smart and they're going to expect that, right? They're going to expect more customized
personalization, more targeted cultivation for what their needs are. So if we're not on board, the customers will be.
That's a really great point. What I'd say, uh, is that, well, for many. Companies and people, AI is experimental. It will become foundational for business over the next five years. And as a business owner, if you're not using AI five years from now. You're probably pretty far behind your competitors. Uh, so really is it's actually creating,
uh, I think existential risks for businesses, both those who aren't going to use it and for certain types of businesses or roles where AI really could take over. So it's going to be super important to manage those risks, not just as business owners or members of society, but also. In terms of the government and regulators and other business groups, um, and also to be ethical about it, there's
a group called the It's a global ethical AI Institute, for example, that focuses on that, um, around the world. And their point is, you know, ethics are different in different places. You can't just assume that, uh, what one might consider ethical in the United States, for example, applies everywhere in the world.
Well, I don't know about that. I have a different position. How I measure my own ethics is like this. If I create a prompt and automation, a directive of what I want AI to do. I always look at the output, does this impose anything negative on your family, your children? That's very clear to me. If there's any hesitation for me
to answer that, then don't do it. You know, it's about humanity. It's about enhancing life. So anyhow, I think we're on the same page, but, but there's a lot of complexities who come to that determination. So I understand. Now, considering your role in managing AI risk, let's delve into the balance between potential and risk.
So now, how do you view the balance between AI's potential and the associated risk? What do you do?
Yeah, that's a great question. I think, um, a good way to think about it, um, is to think about specific case uses. It's very tough to say, Oh, okay, how are we going to balance, uh, risk and potential across everything in society? But let's think about that in investing, which I think is a great example. So, so now, for example, you can literally go into one of the chat bots and say,
you know, one of the 10 largest stocks in the S and P 500 and ask and answer all kinds of interesting investment questions. So that is interesting and that should help investors. The problem is obviously ChatGPT doesn't know how to invest. So don't ask it for advice, right? Don't say what stock should I buy today or should I buy bonds?
It's not programmed to do that. Uh, and what will probably, and if it does give you an answer, it's probably not going to be the right answer. Um, but there are obviously. Uh, AI tools that are already out there that people are using. Uh, so for example, robo advisors have become pretty popular at a lot of the large asset management firms.
Uh, honestly, like I don't think they're that great, uh, because they're kind of one size fits all and everybody has their own risk tolerance and, uh, Desire for different levels of income out of the, you know, how much they want to spend, how much they want to lead to their kids, things like that. Um, and I'm also concerned about, you know, the potential
for fraud, especially for. Um, people who may not be super computer savvy and if everything's electronic, meaning you've got a robo advisor and you're just going back and forth to that, like, I think that it does create, um, some risk. Uh, so, so what I actually advise maybe counterintuitive to some people, which is, uh, I think people should reduce
risk by actually having their own human financial advisor, which sounds like, Ooh, my own person that must be expensive. No. Not that expensive. Not that expensive. Uh, and well worth it to protect you from someone trying to steal your assets or hack you or whatever.
Now, let's hone in a more about that, your own AI assistant or large language model. I see that as huge because, you know, often people think, well, it's so expensive to have an AI consultant, an AI assistant and so forth. But you know what? Not at all, because in order to reap the full benefits of
AI, it's very personalized. Don't subscribe to anything that's generic because it rep. Your AI should represent your voice, your brand, your clients needs, and all the personalization that represents you over, over the years. And not to mention the privacy and the safety, so you want to encompass that within your own
ecosystem, your foundation model. Right. Can you talk to that?
Yeah, absolutely. No, I think, I think that's a very good point. You know, when you, when they released ChatGPT and people started using it in earnest last year, it was pretty generic, right? You asked and answered questions, didn't really know anything about you. Maybe you'll remember the prior.
The prior question, something like that, uh, now, uh, it's, it's become pretty straightforward. You may need a little help, but pretty straightforward to load in some of your own information, uh, in order to ask a question. So a good example might be. Uh, I want to summarize a 10 page document that I have here and I
don't want to read the whole thing. It can do that. Uh, what I would caution is that whenever you do that, that information effectively becomes public. You know, it's not like it's going on, you know, being printed on the internet. Uh, but information once it's put into most models, whether it's ChatGPT or BARD or something else is accessible to those
companies in order to help train the model and is potentially accessible to some third party somehow on the Internet. So you do need to be careful, uh, especially with personally identifiable information. You do not want to put your. You can put your name and address and social security number and your birth date out there and ChatGPT or
bad things will happen at some point.
Yeah. And my take on is the first iteration, is it GPT 35 November of last year? It was pretty good, but nowhere near compared to 4. And then recently, about a week ago from the Dev updates, 4 Turbo is amazing. So it's evolving. And I think what's most important is we have to, at least in my mind, how
I, the approach that I take is that all of this is to enhance your work. It isn't to replace your expertise because it still requires you as a prompter to know how to direct what you want it to do, right? And again, you may not get the output that you want right away. So then it takes emotional intelligence, creativity.
And knowing how to prompt to get to the output that you're seeking. So how I look at it is it's an evolution of change and you need to adapt to that, whether it's private to your own data or something that you care to leave it public, but I think it's very important that we look at it as an enhancement, as a co pilot, a companion. Okay.
Now, also adding to the fact of the privacy and not letting your information go out, but there are enterprise platforms that it's actually yours and what's yours is yours and it's not scanned. It's not scraped. It cannot be. You know what I'm saying? So can you talk to that?
Yeah, absolutely. So, uh, a company or a person can set that up. It is relatively complex. So, so most people who are just pulling up a web browser and type typing things in. Uh, that effectively is public. But, uh, for, uh, a relatively low fee, you can get an enterprise license and access their programming
interface, and then that data does not get stored by, um, by OpenAI. So that, that obviously could be, uh, pretty helpful. The, the other, um, thing which is pretty cool, um, is that there are a lot of plugins for these different large language models. So, for example, one of the things that's now offered, Is the ability
to plug in Expedia to ChatGPT. So when you're planning your next trip, you can use ChatGPT as your personal assistant. You know, I want to fly next week to Dallas. I want to stay at a hotel. I can link in with Expedia and find all that information for you. Which before, it couldn't do because
it didn't have access to the internet. It didn't have access to travel schedules, for example.
Mm hmm. Very true. So now, what's your take on how should regulatory bodies adapt to the integration of AI in various industries? What's your take on that?
Yeah, I think, well, first of all, I think, um, if you take a step back and think about, um, you know, where, uh, where are there regulations, you know, Europe, um, has really been at the forefront there. Uh, and they've passed, uh, passed laws, uh, about regulating AI, and they took a risk based approach. So, the way to think about that is,
um, if something's very low risk, like I'm working with AI to figure out what color to paint my walls, there's pretty much no constraints on it. Uh, if there's something is high risk, like something to do with medical care, Then obviously there's a lot of risk management around that and, you know, making sure that the AI is accurate, or maybe it might even require human
review before release to a customer, for example, and that the very highest level of risk, um, they have bands. the use of AI for certain things. Uh, one of them is facial recognition in public. For example, they don't want AI tracking wherever people are going in Europe, for example. Uh, we don't have that
yet in the U S right. Um, Biden did sign the executive order. Um, a lot of that is still preliminary. He directed the national institute of science and technology to formulate. Uh, rules which later will be adopted. So right now we don't really have that much of a framework, uh, in terms of rules and regulations in the U. S.
What has happened, especially, uh, within, uh, already heavily regulated industries such as banking and health care is the regulators of those areas have said. Look, just because it's AI doesn't mean you get to skip all the existing rules, right? So, uh, for example, HIPAA still applies, you know, and healthcare, whether or not you're talking about AI or not AI.
And the same thing goes for finance. You still need to protect customer, uh, AI or not. So, so that's important. Uh, and some, uh, companies and institutions. Kind of forgot about that. So we say and and got in trouble with their regulators are fine by the regulators So people are
starting to pay attention to that more What what I expect to see? going forward is Is an expanded pretty general framework around AI Perhaps similar to what they're doing in Europe, so it's not going to be prescriptive for each industry, for example, but it's going to require, um, uh, a fair amount of reporting, especially reporting by companies that are running large,
uh, AI systems with many, many users. And that's, that's already part of Biden's executive order. And I think that's going to get expanded over time.
You know, back to the point that you mentioned how, just because it's AI, it doesn't replace HIPAA, it doesn't replace regulatory for investments or banking, and what it does is It's perhaps make it more even concise and even suggest better ways to protect your clients. You see? So it doesn't replace all those regulations.
So we have to think of it as in terms of enhancement, augmentation, and not to replace your expertise. And for those that think that, you know, that you can get away with that, I don't think so.
Yeah, I, I agree with that. I mean, the, the way I think about it is, uh, and they're, they're kind of. Two extreme paths, like, neither of which is going to happen, but just as an example. One path is years from now. Everybody gets their own AI co pilot, right? So in your job, the parts that you
really didn't like that much, guess what? The AI is doing that for you, right? It's fixing the grammatical errors in your emails. Uh, it's deleting the spam. It's, uh, organizing the financial records for quarter end for you. Things like that. And you're like, this is great. I can do what I love to do, and I can
be more creative because the co pilot is taking care of this stuff that. I don't really like doing, uh, everybody becomes more productive and the economy grows even faster because everybody's more productive in the economy. The flip side of that is, uh, which I really hope doesn't happen. And, uh, I'm certainly working personally towards making sure it doesn't happen.
Lots of people lose their jobs to AI, right? Uh, we don't need that person anymore. We're just going to have AI do it. Uh, and then we've got high unemployment and unhappy people five years from now. I don't think that's what's going to happen. You have to know that that's a possibility in order to avoid it.
So that's, that's the, the future that, that, that we should actively work against.
And you know what? I look at it is whether you are an employee or an entrepreneur, but look at it even from your day to day. It doesn't matter where you stand with employment. It's really about you being more productive with less time and it's an enhancer and like you said, I'm trying to think of a word while you were speaking
and now it doesn't come to me right now. You have to look at it as if it's like you said, copilot, companion, an enhancer, making you more productive. There was one word that was ringing a bell and I'll come back to it when it comes to me again.
I'll tell you where it's been amazingly helpful, and that is for people, uh, who program computers, software developers. Now that's obviously my background, and, uh, this summer I decided, oh, you know, I'm going to write a demo code for my, you know, new company. And of course, I haven't programmed in a while, and I didn't even know
Python, but I started to learn Python. And, uh, I got some code. You could ask ChatGPT questions, it would give you snippets of code. Uh, but also, um, very sophisticated questions about that. Like, what's the scope of this variable? Or how do I use this SQL command? Things like that. It's pretty amazing.
Yeah, it shows that it's got depth. Exactly, because before I'd go ask my boss that question, right? Or maybe you look at, you know, there's a popular website called Stack Overflow for programmers. I was getting my questions answered in 10 seconds. It was incredible. I probably ended up developing that
software three times faster than without ChatGPT, which is pretty amazing if you think about it.
Yeah. Yeah. I think the word I was trying to look back is it allows you to get back to the soul of your work. Yeah. What you enjoy doing what you were meant to do instead of answering emails or even locating where was this email? Where's the chain of this email?
Where do we stand on this? So I guess it's really the heart of it is to for you to do what you were meant to do to enjoy it and for People who are afraid of losing their job rightfully so guess what you have the same tool get back to doing what you love And perhaps, you know, it's time, again, here's the other thing I want to add. We can just hit reset on what
we know about technology, right? Because we now are on the same plane. We all have the same tool. I mean, talk about democratizing. Anybody in the whole world will. I don't know. Is there a place in the world that doesn't have ChatGPT? Is it?
Good question. Good question? If don't have the internet. You don't have it. Certainly. But, other than that.
Well, my point is we're all on the same plane. We now have the equal opportunity of somebody, you know, 500 fortune, 500 companies, whether you're five. People start up, we have the same tool. So I think it's great that we have that opportunity, that empowerment, that we all can hit a reset and start innovating, recognizing, recognizing
the precaution, of course, you know?
Yeah, absolutely. Sounds great.
Yeah. So, now, how will AI transform your industry in the next few decades and how do you plan to integrate like traditional data with AI driven insights? What's your take?
Yeah. Well, I think, uh, we're, we're really going to see, you know, radical change. in the investing industry, right? And it's not just about AI. Uh, AI is going to be one of the shaping forces. So let's think about the shaping forces of investing, right? What, what are some of the big things
we've seen over the last 20 years? Well, one is the rise of passive investing, right? So, uh, 50 years ago, you bought stocks in your portfolio. If you're lucky enough to have one, uh, now you go out and buy the S and P 500 index in your 401k plan, right? That's passive investing, right? Because you're not actively picking
the individual stocks, you're basically buying The large cap stocks in the market. So I think that trends will continue. Now, how is AI going to influence that? Uh, I, I think it's, it's going to make, uh, institutional investing like even harder, meaning your, your opportunity to add value versus past investing is going to be tough, right? And, um, you're really going to have
to be a specialist going forward to, to be able to get people to invest in your non generic, uh, product. And there's something that institutional investors called core satellite. Now what's that? Core is I buy an index, I'm buying the S and P 500 or the Bloomberg aggregate bond index. And what's satellite?
Satellite is something unique and interesting. So, for example, I could buy the S& P 500 and I could buy an AI focused ETF, right? That's very different than the S& P 500 because I might believe that AI is going to do great over the next five years. So that's one example. Or I could buy the aggregate bond index and then buy a specialized Private credit,
high yield funds, for example, which has nothing, which has very little to do with, you know, the bond aggregate. And I think that's really the direction we're going to see investors moving. Uh, and I've also seen some predictions that individual investors who right now own mostly stocks and bonds. Uh, that 10 years from now, we'll have something like between 10 and
30 percent of their assets in what are called alternative investments. So that might be private credit or private equity or hedge funds, or maybe some of these other specialized vehicles that we've been talking about. So that's going to be, you know, pretty big change for the industry as well.
So let's hone in a little bit. So how can AI and analytics be leveraged with what you just talk about?
Yeah. So, um, one way that one can use AI to leverage this is to figure out, um, is to take lots of potential investments and use AI to figure out what's the, what's the optimal portfolio for me, given my risk tolerance, like, am I willing to take lots of risk or I don't want to take lots of risk? How much money I need to
draw out of that each year. Right. Let's say I'm retired and I need to have certain payments I need to make. And how much money you might want to have left, uh, you know, when you're a hundred years old or something like that, right? Uh, that's something that I think, uh, a specialized AI program could be really good at.
Uh, right now, obviously you can talk to your advisor, uh, your, your, your human financial advisor about that. But this is a very complex problem that. Needs to be solved by a combination in the future of AI. And analytics. Uh, and, and this is what we were talking about earlier about robo advisors. It is not, those are not solving
this problem in my opinion. It's too generic.
It's generic and AI is all about personalization. So, yeah.
Mm hmm. All right, great. So let's shift to the human element of leadership. Okay. So you've led successful teams. So what do you think the qualities are that are important in leadership in the industry, let's say investment?
Yeah, that's a great question. I mean, I think there's some qualities of leadership, which are important really, no matter what you're doing. And there are some that are more specific to, uh, investing. Uh, I think one of the important qualities is to be transparent with your team, right? If someone's not doing a good
job and you never tell them, how could they possibly do any better? So you have a situation where someone wants to be nice as a manager. Uh, you're not being nice by not telling someone that they didn't do a good job on a project, right? That just makes it worse for everybody. Um, I found that, um, another important thing is to have a clear
vision and plan and make sure you repeat that, uh, over time. If people have no idea why they're working on something and why it's important. To you and to the company, it's much tougher for them to do their job. That's also pretty important. Uh, the third thing that's important, I feel is individual connections with each person you're working with.
It's pretty easy to, as a manager. To feel like you're very busy and you don't have time for individuals on your team. Uh, I think it's really important to have one on one meetings with the members of your team. Uh, I do it, uh, every week, uh, with people on my team. But there are plenty of people
that don't do that, right? Um, and then, um, I think, uh, I think the other, the other thing that I focus on a lot is I'm a lifelong learner. Mm, yeah. And If, if all you're doing is doing your, you're, you're doing your job, you know, every day, you know, working 8, 10 hours a day and nothing else, eventually you're gonna have a problem.
So, uh, I, I took time off to learn things, go to conferences, uh, read books, try to learn about new topics and for my team. Each year, we come up with an individualized learning plan for each person. What conferences are they going to go to? What books are they going to read? Uh, what papers are they going to read?
What new skills are they going to learn? Are they going to learn how to program? Whatever it is. Uh, that we all, that we both agreed on. And, uh, monitored throughout the year, and people got, um, ranked on that. And, uh, and as well, um, we did team learning. And we agreed on what we would learn about.
So, for example, uh, a couple years ago, Uh, my team decided they really wanted to learn more about strategic thinking, right? So we ended up reading some Harbor Business School's case studies and some of their books and blocked out a couple hours to talk about what we learned. It was amazing, you know, and they had, it was, it was a great way
of bringing the team together. And stepping outside the day to day to really, uh, learn a lot more and enhance everyone's career in the long term.
Mm hmm. Now, when you talk about lifelong learning, boy, I love that topic because, all right, what's your take in learning AI, adapting and integrating it to your day to day life and also your professional life? But isn't that the key trait is to be a lifelong learner? Because how I adapt that attitude
or even my own learning journey with AI is that it doesn't necessarily work the way how you want it. And it's easy to say, well, my business is, let's say, hypothetically doing well. I don't need it because I got to go through a learning curve, right? And, you may convince yourself that with all these negatives around it, I don't want to deal with that.
I don't want to put my data out there. I mean, there's so many things that if you start thinking that it can go wrong, what that does is it justifies that you don't need to do it. That's not lifelong learning. That's a fixed mindset. So when you talk about lifelong learning, boy, it's very crucial in adapting learning AI, whether
it's personal or professional.
Yeah. Great point. I may think. I think lifelong learning about AI is, it's going to be so critical for people's lives and their careers over the next few years. Imagine two years from now, you're interviewing someone to work for you and one person has never used
any AI tools and the other one has. Which one are you going to hire? Exactly. Right? Yeah. Um, and what's interesting. Is that, um, there are obviously a lot of very popular AI tools, ChatGPT, DALLE which creates images, things like that, that everybody's aware of.
There are hundreds of these things. And, uh, there's a, there's a fun website called there's an AI for that. And if you go there and you type in things like resume or whatever, it will pop up a list of the AI tools that will help you with whatever you're looking for, whether it's updating your resume, tuning your LinkedIn profile, taking a trip somewhere, whatever it is.
There's a specialized AI for that, which is pretty cool.
Yeah. And you know what, when let's say I'm interviewing now and forward. One of the very first few questions would be, what AI technology have you used to potentially save my business some money or enhance my productivity? I mean, right away, I think business should be thinking in those terms when hiring.
What AI have you used or create or learn or, you know, however you want to scope it. That's going to help save my business time and money and enhance the customer. That sounds great. Yeah. And if you say, well, I've only heard about it. There's so many bad things about
it, so I just didn't want to learn.
Yeah. Yeah. That's, that would not be a great attitude. Yeah. Yeah. Definitely want people are going to learn about it. And, and look, there's literally by the time, uh, I write my blog
about, uh, anything to do with AI and the editor finishes with it. It's already out of date. I mean, that's how fast things are moving.
Yeah. Yeah. So leadership traits are pivotal. Equally important is how innovation shapes strategy. So now your career is a senior care mark by innovative strategies. So can you share some impactful examples?
Yeah. Innovation is so critical. And I think that, um, so there are different kinds of innovation. Uh, I'll talk a little bit about product innovation first, right? So what's interesting, especially in financial products, is that, uh, many of them come and go over time. I mean, think about this, uh, you know,
the passive investment strategy didn't exist until John Bogle invented it, you know, more than 50 years ago, right? And now it's taking over to the point where it's almost half of. Act of a large cap, you know, equity investments in the U. S. I mean, incredible, right? Um, so I think that, uh, where
product innovation and investments is going to be important is in alternative investments, right? I mean, I think that innovation around kind of equity funds and, uh, public fixed income. Sure, there's stuff that can happen there. But I think the real innovation is going to be about alternatives to that and figuring out ways.
So how do I generate money? That's not necessarily only correlated with stocks and bonds. So maybe that's private securities. Uh, maybe that's better access to real estate investments, uh, where I think we're going to see a lot of volatility over the next few years as, Uh, as we all know, a lot of these office buildings, uh, people are not,
maybe not going to renew their leases, uh, for their giant office space. Um, and all kinds of interesting things, uh, around that and interesting, innovative, uh, lending products and borrowing products and things like that. Great example, uh, I heard was there's a company now that wants to give you a credit card that you can use with a really low interest rate.
And it's backed by the equity in your home, for example. So instead of playing some crazy, you know, 20 percent interest rate on your credit card, it's seven or something like that. So I thought that was again, unique product, pretty interesting. Um, so that's product innovation. I think there's also a
management innovation, right? You look at a lot of these different companies, uh, many of whom are, are wildly successful. And you look at their management style and it's quite different. And I love the story about, um, Jeff Bezos at Amazon in the early days where he's in a room, he's getting a PowerPoint presentation.
He's literally about to pass out, you know, from the boredom of the PowerPoint presentation. And, uh, and he asked the person speaking, it's like, well, where are the, you know, the, the things you're saying to go with the slides, well, where's that? Can I read that? And he goes, well, those are my speaker notes here.
He goes, I just want the speaker notes. So that's how they ended up going to a model where there are no slides. Everybody gets the four page, you know, memo. They start every meeting with 20 minutes. So everybody can read the memo and then they talk about it and make a decision. So cool. Uh, would that work in every company?
Maybe not, but, uh, interesting management. Uh, innovation as an example.
So now can you share a novel approach that changed the trajectory of one of your projects?
Yeah, uh, that's a great question. So um, so I, one of the, one of the projects I worked on in one of my prior firms was a large portfolio and risk management, uh, platform. So this would be something used by the risk managers and the portfolio managers. And, uh, and I was asked to be the executive sponsor for that, uh, for that project.
And it was pretty standard, you know, project most of the way. It might look like a lot of these other tools, um, but one of the things that we Added to it, which was unique is, uh, if you look at, at, at, uh, investment data, almost anywhere, whether it's on the internet or Bloomberg or some other tool is it's their data, right? You're looking at it.
It's not much you can change about that. We added features for us to put our own data in there or individuals to put their own data. So it might be a note about a bond or a portfolio or whatever. And it could even be an analytic. So in other words, let's say you wanted to rank things or whatever you wanted. So that ended up being, you know, people
ended up just loving that feature, being able to like not just look at the data from outside, but look at their own, uh, data and run analysis on it. So that was, uh, that was pretty cool.
Mm hmm. Mm hmm. So, let's talk about client relationship management and communication. Now, dealing with skepticism is part of client relations, so how do you navigate these challenges?
Yeah, great, great question. So um, there are really two kinds of clients, right? Clients that you already have and clients that you hope to have in the future, right? So clients that you already have already believe in you. And, uh, what you're hoping is they perhaps buy a new or different
or better product from you. But since they already believe in you, that, that shouldn't be that hard. In other words, they've gotten over their skepticism to some degree. Uh, it's the clients that you don't have that obviously are ready that may be skeptical. And. I think a lot of that, a lot of
what you need to do is, uh, develop trust between you and the client. And, uh, so this is basically the opposite of being a used car salesman. So I'll tell you a story. So, uh, I went to buy a used car and I think that, uh, the salesman probably changed his story about certain things like five times. Like so for example, uh, well,
this is a pre owned used certified car, so, so it couldn't possibly have been in an accident. Oh, oh, but there's an accident report. Oh, I was wrong about that. Yeah, it's allowed to be in one accident and then on and on and on, it was just incredible. It did not develop a sense of trust between the salesperson and
myself kind of changing your story. So I think, um, I think developing that sense of trust, um, first of all, it's meetings and consistency and things like that, but it's also doing what you say you're going to do and also demonstrating that you did that in the past. And Interesting with interesting with financial products, you could demonstrate that through
the performance record, right? And the risk management record, right? So if you go back and say, look, we've managed this very conservatively and you look at the last downturn and you outperformed all your peers. Well, that's you're demonstrating that you managed it pretty conservatively. If you say that, but somehow you were the worst performer in the last downturn,
well, the facts just don't add up, right? So, being transparent, developing trust.
And you know, in the digital world, and now AI transformational world, I feel like that's another opportunity for folks to learn about you, your work, your track record, even before they even talk to you, right? So I think social media has opened up. The opportunity to gain trust even before you even talk, what do you think?
That is such a great observation, uh, and, and so I've met so many people, including you Han. Yeah, I know. Uh, online or through social media that you just hit it off and everything's great, you know, and other people are like, oh, okay, maybe talk to them once and don't hit it off or whatever. But it's really has.
You know, opened up the world to people and, uh, what's funny is, you know, there are people I know that are still not on social media and very intentionally and, and, you know, that's their choice, obviously, but sometimes I just scratch my head and go, wow, why would you exclude yourself from being able to engage with people from all over the world about what you feel is important to yourself?
Yeah. You know, on that topic. You know, growing up, I actually forbid my children, especially in the adolescent years, from using social media. You know, when they were, you know, middle school, elementary, and then high school is a different story. But my point is, there needs to be some guardrail as a parent to your children.
I get that. Lord and behold, they flew the nest. I'm now on social media doing this, but it's, it's valuable and I get to, you know, meet folks like yourself. So, I think. It's too big to ignore. We just have to integrate it in a very positive way. Just like AI is too big to ignore.
We have to integrate it so that it can enhance our lives. And that's an evolution because I still don't know all the specifics that I need to do, right? Because sometimes it's easy to get caught up, whether it's likes, love, whatever, you know, all those stuff and those are metrics. They're nice to know and to have,
but I don't know if we should all be driven by all that because it's the one on one, the conversation, the insight, the relationship that are built outside of all that. What's your take?
Yeah. I agree. I mean, it's social media is, is amazing. And I'll, I'll tell you a story. Uh, when I started publishing, uh, my blog stay blog. substack. com back at the start of this year, like I was just checking the readership compulsively, how many
people read and didn't like it. And now what do I do? I publish it and then just walk away. Right. People like it. Great. They don't like it. Oh, well, uh, it may guide me in terms of future topics. Like, oh, well, I guess that topic
wasn't interesting to people, but I certainly don't take it personally. Yeah. Um, and it's interesting because different platforms have pretty different approaches to this. So, for example, Um, LinkedIn, you don't, you never see a lot of toxic or like, I don't see a lot of toxic stuff on LinkedIn.
Maybe 1%. I mean, over the 15 years, it's like very little, yeah.
Very little, right? And most people trying to help each other and put up things that are interesting and will help people in your job. Uh, you know, other platforms, not so much, right? So, um, it's really up to them to, to make it better. And of course, the problem, as is the problem with, you know, print media like
newspapers is that, you know, negative news and conflict sells and gets clicks. So it's just, it's, it's tough. Um, it's, it's tough thing to avoid, unfortunately, but you just have to remember when you're reading the newspaper or reading things like that, like most people are nice. Most people are good people. Yeah, there's some bad people out there,
but you just have to kind of ignore them. It's not, you know, more than half of humanity is bad just because more than half the articles in the New York Times are about something bad, right?
Yeah. Yeah, that's true. So let's discuss. The unique challenges you face in problem solving. So, every role presents unique challenges and how does your current role compare to previous experiences? What are some of the unique challenges do you face in your current role?
Yeah, well, I think, um, it's the large company, small company thing, right? So, so problem solving, uh, in a large company. First of all, you've really got to make sure you define what the problem is. Like, a lot of the times, the problem isn't scoped correctly. You're trying to boil the ocean, as they say, or you're trying to solve something
that's kind of too simple and easy, right? And a lot of problems today can be solved with software, right? Whether it's, uh, AI or more traditional software. And there is a bias, for example, large companies just buy software from other large companies, right? If you're a small company, then, um, you know, obviously you've got very
different, uh, very different issues. You may not have a large enough team to help you. You may have to do everything yourself. Hopefully, you can find an AI tool that will help you, uh, maybe, um, enhance your story on social media or send emails or, uh, help you plan your next trip. Things like that. Um, but the software doesn't have to
come from large companies that could really come from anywhere, right?
Mm hmm. You know, and I want to add to that is, let's say when people ask, like, how do I integrate AI into my business? My answer, because I've been asked that question, and this is a very simple answer, is that, you know, as consultants, you and I, let's say, we can't tell people necessarily how to use AI in their business.
I always suggest, first, you have to identify what your pain points are. What is it in your, whether it's day to day, that's repetitive, that has a lot of errors. That you just want to just remove from it, okay? Start with something small. And then once you integrate the AI into that something small and see the easy
wins, then it will enhance your trust. Right. So I think defining the scope of what that pain point is for businesses or that they need to do that is huge because you can't approach a problem when perhaps they don't admit that they have a problem. You know what I mean?
Oh, that's so right. And what's, what's almost hilarious is AI is so hyped right now that you literally had going ahead of technology at a lot of public and private firms and saying, here's some money, do something in AI so I can tell the board and our clients that we're doing something in AI, which is obviously completely backwards, right?
It's not a silver bullet solution. Exactly right. You can't solve something when business They don't even know what their pain points are. You're wasting money.
Exactly right. And the problem was, they didn't, they didn't tell the technology people what problem to solve. They just said, here's some money. I mean, it's just crazy, right? Big waste of money. So, uh, so now I think what's going to happen over the next few years is people will be more judicious
about their spending budgets and try to figure out, well, what problem am I really trying to solve here? And should I solve that with AI or something different? Right?
Or both. Because you can't leave out the, yeah, so I'm with you. So as we approach tail end, is there anything else that you want to add before I close out?
Wow. Uh, well, this has been so great. I mean, I think that, um, I, I do want to talk a little bit about the future of AI, right? Because I think, you know, the classic, uh, Bill Gates quote is, you know, technology changes less in a year than people think and more in 10 years, right? So to think 10 years out, I think
AI is going to be so powerful. And it will literally, uh, like being, having, having an assistant. And I'm not sure how we're going to communicate with it. Are we going to be typing to it? Are we going to be talking to it? Is it literally going to be, you'll be able to think and it'll do things? I don't really know, uh, because
things are going to change a lot. But I think, I think what we talked about before, like having a co pilot for all kinds of things. I mean, think about a personal assistant. We're just starting to see these, uh, these AI tools, which are just a little button that you wear that have a speaker and a microphone basically, right, instead of a screen.
And soon you'll be able to ask and answer questions to that and all kinds of things. Um, And I think that, um, humans are going to move more out of the loop when lots of little decisions need to be made, which is a big pain for us, right? Like really have to make a hundred decisions in an hour or easy to move back to AI and the big important decisions, especially to do with.
Ethics should remain with humans.
Yeah, boy, I, I have a lot of stuff like swimming in my mind as you were speaking. You know, I think of AI as, as a tool, and I think we've touched on this, but you have to remember you're the one that's directing it. Right? You're, you're directing it. And to truly reap the full benefits
of AI, you want to have your own foundation model driven by an ecosystem where you can create as many tasks as you want and that you protect your data and don't relinquish that. That's when you truly reap the full benefits of AI is to have your own large language models. And you know, and the thing is, it sounds intimidating.
But it's so doable nowadays, right?
Oh, absolutely. Yeah, I think Well, what, what we're, what we're talking about there is owning your own data, making sure your data is clean enough to use, because if it's garbage in garbage out, we've got a real problem, right? Like it basically won't work. And uh, I think we've seen some examples of that in the past where.
Models are overfed or there are issues and you know, they didn't really, didn't really work that great, but, but I, I think, you know, the key there is again, is going to be trust, right? Not just of the CEO. It says, let's create this. Let's use this data set and create this model, but getting everybody to use it. Uh, whether it's the same model or
customized models at your firm and, uh, and, and getting those early wins, right? Yeah. Yeah. The small wow. Yeah. Where I'm saving an hour a day. This is awesome. Right? Like that's, that's how
to get people involved. Um, if you try to do the. Moonshot project, which is going to take two years and no one sees a thing between now and two years from now, that's going to fail, right? You got to go with the small wins first.
I echo that. And the thing is you can't, like you said, work on a vacuum. You can't, because we're not in a business of just building models. The end user, whether it's your, your customers, your clients, your staff, they have to be very integral in that model creation. And the word vacuum cannot even
include that in your vocabulary in the creation of the model. So, but you know, it, it seems, it seems very straightforward, you know, but it's amazing how people are still working in silos. I guess that's what I'm getting at too.
Yeah, absolutely. Look, I think that, um, as we talked about before, there are kind of two paths in the future, right? One is an awesome path where AI helps everybody and helps us collaborate and everybody gets co pilot and the opposite, right? And I think, you know, my closing comment would just simply be, let's all work
together for the better future using AI, uh, not, you know, the worst one. Yeah. If we can do that, we'll be in great shape.
Great. Great. Well, thank you so much for sharing your valuable insights today. So as we conclude our conversation, I want to thank Alec for sharing his valuable insights on the impact across industries, the balance of innovation and risk management, the future technology in the professional landscape,
thoughts on leadership strategy and adapting to the evolving changes of AI. And thank you so much for joining us today, whether you're going to be listening to this on a podcast or watching it on YouTube. Thank you so much for being interested in this very important topic and follow Alec and I on LinkedIn for more upcoming events.
Thank you so much.
Thank you, Hanh. Great to be here.
Yeah. Thank you.