Episode 57: The Future of Tech, With Jim VanderMey

Kiran: So Jim, you just returned from the Hawaii International Conference on System Sciences. In addition to the sun and sand, I’m sure you got to enjoy, there were a few highlights that I thought would be worth digging into for a conversation today. So if you could sum up your greatest takeaway, what would that be?

Jim: Well, first of all, I really enjoy the HICSS Conference. And this is, I think, my ninth or tenth time there. And I get a lot of flack from my family because it’s held annually the first week of January in Hawaii. And when you’re coming from Michigan, no one really takes you seriously that you’re going there for work reasons.

But this year, there was a great energy and a great discussion because it was the first time we’d been together since January of 2020. 

But yet, my takeaway was that the most exciting tech isn’t tech. We’re not looking at the advent of new, hype technologies. There’s not a major inflection point that we’re looking at. So it’s an interesting time right now where the most interesting tech isn’t.

Kiran: You must say more about this, because in the past, I think people are always looking for, you know, what is the latest and greatest invention? What is going to come and change how we work and how business gets done? 

But what I hear you saying is, it’s really not any one thing. It’s not anything new and flashy. It’s sort of actually a different way of thinking about things. So tell me a little bit more about what that means, “The most important tech actually isn’t.”

Jim: Yeah, so just think about how tech is now in your life. You have the devices that you use, but you’re probably not planning on buying another device. Rather, it’s the things that you do with your devices that integrate into your lives. 

So tech has value as we integrate it into our lives. It can be integrated into the products we use, so smart and connected products. For example, we’re creating digital products for Winnebago Industries right now with their electric RVs. It can be integrated into our workflows, so the tools we use to get our jobs done. It can be at the level of personal productivity, like 3D printing, using the office productivity tools that you use every day. 

But it’s about how that tech is integrated into our work and into our life where value is created. And so we simultaneously have to be addressing behavior issues and opportunities simultaneously with the technology that we’re working with.

Kiran: Talk a little bit about data, because data can be used to create value, but it still remains something that is difficult or elusive for companies. So, where do you see data playing into the future as far as trends are concerned and how does one create value from data?

Jim: Well, Tiankai Feng leads data governance for Adidas Corporation, and he recently stated, “In data and analytics and data science, we work with data to improve human judgment, and in data governance we work with human judgment to improve data.” 

And so there’s this relationship that we have between good data, good governance, and then the tools to use that data. And aligning the right data to the right problems and then driving value remains really difficult because we have been tending to treat data as a technical system that we use, instead of as a capability to create new understanding. 

And IT organizations don’t have line level responsibilities, so they don’t have HR, they don’t have manufacturing, operations, marketing, sales responsibilities. So the levers that IT has to influence the organization are all through partnerships with other parts of the company. And so the finance team can get great value from data, but that means that IT and the finance team have to partner together to do that.

And so creating these liaison functions, these service functions, to enable IT to partner effectively with the business drives the value from the data. Data passively sitting inside of systems generates no value.

Kiran: And of course, there’s a privacy component as well when we’re talking about individuals and their own data and information and the benefits and potential downsides of using that for public good. 

So could you talk a little bit about any concerns or discussions there?

Jim: That was a significant point of discussion at HICSS this year and because when you think about public good, it’s about large scale anonymized data that can be used for research. It could be something such as the COVID dashboard that was used that John Hopkins published during the recent pandemic, and talking about the progress of immunizations and so on. And in order for that information to be available and useful, that had to be created by county health departments. It had to be rolled up to state levels. It was scraped by John Hopkins and then turned into a public data presentation. 

But at some point, there’s a transition from the data being about you as an individual to being one of many individuals. And so there’s the simultaneous tension between my data for my own purposes, for myself, and the privacy that’s necessary for that, and part of my data being shared to create a public good. And we don’t have, socially, the ability to have good discussions about that because it immediately goes to the politics of privacy, the concerns about government oversight, the concerns about corporate intrusion from the big tech companies. And so there’s whole body of work that is having to be developed about the relationship of my data to myself and to others.

Kiran: Yeah, and there’s a lot, there’s almost an ethical component too that needs to be weighed when having that conversation.

Jim: Absolutely. Absolutely.

Kiran: So I wanted to dig into some of the things that we’re hearing that are trending now and that largely has to do with AI and machine learning. I’m certain there was discussion in these spaces, so can you elaborate a little bit about that topic and this idea that, I mean is that going to replace people’s professions, or how does that fit into work?

Jim: Oh, there was so much discussion about that. There’s a term called RPA, Robotic Process Automation, and this is around creating algorithms and machine learning to automate parts or all of people’s jobs. So think about something as simple as matching invoices to accounts payable for payment — or accounts receivable checks. 

So that matching process, there’s discussions around how that can be automated, but we’re at a really interesting point in history, because these models are being developed based upon the expertise of people who have generated value over decades of their personal careers. And so they’ve developed methods of doing the work, and now we’re applying machine learning models to learn from those things. And then, we want to take those machine learning models and then allow those to be tools for people who don’t have decades of experience. 

So ChatGPT, for example. Kiran, you’re a content provider, you’re a writer, you write things for consumption on the web. How do you feel about someone mining all of your content and saying, write an article about ChatGPT in the voice of Kiran Patel and see what it comes up with? And that’s what they’re talking about is mining the content that we published on the web to create. And whether it’s art or whether it’s writing.

Fred Brooks, who wrote the book The Mythical Man-Month, advocates for the term — he recently passed away — but he advocated for the term Intelligence Amplifying Systems. IA as opposed to AI, suggesting that people and machines will be able to do far more than AI alone. And so, the idea that they’re supportive technologies as opposed to replacement technologies.

Kiran: See, that’s something I can get behind because then, we’re not talking about taking over what we do, but about complementing what we do. And that then creates an opportunity for improvement. And so when we were talking earlier, you mentioned that people are still necessary in this process to train these systems to work. 

Would you argue that’s the case that — do you see that as being possible with the two operating together harmoniously?

Jim: Yeah, people are absolutely necessary to train the systems. And the data that is used to develop these models, you have to have judgment to understand what might be biased, what might be incomplete. Does the judgment of the model align to reality? And we call that concept drift.

And there’s one of the threads at HICSS that I always enjoy, is what’s called the XAI, the explainable AI community. And it talks about how you explain what happens in the black box of the algorithm in a way that humans can understand that, because doctors won’t turn over diagnostics to an AI or to an IA without understanding how it’s working behind the scenes. And so, the adoption of this has to relate to being explainable and that it has to be managed and maintained to avoid it drifting based upon the data that it’s reacting with.

Kiran: I am certain that the incorporation of a lot of this technology is resulting in more complex systems. Can you talk about that a little bit, and what greater complexity of systems means for what’s necessary to manage these kind of systems?

Jim: So we talked about ChatGPT already. Let’s talk about autonomous driving, because that hits at the boundary of these conditions. 

The University of Windsor did a study on how drivers tune out and reduce attention during autonomous activities. They proved that drivers get worse when they have assistive technologies in the vehicle with them because you stop paying attention. And so the moment that you’re needed to drive, the cognitive load in those few seconds to actually get to a place where you can drive, it’s quite difficult. 

And so what we’re now describing is that the technology is not only designed to accomplish something, but you also have to design for the human behavioral interactions that are going to occur as well as the all of the environmental variation that’s going to occur, because we have not yet created generalizable knowledge that can adapt from one situation to another. So it’s highly complex systems that are interrelated. And because there’s a human behavior piece of this as well, the human behavior and the system behavior have to be understood as a whole.

Kiran: I’d love to hear your thoughts on what impact some of these systems and technologies are having on human beings. And what I mean is, we talked a little bit about the dehumanization component and there are new systems and new needs in place, and that’s having an impact on the type of transactions that take place. 

Could you talk a little bit about that and the social impact that’s occurring?

Jim: So this is one of the areas where the intersection of social science and technology is really interesting to me. And the term that I use — which is the difficult term is what I call the role “the digital servant.” And those of us who are in middle class, upper-middle class society during COVID took advantage of a broad class of data servitization, which is a term that’s used in the European community quite a bit. 

For example, Amazon drivers are needed for the last mile of convenience to get the product to the Prime customer. DoorDash, Uber, Instacart. Telemedicine, even. And so many other services leverages humans in the actual product that’s delivered through a new digital platform.

So it has made it easier to get a service through your phone, through a digital platform, through the web, but there is a human being that is in the middle of that workflow that gets the product to you. And because they’re now abstracted through technology, you’re not directly engaging with them. It transactionalizes it and you don’t have the same experience, because all of us know what it’s like going into the grocery store and you see things that, “Oh, that looks good,” but you don’t have that experience when you’re doing it with via Instacart. Likewise, you don’t have the experience of seeing what’s being served at a different table when you’re ordering online for takeout, as opposed to sitting in the restaurant. 

And this is just something we went through with COVID, but we have to be really thoughtful about how we integrate people into the workflows and supporting these digital transaction environments that we’re developing in a way that is not dehumanizing. And I think that’s an important part of how we create services and products in the new world of the digital experiences, because we tend to expect that digital experience and not really think about what the social cost is behind those digital experiences.

Kiran: I think I hear a theme emerging from a lot of your findings so far, which is the human component. And in a way it’s odd that we have to say it, but I think it needs to be said that humans remain a critical part of how these systems operate successfully. We should be mindful of the human consequence. Would you say that was a theme that you noticed?

Jim: Yes, it absolutely is a theme that I’ve noticed. It’s that “tech always has a boundary” condition. There’s always an edge where the technology interfaces with the human system, and then when that human system may go back into the technology. 

You think about how telemedicine works. You have a primary care, or you want something as simple as “I want to refill a prescription.” Well, that prescription or refill gets placed, you have to physically go to a pharmacy or have that pharmacy physically place the order and have it delivered to you. There are humans that are in that loop inside, outside. 

And so when we talk about — and our services design team has done this — they’ve created service design, which is then supported in a technology path, and that goes into a human workflow and then back into the technology path. And then consumers or customers, clients can interact through digital means, through in-person means. And you’re thinking about how that value is being delivered at every stage of the process and how the interaction looks, so you’re actually designing these interaction patterns.

Kiran: On the other end of the spectrum, we know that some of these technologies are being used for for entertainment purposes and things like immersive experiences. 

So, I’m intrigued by this, and I’m wondering if you could share your insights into this world of immersive experiences and what you’re seeing here.

Jim: Well, and that’s an area — again, technology is not part of a digital product. But now, the entertainment, that is a fundamental human need to be distracted, to be entertained. And technology is setting up these immersive experiences. And video games are a wonderful example of that, where it’s not a movie with a plot line, but you are creating your own plot line. And you can explore that. You can explore that by yourself, you can explore that with other people.

But then, augmented reality and these new immersive experiences, we’re now seeing expectations being brought into the corporate environment in high-value activities. Like our work with Stryker in their operating room design, that in the high-value space of an operating theater, that having doctors and the surgical team being able to look at what the layout of the room would look like in a fully immersive experience, and experience that in 3D. 

Our configuration services teams build these immersive experiences for customers, for consumers to understand what the product is that they would be engaging with, whether it’s a recreational product or whether it’s an office product, that there are these immersive experiences to really visualize what the thing is that they’re buying, so they can experience it before they sit in it, before they ride in it, before they touch it.

Kiran: As you think about businesses listening, and clients and consumers tuning into this episode, and all of these technologies that we’ve talked about, are there key takeaways that you think they should be mindful of as they think about their own spaces and their own verticals when we think about the future of tech, and the human component, and some of these themes?

Jim: In summary, and this is a message that I am involved with all of the clients that I’m doing direct consulting with, is that we’re talking about technology innovation oftentimes now requires mutually supportive, simultaneous innovation in other spaces in the business. 

So to take full advantage of the thing that we’re building from a tech perspective, whether it’s a mobile app or it’s an IoT product, or it’s a new platform, that there has to be at the same time, innovation in the business. Their channel and their ability to bring value to their clients through business model innovation. And so, think about the innovations that have to go together, that this tech innovation — this is why we’re not in a space — I could go all the way back to when we moved from proprietary Unix systems to x86-based mid-range systems in the early 2000s, and blade servers, and network-attached storage, and the smartphone, that the device, the thing was the source of the innovation itself. 

And there were things we did differently because of that. We started, we created new practices around these new technologies that we put in place. Now, we’re at the end of the cycle. We’re at the early stage with AI, but we’re really having to shape the human side and the technology at the same time in partnership with one another because we can’t do the human stuff without the tech, and the tech, if we build it without the human components, will have no value or adoption.

Kiran: It’s fascinating. If you had to look in your crystal ball and maybe consider what the Hawaii International Conference on System Sciences will hypothesize in 2024 or beyond, do you have a prediction that you’d wanna share?

Jim: It’s gonna be more about how we make digital innovation real. There’s gonna be more discussion about AI. There is a huge amount of work around the social systems inside of companies and in society, and how technology changes people.

One of the themes that came up that was really interesting for me was using apps therapeutically to help people with early onset Alzheimer’s or dementia, and how we could use apps to help those that have declining cognitive skills, some level of increasing cognitive impairment, and how we might be able to use technology to support the humanness of people through that transition. 

And so I think we’re gonna be taking on harder and harder problems over time as we understand how to design for behavior and technology simultaneously.

Kiran: To our listeners who may want to engage further in this conversation with OST, what would you recommend their next steps be?

Jim: If you’ve got a tough problem, if you’ve got a technology that you’ve implemented that hasn’t seen the return on investment that you’ve hoped that it would have, there may be a human design problem that we have to begin working on, and we can help design those human systems and go after the behavioral pieces, whether it’s an organizational change management or it’s a design issue. Or it might be that you have an idea that you’ve envisioned and designed, but now you have to figure out the tech to make that work. 

And so, we live in that very special space of where the humans and the technology comes together and I think that we have a place to, to serve in a really profound fashion for our clients in that way.

Kiran: Excellent. 

Jim, thank you for sharing your insights with us today and for being on the show.

Jim: Thanks, Kiran.

Kiran: Appreciate it. OST, changing how the world connects together.