Road Work Ahead

#2 - Mitch Shue: AI Adoption, Data & Privacy, Art & IP, Advice for Students

• Waypost Studio | Sam Gerdt • Season 1 • Episode 2

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I welcomed executive director of AIRISE at Clemson University, Mitch Shue, to our latest episode. With extensive experience from the startup world to the enterprise level, Mitch discussed his insights on AI, data privacy, and cybersecurity.

Our discussion branched out to explore how AI is changing workforce development. We explored how the right AI adoption strategy can enhance efficiency and generate value for individuals and organizations alike. Mitch and I considered the crucial role curiosity and innovation play, the hurdles in talent acquisition and retention, and leaders' approach to AI adoption. Mitch also shed some light on the prospects for budding tech professionals and the roadmap they can follow to gear up for the future.

Other highlights of our conversation included a dive into the repercussions of AI adoption on individual data privacy, intellectual property, and data centralization in the digital era. Mitch shared his viewpoints on art and social media, teaching the next generation, and the work that he has been able to involve himself in with AIRISE.

Sam Gerdt:

Welcome everybody to episode two of Roadwork Ahead, a podcast that explores the unmapped future of business and technology. My name is Sam Gerdt and I am your host. Today, I give you an interview with Mitch Shue, the executive director of AI Rise at Clemson University and a professor of practice in Clemson School of Computing. Mitch came to Clemson after a long career as a successful technologist, both at the startup level with companies like Webs. com and Hello Wallet, and at the enterprise level with Morningstar, where he served for several years as chief technology officer. Our discussion focuses mainly on the present challenges that companies of different sizes face, from AI adoption to data privacy and security, but we also talked about the next generation of technologists being trained now and some of the professional and ethical challenges confronting them as they enter the workforce. I found Mitch to be a down to earth thinker when faced with an unknown technology landscape, and his emphasis on balancing progress in all areas of technology is excellent advice for us all. I'm grateful for Mitch's time and his expertise, and I hope you benefit from it as much as I did.

Sam Gerdt:

Mitch, thank you for talking to me.

Sam Gerdt:

You come from a really interesting background in that you've got really really impressive resume on the startup side, and then you've got an equally impressive resume on the enterprise side and now you're teaching.

Sam Gerdt:

So you have your foot in three very different, very unique arenas and I think you have some really interesting perspective when it comes to topics like the future of business, with disruptors like AI, data and privacy becoming more and more of an issue, cyber security becoming more and more of an issue.

Sam Gerdt:

So I want to just pick your brain on a few topics and I want to hear more from the different perspectives about how we should be thinking about some of these topics, maybe approaching them as business leaders, and then maybe just get some ideas about how you're thinking about them on a more personal level, what you see and what some of your gut feelings are. So I think my first, most obvious question is you come from the CTO position at Morning Star. You had something like 1500 technologists working under you. That's right. You're not there anymore. But if you were, or if you had a new opportunity and you were dropped into a similar position, what would be some of your first directives to make sure that that organization was getting up to speed with some of the newer issues that we're talking about AI, data and privacy and cyber security?

Mitch Shue:

Yeah, that's a good question. Actually, when I was serving as the CTO, the advances in technology just never stopped, and so one of the challenges we were faced with was a cloud computer, and so what we did was we went through our entire workforce to make sure that everybody understood and could have an intelligent conversation about the technology, and then we would make decisions based on what we learned about the technology and how to improve the business. And I think we're still in that same climate with the emergence of AI, which certainly been in development for decades, and all of a sudden, the scene burst on the scene. The tendency for a lot of technologists is to just find problems and try to apply new technology to solve them.

Mitch Shue:

Sometimes that works, sometimes it doesn't, and so if I was still in a role like that, I would again encourage the development of conversational knowledge about the technology and then, in a rational way, figure out if there's a way to apply it in order to improve the business.

Sam Gerdt:

Now you're coming from Morningstar, which is obviously going to be a more conservative setting for a technologist. Is that the kind of mindset that you're applying to this a more conservative mindset? Is there a more aggressive mindset where you can afford to take risks, or is this something that we should automatically skew conservative with?

Mitch Shue:

I think that answer was from my role at Morningstar, which is a decidedly well established company, and you obviously have to have a different approach than you would if you were a startup. Actually, most of my career has been growing venture backed startup companies into sustainable, successful businesses, and the approach has some common elements. But clearly, as a startup company, one of the challenges you have is limited runway and you want to make the most of your resources. It's a race against insolvency. So if there's advantages to be had by employing technologies like AI in a way that's aggressive and that can sort of increase your mass as a startup, I would certainly look at those. So it's kind of a different approach depending on whether you're a well established business or you're a startup that is racing against insolvency.

Sam Gerdt:

When you moved from that startup culture to your position at Morningstar, did you find that you had some catching up to do in terms of shifting mindset?

Mitch Shue:

The interesting thing is this sense of urgency. The sense of urgency is quite different. When you're at a startup company, you wear a lot of hats and that sense of urgency is very, very real. When you're at a more established company, it's not like Morningstar is going to run out of money in the next few months or anything like that. So that sense of urgency is somewhat different and you have to instill a sense of urgency in your culture, but it has to be authentic because, again, clearly Morningstar is not going to run out of money anytime soon, but you want the teams involved in driving the business to have this sense of urgency. It's tough, it really is, but if you want to be a well established, long standing company that is relevant for generations, like a Morningstar, you do have to sort of think about what is going to keep you relevant and get people excited.

Sam Gerdt:

Do you feel like there's going to be a lot of disruption then from these startups who are moving fast? Have that sense of urgency? Is there a hesitancy from the enterprise level that's going to come back and bite them? Is there potential for?

Mitch Shue:

that you know. I think one of the challenges is that this is proven out in history. Sometimes the most innovative companies aren't the ones that win right, because no one knows about them or they're too small. There's too much risk associated with them. So sometimes you know startup company. That's what you're faced with right In the financial services space, morningstar is a trusted brand.

Mitch Shue:

There's lots of trusted brands in all industries that we look to right, we look to see what they're doing and then we have this sort of inherent trust in them. So I think innovative startups one of the challenges they have is to rise above the noise of every other quote. Innovative startup, right, and that's why we always see we're seeing this now with AI. It's everybody just doing anything with AI is going to get some sort of attention right, it's always happened. Just every few years there's something that everybody latches on to and it's tough certainly for the layperson to discern what's going on. It's tough for the investor to discern what's going on. So it just needs to shake out. But there are lots of companies who are really trying to take advantage of just the buzziness of whatever is irrelevant today.

Sam Gerdt:

There's definitely that hype that we're almost fighting against, because for people who are inside certain industries, especially people who are well versed in what's going on with AI, I think it's really easy to start looking at that hype and almost wishing it weren't there, because there is this disconnect that eventually is going to come back to bite everyone, because the general public is going to figure it out. We're not dumb people. We understand when you're over promising something that's just not going to happen. But one of the things that I think is really interesting from your answer just then is you mentioned the value of brand and how it sounds like what you're saying. One of the biggest hurdles to a successful startup is they have to overcome the fact that they have no established brand, and so, for that startup who has such limited runway, they have to balance innovation with establishing some kind of name for themselves.

Mitch Shue:

That's absolutely right. And then they have to land a client that has a well-established or recognized brand, because then people can relate to that and say, hey, these people believe in them and I believe in this brand. So, by extension, you must be doing something really good, and I've seen that several times in my career. I'm like there's no way this startup is going to overcome all this brand awareness in their industry and they have. They've managed to do that. They've managed to do it with superior technology, superior user experience and just landing the right influential client to push other clients over the edge.

Sam Gerdt:

And I suppose chat, gpt and open AI is probably the poster child for this in this particular cycle, because you have a company that was founded, co-founded by Elon Musk, who is something of a hype machine himself, and you have Microsoft coming and pouring in something like $8 billion into the company, and now you have what is probably one of the more well-established brands in that AI startup culture. The GPT logo is almost instantly recognizable by many people, and for that to happen so fast is pretty incredible.

Mitch Shue:

It is, and I think part of it is because the layperson has access to this technology and can see for themselves what it can do, and so they're able to just sort of spread the word to people who look to them and trust them, whether it's their family or their friends or people in their startup. What have you? It's easy for everybody to sort of sell.

Sam Gerdt:

Yeah, and what's interesting too, is the first business tool that's almost exclusively AI. We've had AI advancements in all of our business tools for quite some time, but the first business tool that's almost exclusively AI is chat GPT. We see this flooding into workplaces and it's not coming in from leadership. It's coming in from the average worker who's using it to augment their tasks. That's right. Is that something that you would be a fan of or a verse to in a CTO role and maybe speak to the startup versus the enterprise level there as well?

Mitch Shue:

Yeah, I think, as I mentioned earlier, there are continuous advances in technology and you see sort of gut reactions to these kinds of advancements. Now that I'm in academia, I see sort of the gut reactions to things like chat GPT. Personally, I think that, especially as a technologist, you really need to learn about these things and understand them and make decisions about whether or not you want to invest in learning more about them, whether you want to apply them to the business or what have you. I think that somebody who is an expert, who uses AI, is so much more powerful than somebody who knows nothing and then just relies on AI. And so what I see a lot and I see it in my students is that the best students use tools like chat GPT to make themselves better, make themselves better writers, make themselves better readers, but they don't completely outsource their brain to chat GPT, so they're actually using it as a tool, not just relinquishing all of their thinking to it, and so that is.

Mitch Shue:

I think the key for technologists and students is to use the technology in ways that are going to help improve you as an individual and then, by extension, improve the business.

Sam Gerdt:

It's really good to hear you say that.

Sam Gerdt:

I 100% agree that these tools, especially as they exist now, certainly not capable of replacing humans in work, but boy, are they capable of augmenting humans in work and magnifying the value that a person is bringing to the table, and so what we've seen, even in our own workplace, is the people who take the time to learn the tool use the tool to do better work than they were doing, and people in general who are already very good at their jobs tend to do much better with these tools in terms of producing value. There's almost like an exponential magnification of the output. So a highly skilled writer, for example, can produce a much greater percentage increase in efficiency and quality with these tools than a lower skilled writer.

Mitch Shue:

I completely agree. And you know I say this to people all the time because you know everybody's worried about AI is gonna replace my job or AI is gonna take over the workspace. And I tell people all the time you know AI is not gonna replace you, but somebody who is really good at their job, who uses AI, is gonna replace you.

Sam Gerdt:

Yeah that's right. Yeah, and yeah, if you, if you have a job where your tasks are repetitive and mindless, then you need to figure out a way to maybe break up to the next level, where the tasks are a little bit more thoughtful and a little bit more nuanced, because that's where you're gonna have good success. You're gonna be able to differentiate yourself with AI tools augmenting what you're doing.

Mitch Shue:

Yeah, that's exactly what I what I think is is it can definitely free you up for higher value tasks, and your job as an individual is to is to create value. You know it's to create value for your business and if you're in a leadership position, your goal is to develop more leaders, and you can do that by employing any kind of tooling you know in a way that advances that cause.

Sam Gerdt:

So this should really be a wake-up call, then, for those leaders, for those decision-makers, as they approach AI adoption in their organization to, instead of focusing on the efficiencies of the tool or the bottom line, they should focus on the efficiencies of their people, they should focus on upskilling, they should focus on education opportunities and building something of a culture that says we love AI, we love our people. We want to put the two together.

Mitch Shue:

Yeah, I think one of the challenges that all companies face today is is talent right, hiring the right talent and then, beyond that, retaining the talent. And the way you retain talent is you have a mission that they believe in, you make the work fun, you're investing in their professional development right, and you have their back and that's how you retain your workforce. And certainly, with advances in AI, with tools like chat, gpt and other tools, encouraging that curiosity in your culture is going to really help with retention and actually create new ideas for the business, and there's tons of pressure on business these days right, regardless of what industry you're in.

Mitch Shue:

If you're a well-established company, you have to remain relevant for years to come. If you're a startup, you know you want to try new things, you want to find your place and you can do it if you look at this new technology and learn about it and understand its strengths and weaknesses, and how to apply it to your mission.

Sam Gerdt:

What's interesting, too, is it seems like it's the younger generation just coming up that's doing that, that's taking this seriously, learning about it, and so it's. It's not going to be very surprising to me, I don't think, when companies discover their greatest talent for the next wave of business is coming from those entry-level positions, those lower-level positions, and not from established positions. That's that's why I think culture is so important, because otherwise those employees are going to figure out really fast that they have value that their company's not tapping into and they can go somewhere else, yeah, and be be used more efficiently.

Mitch Shue:

Yeah, yeah, you know. I think that the challenge for leaders is really to understand that they need to learn about this technology as well, because, especially if you're a technology leader, your goal is to make sure that your technology supports the business, and you need to understand what is available out there.

Mitch Shue:

And if you don't understand it, don't react by saying you can't use it, don't do this, it's not allowed, that doesn't support the business. You need to better say let's figure out what's going on here, let's figure out how we can remove some friction from our development process, how we can be innovative and maybe there's opportunities to employ AI. However, having said that, it's like a lot of technologies that we've seen throughout the years. Some of the technology doesn't really solve a problem and yet technologists are trying to solve problems with the technology just to use the technology.

Sam Gerdt:

Yeah, yeah, we have a lot of waste, I think, in that arena. So how are you approaching this, then, with students who are looking to get into the workforce? They're coming up in an age of LLMs and in an age of AI augmenting business on an individual level how are you telling them to approach this? Is there any caution? Is there just no? Go and do learn as much as you can. What are the caveats that are probably more important that they keep in their minds?

Mitch Shue:

Well, most of my students are computer science majors and one of the things I talk to them about is how to have a long career in technology. And I sort of reflect upon my own career, I reflect upon my undergraduate program compared to their undergraduate program and I tell them about a world where there's no internet, there's no personal computer, there's no GPS, there's no smartphone and they look at me like you know, I'm a caveman right and I tell them that the way you have a long career in technology is you learn about technologies constantly and you have this sense of curiosity that you are always trying to satisfy, and it's just, it's important for you to be curious about these things.

Mitch Shue:

So, as a student, I want you to be curious about these things, but at the same time, as I mentioned earlier, I don't want you to outsource your brain to something that is not that great at everything, right, I mean, I want to know what you're thinking. I don't want to know what the AI is thinking Right.

Mitch Shue:

I saw when you asked to write a paper. I want your thoughts on this subject and this subject. I want your thoughts and I want you to go through the thinking process rather than just trying to come up with the coolest prompt to generate something that's going to get you a grade Right. So I tell my students, don't use chat, ebt or any tool to get a grade. Use the tool to learn, because at the end of the day, you know something and are able to use AI, are going to amplify your skills and your ability to do really cool and helpful things for the world. And you know it seems to resonate with students.

Mitch Shue:

I've, you know, some of them have completely outsourced their assignment to chat EBT and I asked them why. You know, I'm like, why'd you do this? And, first of all, they're kind of startled. They're like, well, you know, how did you know? And I'm just like you know, not a complete idiot, I can tell. But you know, tell me, you know why, and a lot of it is down, comes down to not being well-organized, not understanding time. You know those kinds of things. And I talked to them like these are important skills to learn, right, if you can do everything with chat EBT. Why would I hire you? Because I could do your job. I could do what. I hire you chat EBT, just like Google, I could just Google everything. If you're going to Google everything, I can Google it. And they understand.

Mitch Shue:

And I guess I have the advantage in that I'm not a career educator. So I tell them that I interview people like them and I know that within the first minute I know you know, did you cheat your way through school? Did you outsource your brain to some AI? I can tell. And one of my students asked me how can you tell? And I said because I asked a question. And then I asked a follow-up question and they're like oh, I'm just like, you cannot cheat your way in your career. You know you're going to be, you're going to be discovered and it's going to be too late, right? So I tell them don't cheat your future self. Right, it's kind of cliche, but I tell them don't cheat your future self.

Sam Gerdt:

No, but it's so true and even in my own experiences, I use I use chat GPT daily, probably in some cases, hourly. It's a huge part of my workflows. At this point, it's something that I'm training myself on, and I also use other AI tools to manage portions of my day. I happen to be one of those people that's extremely disorganized. I have terrible time management and I'm actually very thankful for AI, because there are some really good AI scheduling and time management tools out there and I use one to manage my calendar and all it needs to know is what's on the list and roughly how long does it take and when does it do, and it handles the rest. It gives me a time blocked calendar. I can stick with it. If I miss something, it adjusts for me. If somebody schedules a meeting in the middle of a block, I don't have to spend 30 minutes trying to figure out how do I recover from this. I can just go to the meeting and it's, it takes care of itself. My calendar adjusts for me, that's.

Sam Gerdt:

I think that's an example of what you're talking about, where AI can be an assistant, but it's you're not outsourcing your brain Right, even in writing projects that I've done where I've used AI to help chat, gbt to help. It's not. Will you please write this article for me? It's. Will you please assume this personality and let me bounce some ideas off of you. Help me to develop this outline in a more cohesive way and, at the end of the day, you still have to be a very talented editor in order to produce good content.

Mitch Shue:

Yeah, yeah, I found that, I definitely found that is true for me too, when I use chat, gpt, it's almost like a, a springboard for ideas. You know, it's like, oh yes, I didn't really think of that, but now, now that I've seen this, this response, you know it gets me to think about things that I wasn't thinking about, which I think is great, because it sort of teases out parts of you that you know perhaps need to be teased out.

Sam Gerdt:

Absolutely, absolutely. And and you know we can't we can't necessarily go through those exercises as quickly as it can. It doesn't mean we can't go through those exercises, but that's where the efficiency comes in, is it's? It's allowing you to do things that you already know how to do if you're if you're a good writer, if you're a good editor, but it's allowing you to do them much faster, much more efficiently. Yep, and I think that I think that's why it really it does belong on everybody's desk Quickly. I want to. I want to change subjects. Sure, one of the one of the reasons why I see more enterprise level organizations hesitating on the brink of artificial intelligence is because of how important and critical cybersecurity and data privacy has become. I think there's this sense that giving data to an LLM is a risky idea. Is that? Would you agree with that?

Mitch Shue:

Yeah, I think. You know, I think people often don't think about security first, right, they're just sort of an amber with this response they get and they're not really thinking about security. But we've seen that in a lot of cases, with advances in technology, security sort of comes later, unfortunately, yeah. But now we're employing technologies now where that we can't afford that. We actually have to think about security first and as a first thought, not an afterthought. And I think that's definitely true with AI tools, especially when it comes to the code.

Mitch Shue:

You know, I've heard of teams that use chat GPT. You know, I understand why they're using it this way, but they're not thinking about the fact that they are basically exposing their intellectual property in the form of source code and they're just feeding it in the chat GPT. You know, like, help me, help me debug this or help me improve this piece of code, and it's like this is your, this is your source code, you know, for some important product or service that you're offering and you're just just kind of throwing it out there. So, yeah, so I think engineering leaders, especially, while they have to encourage this curiosity, they need to have some guidance, you know, for their teams, like, like, don't give away our intellectual property in whatever form. Right, be smart about that. But you know, it's amazing. I've talked to several engineering leaders who are like, oh, I haven't really thought about that but yeah, we need to have some guidance there.

Sam Gerdt:

Now do you think that there's much incentive in the short term then to build out LLMs on private infrastructure? It could be cloud based, it could be privately held, but the idea that you're that you're creating a gap between your data and your inputs and the rest of the world I mean, some of these open source LLMs are already pretty powerful. I mean Lama two is very powerful. So is that something that that business is maybe more enterprise level should be considering at this point?

Mitch Shue:

Yeah, probably, but not, not. Not all enterprises, big or small you know, actually have those kinds of resources. They don't have the skill sets, they don't have just the overall capacity to do those kinds of things. They can barely keep up with their own roadmaps and things like that. So some of it is it'll become easier. But again, there are ways to use chat GPT safely without having to sort of invest in your own infrastructure or expertise. You just have to think a little bit about what are my guard rails?

Sam Gerdt:

Yeah.

Mitch Shue:

I would imagine that you know most companies and most industries will be able to use something like chat, gpt out of the box without having to do some more specialized or sort of isolated isolating their own LLMs. But you know.

Sam Gerdt:

Yeah, it seems to me, and maybe you've got a different opinion on this, but the direction that we're headed, especially with the way open AI seems to be conducting business, is we have the original training set, the data set that was used to train GPT-4 or any of these other models, and it seems like the inputs into the interfaces like chat, gpt. It seems like they intend to use those inputs for future training and it also seems like they intend to continue scraping the internet for human-generated content, specifically for future training. I think they recently came out with the web crawler and I think they signaled this a little bit when they said you can disallow it Because they got into some trouble because it was scraping content behind paywalls, and the response to that was well, you didn't tell us not to. That's the way I'm reading it.

Mitch Shue:

So if it can, yeah, it's a standard privacy issue. This notion of opt-in versus opt-out Opt-out is so easy for businesses. They can just say as you just said well, you didn't tell us we couldn't do it. It's kind of easy for them. But for us and businesses, a lot of us just individually, we don't even know that we can opt-out. But if we went to an opt-in solution it's a lot of friction for a lot of businesses. So, privacy advocates always want opt-out, I mean sort of opt-in. But businesses they want it opt-out.

Sam Gerdt:

Being on both sides of it, I can see. For a business especially, opt-out is certainly easier, but it seems like we've got a bit of tension here because regulation is tending to favor opt-in models and consumer privacy, whereas business models are still more opt-out and we need your data Give us your data.

Mitch Shue:

But the other thing is even opting in anything involving you having to digest some terms of use. It's just nobody reads them.

Sam Gerdt:

Yeah. So with regards to that opting in, opting out, we need more data for training in order to improve these models. To me, it would seem unwise for a company to willingly hand over data through prompting to a public model like GPT. What I'm hopeful is we get some SaaS and infrastructure as a service offerings that allow us to adopt larger scale models for companies where your data can be secured by you, with some assurances, some compliance, and that would enable, I think, a lot more exploration in this area.

Mitch Shue:

I think that's going to happen, Just like if you look at all the public cloud infrastructure. It used to be so focused on infrastructure, whether you're AWS or Azure or GCP or Alibaba Cloud or whatever, but now they've all gone to higher value services so that you can explore and experiment with these kinds of things. I mean, they all have AI offerings of some sort. Yeah.

Sam Gerdt:

Well, there's going to be a huge demand for it. I mean, to get this off the ground on your own would be crazy expensive, right, I think, with chat GPT, your open AI just said that chat GPT by itself costs them $700,000 a day to run.

Sam Gerdt:

I mean, granted, they've got over a billion users, but yeah, these models are incredibly hungry when it comes to energy and it'll be interesting to see how that scales. I know NVIDIA just announced a new, more efficient chip. I'm sure more of that's coming down the pipeline, but it'll be interesting to see whether hardware can keep up.

Mitch Shue:

Right. Well, that's why we're at this tipping point now is that hardware and compute infrastructure has reached this point. We can do these kinds of things, and combining that with this proliferation of data and these advances in AI techniques put us here what seems like happened all of a sudden. It's been happening for decades and I think it's going to keep going. And what's going?

Mitch Shue:

to happen is that people are starting to think about this. It's like you mentioned it also is the energy costs. It's like how do you measure the energy costs of this? And it's tough, but it's enormous.

Sam Gerdt:

This isn't necessarily the same topic, but I've listened to a lot of people who are in energy and they believe that we're headed towards lower cost energy in terms of generating power, but also greater efficiencies in running some of these vast, vast computing machines that we've set up. What I think is interesting is you come from a background where you were very heavy in cloud computing and it doesn't seem to me maybe you can correct me on this it doesn't seem to be that AI was really any kind of a focus in the migration to cloud computing for so many enterprises. I think it was generally cost. Is that correct?

Mitch Shue:

It was cost and also removing friction, because traditional computing environments would require a developer to have to provision a server, whether internally or in the cloud, to do some exploration or experimentation. There was a lot of friction there, so by going to the cloud we removed that friction. It's like I need to try this out. I'll just spin up a server for half an hour or try this out, tear it down no friction. But the other driving force is really running our own infrastructure in business differentiator and for most companies running your own data center is not a business differentiator. I mean, no one buys Morningstar products and services because of its data centers at all.

Mitch Shue:

So I think a lot of companies realize that they need to get out of the data center business, and then the cloud providers reached a point where they could provide the infrastructure necessary for companies to do it and what they feel like is a scalable, secure way, and more and more companies move to the cloud and just because of that, you're able to have companies that can grow very fast and can respond very quickly. Case in point Zoom during the pandemic, march 2020, everybody goes online and if you have your own traditional infrastructure, it's like I gotta buy thousands and thousands of servers, I have to rack and stack them, I have to secure them. That's just not gonna happen.

Mitch Shue:

So with public cloud infrastructure. I read one account that said, during the first few months of the pandemic, Zoom was adding now 5,000 servers, since it was a day and you can't do that. As you use it. That would be Employee for the cloud infrastructure, so I think the same is gonna be true with these higher value services, like related to AI is why am I? Going to build that infrastructure.

Mitch Shue:

I'm just gonna use it in sort of a utility fashion and pay for what I use, for as long as I use it and get on with my business.

Sam Gerdt:

Sure. So we're painting a picture now of data collection increasing and increasing and increasing, infrastructure getting more and more and more centralized and all of that data is obviously going to that infrastructure. So, as we see a centralization of all data, all infrastructure, what does that do for cybersecurity? Is that a good thing or is that a bad thing?

Mitch Shue:

Well, there's lots of different ways to kind of look at this, but I think again, at the root of my answer is the fact that advances in technology have far outpaced our ability to safeguard the people most affected by these advances in technology, and we see that still with this proliferation of data, just the velocity of data collected for everything. In a lot of cases I think Europe is far ahead of what needs to happen, that we are here in the United States, but still it's woefully inadequate for the time we're in now. There's just so much data collected from so many different places and, honestly, a lot of companies have no idea or cannot differentiate the sensitivity of the data they collect, because not all data needs to be treated the same way.

Mitch Shue:

And it's just a remarkable situation. There's quote anonymous data. It's really not anonymous. You look at it and you triangulate and you can re-identify pretty much anything. So it's not really anonymous. So I think our ability to sort of regulate this is far behind from a technology perspective. On how to secure it, I think we can secure the data, but in order to secure anything, you have to actually know what it is that you're securing. How does this data need to be secure? Like I said, not all data is equally sensitive.

Sam Gerdt:

We talk about personal information and then sensitive personal information, and the difficulty with that is a lot of it has to do with the context. On its own it doesn't necessarily seem that sensitive, but then you put it into a certain context and all of a sudden now it's sensitive.

Sam Gerdt:

We actually have to think about that a lot. We're in digital marketing. That's what I do, and the example that I give is a name and an email address is not necessarily sensitive, but a name and an email address on an Alcoholics Anonymous List all of a sudden becomes very sensitive and being able to understand those contexts and protect that information super critical, absolutely super critical. You touched on it a little bit before, but I'm actually somewhat disappointed and I don't say this very often about regulation. Europe did GDPR several years ago and then it seemed like there was this push to have something like that here. But then I feel like maybe I don't know, maybe COVID happened, maybe Trump happened, maybe I don't know what happened, but completely derailed.

Sam Gerdt:

And again, usually I don't have a lot of positive things to say about lots and lots of regulation, but GDPR was, in my mind, a very thoughtfully put together piece of legislation that really and truly put the user in the center, and the result of it was actually strikingly very good. Companies were headed in a trajectory that was not healthy, not good, and larger companies now that anybody who does business in Europe really had to change everything, even to the degree like you. Look at products like Google Analytics now, and they're completely different in terms of anonymized data, the way that you can target audiences, the way that you can collect information on users completely different, and we have GDPR primarily to think for that. I was hoping that we would get some guidance like that in the United States. That would maybe just not necessarily go further, but at least make those principles that you find in GDPR a little bit more universal the right to be forgotten as an established right of the consumer.

Mitch Shue:

Yeah, what's interesting is we have these sort of national boundaries and things like that, but you look at something like the internet and everything associated with it and there's no national boundaries. So it's tough. We don't have a world government, but things like GDPR actually gain traction because of globalization. Countries want to do business with other countries, so they have to make a business decision, so I think a lot of regulation is going to be influenced and driven by business. It's interesting, it's troubling, but honestly, also as individuals, I guess there are some individuals who are very aware, or try to be aware, of all the information disclosed about them, but honestly, most of us don't know how much information is out there available to us.

Mitch Shue:

There's an enormous amount of information and somebody can find enough pixels about us to form a very detailed picture of us. That's why we have this very, very targeted marketing and it's kind of scary, but as a technologist, when I see it happening I understand what's happening.

Sam Gerdt:

Yeah well, and I think that's what makes artificial intelligence such a scary prospect for so many is because when you have those diffused pixels of information out there, it's not necessarily possible for a person or a group of people to put together an accurate picture. But you throw the computing power of artificial intelligence at it and all of a sudden you can produce that clear image.

Mitch Shue:

Absolutely, you can produce that clear snapshot of a person's life. I mean, even before things like chat, GPT and things like that just your typical basic, unsupervised learning. It's just like finding patterns in this data, patterns that I can't see, find them for me. And you look at these emerging patterns and you're like, wow, that's something I didn't know and I can exploit that.

Sam Gerdt:

Yeah, so AI is going to be a nightmare for privacy. We've established that pretty thoroughly. Oh yeah, what's it going to do to intellectual property?

Mitch Shue:

Yeah, that's a really interesting question, especially with the rise of, you know, all sorts of generative platforms, right for generating music in the style of this person or, you know, actually using this person's voice, generating just sort of visual art, you know, in the style of some artist. Yeah, it is just a crazy time because, you know, when you think about traditional intellectual property, it's about has its roots in rewarding creators, right, right, and it encourages people to create. Because, you know, I reap the rewards of these things I create, whether it's music or some wood carving that I make or something like that. It's just like my work. My blood, sweat and tears have gone into this and, as a creator, because of you know I created this thing I should reap some rewards for at least for some period of time. Right, that's kind of what's at the root of intellectual property.

Mitch Shue:

Yeah, but now it's like everything is derivative, not everything, but you know that's kind of exaggeration, but so much is derivative. You know, and we saw this years ago with sampling, right, music, just sampling the song and the song. And you know, again people are like, well, you know, shouldn't that person that you sample get some credit for this? And then some people are like, well, you know, it's not really the thing they created, I just mixed in my work with it. So, you know, maybe not, I don't know. So now it's, it's, it's in our face, right. It's just like, okay, who should, who should? How do we reward the creators?

Sam Gerdt:

I think some of the absurdity of the more recent IP models is coming to light. The original model you had a benefactor. The original model you had a patron, someone who was saying I want this, I'll support you in this, and then usually only after that was the art created, not before. Now we've shifted to this model where art is created almost more on spec, where you're saying I'm going to create this piece and then I'm going to go find a supporter of it and we've gotten so accustomed to that model.

Sam Gerdt:

I feel like and this is something of a personal opinion I feel like there's this sense of entitlement that has grown out of that, where people feel entitled to say I made art, therefore I must be paid, and and the reality of it is, without having that benefactor, without having that patron, there's really nobody who's going to pay you.

Sam Gerdt:

And asking the universe for it or asking the government for it, or whoever is, it seems to me like you're asking a lot, and I think, then, the other absurdity that I'm seeing is you know, google just announced that they're going to license. There's a mechanism now for licensing a I created, I generated music. I don't even know what that means, like licensing from who has the authority to license it, who has the authority to own it to the degree that they can license it. It almost sounds to me like Google is just saying I'm going to pay somebody something so that I can say I paid for it. And that's almost where we're at right now with intellectual property is, if you have intellectual property and you paid for it, you're good. But all of the behind the scenes just seems tangled right now.

Mitch Shue:

Yeah, I don't know what the answer is, but you know, again, you want to encourage creativity, absolutely, you know, and not everybody who creates music is great, obviously, but you want those wonderful artists, in whatever field they're in, to create. And the concern is, how do you? I mean, some people will create just because they love to create, but you know people need to eat, you know they need to make a living somehow. How do you? How do you reward people for what they do? Right, and everything is kind of messed up for me, because I think, you know, I see these influencers on various social media platforms and I'm thinking you know what they're doing is nonsensical, but they make bank right, yeah, yeah.

Mitch Shue:

And yeah it's just, and what's sad, I think, is I run across people who that is their aspiration is. I want to amass, you know, a million followers so that I can kind of say things or do weird things and get paid for it.

Sam Gerdt:

Yeah, well, it's. It's money and fame it's. It's a hard thing to turn down. The problem is going to be when generative AI learns how to do that.

Mitch Shue:

Right.

Sam Gerdt:

They'll know our psychology, they'll be able to, they'll be it. I mean, a movie is a big ask, but a 30 second clip that you know lives and dies in 12 hours, that's not not as big of a of an ask, even today, for generative AI. So yeah, we're getting to the point where there'll be accounts out there that are you don't see the person who's actually behind it, you just see what the the result of their prompt.

Mitch Shue:

Yeah, I think what's sad for me, especially in the area of arts, is it seems like so much is forgettable these days.

Mitch Shue:

You know it's like some of the stuff is like no one's going to remember this tomorrow, even you know. And then part of it is is maybe, maybe this is kind of a boomer thing. But you know, I, I still listen to a lot of music from the 60s and 70s even before that and the 40s, 50s, depending on kind of what genre of music it is. But there is a lot of memorable music, you know, that maybe will never get made again and and and people listen to that music and it's just lasted for decades and decades and decades. And then there's music that is more contemporary and it's hard to say if it's going to be remembered. But you know, even I listen to some music that's maybe 20 years old and it's like just not memorable, you know. It's just like what is this song? I don't even know when it was made, I think.

Sam Gerdt:

I think we all tend to favor the music of our own growing up years, our own generation to a certain degree. But you're, you are right, it does seem like there's this degeneration of art into being far more transient, far more forgettable.

Mitch Shue:

Well, movies too. If you look at movies, tv shows things like that.

Sam Gerdt:

I think motivation has a lot to do with it, though it goes back to that idea of a patron or a benefactor. If you don't have someone who's saying I value this, I want it, I'll pay you for it, then the you're just tend to be making art to. These days, a lot of those people make art just to sell ads. That's where their revenue comes from. I just need I just need to keep somebody's eyes glued on the screen just long enough so that the next real will play.

Mitch Shue:

Right.

Sam Gerdt:

I don't. I don't need to, they don't need to think about me after they're done watching me. They just need to watch me long enough that they'll watch the next one, and then the next one, and then the next one, and it's not a sustainable model. It's not good for humanity.

Mitch Shue:

No, it's not, it's not it's certainly not good for mental health either. You know, I had a student tell me that she was self aware enough to know this. She said one week she spent like 28 hours watching reels and ticktocks. And you know she's like that's 28 hours this week that I don't get back. Yeah, you know, it is that that that sort of it's that addiction. You know, it's just the AI understanding what it is that you keep clicking on, yeah right, and just reading you this, this drug.

Sam Gerdt:

And the people who produce that content to call it, to call it art. I don't want to be hyper critical, but to call it art when the model says we're going to feed one person 28 hours worth of one minute or less videos. I don't know, I can't do the math, but that's thousands and thousands of pieces of so called art and she probably doesn't remember much of it at all now. And so to say, I'm a content creator, I make art. Those two seem to be disconnected concepts in my mind. You can be a content creator or you can make art. Now, that's not to say that there's not some art in there. There absolutely is. And usually those people go back to either having a benefactor or they, you know, they have a patreon account and they have patrons, and so those models aren't completely dead they just get lost in that shuffle yeah, yeah.

Sam Gerdt:

So do you think that IP has a rough, rough future ahead?

Mitch Shue:

then yeah, I mean, you see it already. It's just like we don't know what to do, honestly, with generative AI. You look at these beautiful images that get created, you know, and you're looking at it going Okay, you know, what did you do other than come up with an interesting prompt? You know so what is protected, the results or or your prompt, I don't know. So I just think that a lot of our thinking again is behind, and we're at this point now where advances in technology used to outpace our safeguards by a little bit, and now it's just like a slingshot. It's just like prehistoric times when it comes to international property protections. Now it's just like I don't know what to do.

Sam Gerdt:

Yeah.

Mitch Shue:

Don't know what to do.

Sam Gerdt:

Mitch, I don't want to end the conversation without talking about AI rise and what you're doing at Clemson, so I want to give you a minute just to tell us what it is you're working on, the importance of the program and what you're doing in our area, particularly, I think, with manufacturing.

Mitch Shue:

Yeah. So AI rise stands for AI Research Institute for Science and Engineering. It is an officially recognized institute at Clemson in that it was approved by the Board of Trustees at Clemson University. It serves as the umbrella for AI research, ai education and workforce development at Clemson. Clearly, before AI rise, there was a lot of AI work going on all over the university, across all seven colleges now eight colleges. Yeah, so many different departments.

Mitch Shue:

But AI rise, the Institute, was created to be this umbrella. It's great for researchers because when they submit proposals for funding, they can submit those proposals through AI rise. Ai rise gives their proposal a little bit more mass, a little bit more credibility, if you will. It's helpful. So we have about 120 affiliate faculty from across all the colleges, probably 35 different departments involved with AI rise. So you have people from art, religion as well as all the technology fields involved with AI rise. So it's really about again being the umbrella for AI research, education, workforce development at Clemson and beyond. So our mission is really to take that education component and take it to the upstate, across the entire state, across the region. We want to focus on the areas that Clemson is known for advanced manufacturing, biomedical informatics, material science, cybersecurity, cyber infrastructure and intelligent transportation. Those are five areas that Clemson is known for, so we focus on those kinds of things as well.

Sam Gerdt:

That's cool. So you mentioned art and religion. That means you're taking a philosophical approach as well as a technological approach.

Mitch Shue:

Yeah, it's interesting my historians, for example, trying to figure out how to apply AI to history. There are so many applications, interestingly, at first you're thinking well, what's that all about? But when you think about being able to take an AI system and determine the provenance of some historical document, it's like, well, we've always thought that this person wrote this, but given what we know about all the writing in that time period and everything this person wrote, perhaps an AI can help us determine these true provenance. Is it somebody who was near this person and wrote in the style of this person? So it's fascinating, and the nice thing about it is that historical data is not increasing rapidly like data that's being collected. It's a data set that can be analyzed in a lot of different ways using new AI, it's definitely more static yeah.

Mitch Shue:

So it's important to be able to look through historical documents and determine things like provenance and things like that, because so much of what we know and do is based on historical documents. Right, it's just like did this person? Have we been attributing this to the wrong person or the wrong civilization? Even so, it's fascinating what researchers across the University are interested in applying AI to.

Sam Gerdt:

That's fascinating and you've had opportunities. It looks like to do a lot of stuff. I saw a demo just recently on. I think it's called Deep Orange I guess that's under that umbrella as well. An autonomous vehicle.

Mitch Shue:

Right, the latest version of Deep Orange, deep Orange 14, which is an autonomous tracked vehicle like almost like a tank, but before that Deep Orange 12 was about autonomous driving at raceway speed. So basically Formula One car self-driving. And the nice thing about that is Clemson was responsible for the common car used for that competition, so all the cameras and sensors, the compute infrastructure Clemson was responsible for, and then a couple dozen organizations used this common car and basically raced autonomously on the Indie motor speedway and so since then that has turned into a sort of an international competition. So a lot of times when you see these Formula One cars they're in these self-driving situations. You'll see a Clemson logo on the nose of the car. That's got to feel good. It's very cool.

Sam Gerdt:

Yeah, that's pretty sweet.

Mitch Shue:

And the idea is, if you can self-drive at 200 miles an hour, you can do a lot at regular neighborhood speed or highway speed. Yeah, so that's the idea there.

Sam Gerdt:

One more thing before we go.

Mitch Shue:

Sure.

Sam Gerdt:

I just want to know generally are you optimistic or pessimistic about the future of technology?

Mitch Shue:

You know I'm optimistic. I think that in general, cooler heads will prevail. People are very curious about new technologies and things will settle out right. We've seen it in the past Things that are super hyped. Sometimes are exposed. It's been super hyped.

Sam Gerdt:

And that's not an excuse to write off these tools. It's an opportunity to level up while everybody else is sleeping.

Mitch Shue:

Yeah, and to tell people you know you just want to be curious and curious about things, maybe outside of your normal focus, right, and there's things happening all around you. The world's changing very quickly and the citizens of the world. I think it's important for us to just understand the implications of these kinds of things.

Sam Gerdt:

Excellent, Mitch. Thank you. It's a pleasure talking to you. Your resume is incredibly impressive. You have certainly covered the gamut of technology and it's been really interesting to hear your perspective on all this new stuff coming down the pipeline.

Mitch Shue:

Thanks so much for having me.

Sam Gerdt:

I'm incredibly thankful that you were willing to talk and I'll look forward to catching up with you again, maybe in the future and we can see how we sounded whether or not we were right or wrong about some of this stuff.

Mitch Shue:

Yeah, very good. Thanks again for having me. I really enjoyed our conversation today.