Ep 43: Collective Intelligence Meets Artificial Intelligence to Create Scalable Digital Advisors with Kevin Clark

[00:00:00] Welcome to Elevate Your AIQ, the podcast focused on the AI-powered yet human-centric future of work. Are you and your organization prepared? If not, let's get there together. The show is open to sponsorships from forward-thinking brands who are fellow advocates for responsible AI literacy and AI skills development to help ensure no individuals or organizations are left behind. I also facilitate expert panels, interviews, and offer advisory services to help shape your responsible AI journey. Go to ElevateYourAIQ.com to find out more.

[00:00:28] Welcome back to Elevate Your AIQ. For this episode, I was excited to reconnect with Kevin Clark, a former IBM colleague and now the founder of Content Evolution. Kevin and I share a deep appreciation for the concept of collective intelligence, how we can better harness the collective knowledge and creativity of individuals and teams to solve complex challenges and make better decisions. But what about the intersection of collective intelligence and artificial intelligence? Timing of our conversation is perfect as Kevin's new book, Collective Intelligence in the Age of AI,

[00:01:08] has just hit bookshelves, and in many ways our discussion aligns to that theme. Drawing on his decades at IBM and his innovative work at Content Evolution, Kevin brings a unique perspective on the intersection of technology, content strategy, and human potential. It's a fascinating, thought-provoking conversation. Enjoy it. You'll find a link to Kevin's book in the show notes as well. As always, thank you for listening.

[00:01:31] Hello, everyone. Welcome to another episode of Elevate Your AIQ. I'm your host, Bob Pulver, and today I have the pleasure of speaking to Mr. Kevin Clark, an old IBM colleague of mine. How are you doing, Kevin?

[00:01:42] Good. How are you, Bob?

[00:01:44] I'm doing great. It's good to see you.

[00:01:46] Glad to reconnect this way.

[00:01:48] Yeah, absolutely. You've been a busy man, and you are playing in a lot of areas that are near and dear to my heart, as we have spoken about.

[00:01:56] But why don't we just start with telling the listeners a little bit about your background, who you are?

[00:02:01] Well, when you knew me, I had spent 30 years at IBM before retiring, and I got across the threshold and actually retired from IBM.

[00:02:13] And have a pension, that rare, exotic thing that some people have and other people are increasingly not having, as it were.

[00:02:28] I was the first brand steward for ThinkPad Notebook Computers mid-career after an earlier career in public affairs and communications and marketing communications planner for a whole bunch of industries.

[00:02:48] That ended up being very, very interesting and got me involved with corporate strategy, which we'll play in in a moment.

[00:02:56] When I got three business units sold with help of others, you know, leadership team, we had moved the PC company into the hands of Lenovo and retail store systems in the hands of Toshiba.

[00:03:13] And we had moved the printer systems group, you know, big chain printers that make your credit card statements and stuff into the hands of Rico.

[00:03:23] So that left me with six years to go.

[00:03:26] And I went into corporate to work on customer experience, engagement, and, you know, the experience that our clients had with the company.

[00:03:39] And retired as the director of brand and values experience, which is kind of a straddle between corporate design and corporate strategy.

[00:03:48] So I will tell you the dirty secret of my career, which you kind of know, is that people were paying me for my hobbies for a long time.

[00:03:57] I was actually enjoying what I was doing.

[00:03:59] And when I got across the threshold, my dad worked for IBM and he worked for IBM for 38 years.

[00:04:06] And I said, well, I still have a lot of energy.

[00:04:10] I can keep going, but why don't I do this for some other folks?

[00:04:13] So, you know, I asked, you know, companies that I had worked with, had spent quite a bit of money on over the years.

[00:04:23] So would you like to do some of the things that we were doing in customer experience engagement and market research and strategy and planning for other entities?

[00:04:32] And for the most part, they said, yes.

[00:04:34] So I retired at the end of February and at the beginning of March, continued, you know, to work under the guise of content evolution.

[00:04:44] And look, in the age of AI, content is rapidly evolving.

[00:04:49] So we've grown into our name 22 years later.

[00:04:53] That's my story and I'm sticking to it.

[00:04:55] Awesome.

[00:04:56] Well, I think after all the time that I spent in Research Triangle Park, you would think we would have crossed paths sooner than we did.

[00:05:05] I think when we did, I was working at the Industry Solutions Lab here in Westchester County, New York.

[00:05:12] And I forget if it was related to the Think campaign or maybe Smarter Planet, maybe Watson.

[00:05:18] Yeah, I worked with Mike Wing, you know, who is the guy who invented Smarter Planet.

[00:05:23] And, you know, he got popularized with some work that Ogilvy, you know, did to make it a thematic, you know, for the public.

[00:05:32] But it was originally an organizing idea for, you know, how do we connect all the dots inside the business?

[00:05:39] And Smarter Planet did a lot of heavy lifting for a long time.

[00:05:42] And that was good.

[00:05:44] I mean, at one time, IBM had 430,000 employees.

[00:05:49] It was hard to know all of them.

[00:05:51] For sure.

[00:05:52] Well, it's interesting you say that because we also had a lot of, I call them toys, but we had a lot of pretty advanced software courtesy of IBM Research and some of the software divisions.

[00:06:04] But it definitely made Big Blue feel smaller when you could literally visualize, you know, your social network and your knowledge graph and, you know, expertise discovery tools and things like that.

[00:06:17] I remember early career being on a big green screen, you know, with a really thick keyboard, you know, that was connected to an 8100 that was then, you know, daisy chained to IBM 370s, you know, to make a VM network.

[00:06:34] That I could type on the command line, right, 30 years before we knew what instant messaging was.

[00:06:42] You could just type, you know, MSG space, the person's ID, and you could send them essentially a Twitter message, you know, a little or now X or threads or blue sky or whatever you use.

[00:06:55] You could send a short message to anybody that was with IBM on the planet.

[00:07:00] And we had those kinds of experiences over and over again of doing something that no one had ever experienced before.

[00:07:09] Sometimes it got popularized and sometimes it didn't.

[00:07:11] Simon was the first smartphone, right?

[00:07:14] That's right.

[00:07:15] And it didn't catch on, but, you know, it had, what was it called, features, which were like apps, right?

[00:07:22] And it could do interesting things.

[00:07:24] So, you know, I think IBM was ahead of its time in a lot of ways.

[00:07:29] I think that campaign was brilliant.

[00:07:31] And I think a lot of the concepts underneath it still hold to, you know, make things more instrumented and interconnected and intelligent.

[00:07:41] And, you know, so some of those things are still holding.

[00:07:45] I mean, it, you know, was way before we had the concept of Internet of Things and industrial IoT and, you know, sensors on every device.

[00:07:54] So I have fond memories of a lot of my experiences there, as well as some of the, you know, foresight that a lot of the leaders, not just technical leaders, but business and marketing leaders had for, you know, what was to come.

[00:08:08] I remember at one time that they had received so many patents for, you know, IoT applications that the patent department at IBM just said, don't send anymore.

[00:08:20] Right.

[00:08:21] We get it.

[00:08:22] Right.

[00:08:22] We understand.

[00:08:23] Right.

[00:08:23] Everything can, you know, transmit data.

[00:08:25] You know, we're, you know, thank you very much.

[00:08:27] So one of the things I always remember about working on a research campus was I know they were, there was, it was part of their sort of development plans and performance to make sure they were submitting, you know, patents.

[00:08:42] But what I loved about my role there was like, what do you do with those patents?

[00:08:48] What do you do with those ideas and how do you turn them into tangible, you know, assets, whether you commercialize them with a, with a client who's an early adopter and ready to be sort of a first mover in a particular area.

[00:09:01] That's got a lot of potential or it's an idea that can streamline operations.

[00:09:06] I mean, there was no shortage of innovation happening.

[00:09:11] I had, you know, all of the IP responsibility for those business units I was talking about before PC company, retail store systems and printer systems group on under the umbrella of personal systems group, PSG.

[00:09:24] And interestingly enough, you would produce a lot more intellectual property like patents.

[00:09:33] By the way, IP included things like brand licensing.

[00:09:36] It included, you know, a whole bunch of stuff, all the intangibles, goodwill that you were creating that would end up online, like 67 on the corporate spreadsheet.

[00:09:46] At any rate, one of the reasons that as one of the largest producer of patents for decades, I think I probably 25 years, IBM was the number one patent, you know, producer on the planet.

[00:10:02] It gave us the ability to say no to others, you know, like the mutually assured destruction theory was if somebody came and said, oh, well, you know, you're infringing on.

[00:10:14] I said, yeah, well, we've done some research and let me tell you how many of our patents you're infringing on.

[00:10:20] All right.

[00:10:20] Let's go to court and they would back off.

[00:10:23] All right.

[00:10:23] And so what we wanted to do is simply prevent a lot of time in motion being spent on patent trolls and litigation and things of that nature.

[00:10:33] And so the critical mass of just having a lot of patents, whether we use them or not, was an incredibly important competitive advantage for the company.

[00:10:47] So, you know, when it's a really small business, which I, you know, talk to small businesses today, you know, putting a patent out there is actually putting out in the public domain.

[00:10:59] And if you're a large enough company, you know, you say, oh, well, here's the right-hand molecule.

[00:11:04] Here's the left-hand molecule.

[00:11:06] All right.

[00:11:06] My wife used to work in the pharma and chemical industries and was in the patent department as a legal, you know, paralegal.

[00:11:17] And the fact is that, you know, when she was getting that stuff out the door, you know, you had to get it exactly right.

[00:11:25] So here, you know, I look at small businesses.

[00:11:30] I said, if you don't have the ability to defend your patent, then you should make it a trade secret.

[00:11:37] You shouldn't tell anyone how you're doing it.

[00:11:39] And then when you get close to selling your business, that's when you want to create the patent so that when you sell to a larger entity that can defend,

[00:11:50] that that's when it moves into somebody's hands, right, that can go to court and defend the IP.

[00:11:57] No, that makes sense.

[00:11:58] No, I always knew that there were ways to use that portfolio as from, I guess, offensively and defensively.

[00:12:06] Right.

[00:12:07] And to your point about sort of the medical, I remember very specifically there was a solution that IBM developed where you could do all kinds of advanced patent searches down to the chemical compound level.

[00:12:20] You could identify white space opportunity in a nascent market or things like that.

[00:12:27] So really fond memories and proud memories of my time there.

[00:12:32] I didn't last 30 years, but I did last 22.

[00:12:34] So that's something.

[00:12:36] It's still a long time, isn't it, Bob?

[00:12:39] Yeah.

[00:12:39] Half the time my dad spent at Raytheon, actually.

[00:12:43] I think he retired at 44 years.

[00:12:45] Anyway, let's move on from memory lane, Kevin, and get into some of the things that you're working on at Content Evolution.

[00:12:53] And, of course, I want to talk about the book that you just published as well.

[00:12:58] So in terms of content evolution, could you just give us a little bit of the mission and some of the cool things that you're working on and like the collabs and some of the research and stuff?

[00:13:08] Sure.

[00:13:08] As I said, I probably, you know, back of the envelope, spent about a quarter of a billion dollars of IBM's money on stuff, right?

[00:13:15] A variety of things.

[00:13:17] And some of that was market research.

[00:13:21] Did the largest market research study that had been done to date in terms of looking at how people used mobility devices around the planet and created a Procter & Gamble-like segmentation model,

[00:13:39] which is the first time it had been done in the category for what at the time was ThinkPad, right?

[00:13:46] And the other devices that we got in.

[00:13:48] WorkPads were, you know, another class of handheld device.

[00:13:53] But the point is, that was done so well that it gave me the opportunity that a professor at Duke University, John Lynch, wrote a case about it.

[00:14:03] And it got me into, you know, graduate classrooms, business classrooms around the planet.

[00:14:08] It was very satisfying to be the protagonist and be able to come in and say, oh, let me tell you how we did this.

[00:14:14] And it was half research and half organization behavior because what we had done was change the way that the business looked at this.

[00:14:24] This wasn't just putting together parts on a roadmap anymore.

[00:14:29] It was thinking ahead to what do people want to do?

[00:14:33] What will they want to do next?

[00:14:35] And how can we enable that with the things that we see coming down the road, right?

[00:14:40] So it had to be an intercept between the technology and what people wanted to do.

[00:14:46] We knew that we were already putting together devices.

[00:14:49] And you still have this with any personal computer is 80% of what it can do is undiscovered functionality by the user.

[00:15:00] They just never find it.

[00:15:02] All right.

[00:15:02] It's there.

[00:15:03] But undiscovered functionality is very difficult to get money for.

[00:15:07] You know, you actually want to make it as visible and as, you know, powerful as possible, you know, when you're doing innovation.

[00:15:18] So content evolution comes into that space wanting to bring that kind of innovation and innovators to the forefront.

[00:15:27] We're organized against listening, doing research, both qualitative and quantitative leading, which we're putting into the category of strategic directions.

[00:15:41] Lots of places can do a business plan.

[00:15:43] We're more involved in organization design and organization and end-to-end frameworks to understand your value chain.

[00:15:52] Then branding, so that whatever you're doing strategically can be compressed.

[00:15:58] All that raw material, that coal can be compressed into a diamond, something that's a shiny object in the marketplace that you can be understood by briefly.

[00:16:08] And then you can take that promise and expand it back out into experiences and engagement in the marketplace.

[00:16:16] That's intention with the brand and attention with the experiences.

[00:16:22] So listening, leading, intention, attention in a connected continuum.

[00:16:27] That's content evolution.

[00:16:28] That's what we do.

[00:16:30] And we have 30 members and 40 affiliates.

[00:16:35] So the members are actively involved in a conversation with each other and the affiliates are available as needed.

[00:16:41] Those 30 companies, all of those folks leading into, you know, the book, Collective Intelligence in the Age of AI that I wrote with Kyle Shannon.

[00:16:51] There are 30 digital advisors that we've created of those people.

[00:16:58] And we can write together.

[00:17:01] And we can write together.

[00:17:01] We create content together.

[00:17:03] We can create proposals together.

[00:17:05] In other words, both our physical selves on calls, on different.

[00:17:11] We have the ability to call on someone, even if they're not available, to add value to something because we have, you know, their digital advisor available to, you know, to talk about their GPTs that are hosted on open AI.

[00:17:28] But they're different because we have secret sauce in terms of how we train them.

[00:17:32] So anyway, that's content evolution.

[00:17:35] And all of that birthing process for, you know, for AI work is done in our content evolution collab.

[00:17:42] Oh, okay.

[00:17:42] So there's a lot.

[00:17:43] There's a lot to unpack there.

[00:17:45] Sure.

[00:17:45] So when you say digital advisors, take us through how these create, I mean, I don't need to know the secret sauce, but you've gone deep into, you know, the customization.

[00:17:55] You've created, you know, system instructions and all the things that, you know, not just surface level UI, you know, interaction with, you know, shot prompts and stuff like that.

[00:18:07] But you've gone into the weeds, you've fed it each individual person who's creating, I don't know if I want to call this a digital twin or second brain or something like that.

[00:18:18] But each one has been given samples of writing, maybe transcripts or, you know, whatever.

[00:18:26] Well, I'll let you sort of explain.

[00:18:29] A little bit of background.

[00:18:32] We formed CoLab very shortly, like a month after, you know, ChatGPT appeared in the marketplace.

[00:18:40] So by December, we were up and running and have been, you know, having meetings weekly since then.

[00:18:46] You know, the original premise was, oh, you know what?

[00:18:50] We could just go take everybody's LinkedIn profiles and we could just scrape the profile and, you know, build something like a chatbot or you said digital twin.

[00:19:01] If you look at the literature, if you look up digital twins, it really is very highly associated with computer aided design and computer aided manufacturing.

[00:19:10] So we said that's not really, you know, we use the term for a while and we said that's not really what we're, what we're doing.

[00:19:18] But I'll come back to the semantics in a moment.

[00:19:22] So we said there's a problem with that LinkedIn profile, which is it kind of goes back to, well, I used to be this and I used to be that.

[00:19:32] And I said, I don't want to talk to the person that Kevin used to be.

[00:19:36] I want to talk to Kevin now.

[00:19:37] I want to talk to Bob now.

[00:19:38] And we said, well, gee, we're really good at profiling things to create brands and experiences.

[00:19:47] Let's use the same methodology to try to bring this out from every person.

[00:19:54] So there's a 45 minute video interview that's done with one of our members that's trained.

[00:20:03] I did a lot of them myself.

[00:20:05] And then that creates both a record and a transcript.

[00:20:10] It gives you affect to understand, you know, what the person is doing.

[00:20:15] Interestingly enough, some people tried to answer that like a questionnaire and their digital advisors

[00:20:22] did not turn out to be very good because.

[00:20:26] Hey, this is William Tenka, Work to Fun.

[00:20:29] Hey, listen, I'd like to talk to you a little bit about Inside the C-Suite, the podcast.

[00:20:33] It's a look into the journey of how one goes from high school, college, whatever, all the way to the C-Suite,

[00:20:40] all the ups and downs, failures, successes, all that stuff.

[00:20:43] Give it a listen.

[00:20:44] Subscribe wherever you get your podcasts.

[00:20:46] First, you don't write the way that you talk, right?

[00:20:49] If you, you know, I want to understand, you know, I want to have a conversation with Kevin

[00:20:54] the way that I'm speaking right now.

[00:20:57] Not the one that, you know, would necessarily put, you know, pen to paper per se and write

[00:21:02] an academic paper, right?

[00:21:03] That would be relatively flat.

[00:21:05] So we said, you have to do it this way.

[00:21:08] You have to do this as a video.

[00:21:10] We want those so that in the future, if we want to invoke HeyGen and we want to sync up your voice

[00:21:18] and your image, right, in terms of responding, that we'll be able to do that.

[00:21:22] And I only talk about, that was one of the early capabilities, you know, on HeyGen.

[00:21:28] So they actually respond very authentically.

[00:21:32] They sound like us.

[00:21:34] And that's a, that's a good thing.

[00:21:35] So you consider that a very deep version of a fine tuning exercise to really get to the

[00:21:44] knowledge base of what we know.

[00:21:47] You know, we have a different kind of retrieval augmented generation or RAG, right, procedure

[00:21:54] to be able to link to here's what I've written.

[00:21:59] Here are the things that are out in public.

[00:22:01] So, so I can respond, right, in terms of chapters and books, entire books, you know, things of

[00:22:08] that nature.

[00:22:09] And as I said, we have a collective version of this where they're all together.

[00:22:15] And so I can prompt articles into existence.

[00:22:18] We've probably written a dozen articles this year that were put onto LinkedIn Pulse, where

[00:22:23] there, it was done by the entire federation with some pull quotes from subject matter experts

[00:22:30] that made sense.

[00:22:30] So that's what we ended up doing.

[00:22:33] By the way, our first product was, which is still on the website.

[00:22:39] If you go onto contentevolution.net and you go to the bottom, you can ask a question that's

[00:22:47] bothering you about business or, you know, what's happening, you know, in some organization

[00:22:54] context.

[00:22:55] And rather than giving you answers, what it does is inside of our areas of domain knowledge,

[00:23:02] it asks you the questions that you should be asking yourself.

[00:23:06] So you ask a question and it comes back with, here's what you should be thinking about, all right, to answer this

[00:23:13] yourself.

[00:23:14] We didn't want to, we weren't confident enough at the time to say, all right, we're ready to

[00:23:21] answer questions directly from, from a chatbot, you know, point of view, because this is, you know,

[00:23:27] kinds of things that we deal with are not service and support questions, right?

[00:23:33] They're more metaphysical than that.

[00:23:35] So I'm glad you called that out specifically because I was going to ask you, you know, one

[00:23:41] of the things I remember about the last generation of AI, call it analytical AI, predictive AI.

[00:23:47] But when I, I don't know if you remember this, but the IBM, the Jeopardy studio, the mock studio

[00:23:53] was in, was in my office.

[00:23:55] And so I watched this get demoed countless times.

[00:23:59] And one of the things that always fascinated me was it knew what it didn't know, right?

[00:24:04] Known unknowns.

[00:24:05] And so it would say, well, you know, my confidence level is here.

[00:24:09] And if you want it to go up above the threshold by which I would ring in, in Jeopardy, here

[00:24:16] are some things that I'm missing that would increase that confidence level.

[00:24:20] So in a way, what you just described is, it's not exactly the same, but it is one of those

[00:24:26] things that it gets people to think more deeply about maybe things that they know, but they're

[00:24:32] not bringing to this particular challenge because they didn't connect the dots necessarily.

[00:24:39] And so it sounds like what your system is doing is saying, here are some, it's not necessarily

[00:24:43] known unknowns, like here are some facts that I need, but here are some questions to get

[00:24:47] you to think more deeply about this particular issue.

[00:24:50] Have you considered this?

[00:24:51] Have you considered that?

[00:24:52] Have you looked here?

[00:24:53] Have you looked there?

[00:24:54] Is that fair?

[00:24:55] Exactly.

[00:24:56] Exactly.

[00:24:56] Our tagline was for the business, for content evolution was be intentional.

[00:25:03] You know, we thought that, you know, getting your intentions right was really, really important.

[00:25:07] And that was very durable for over 20 years.

[00:25:11] We changed it to ask better questions because the era that we're in right now is one where

[00:25:21] the people who are able to ask better questions are the ones that are actually going to succeed

[00:25:27] the most in what's emerging right now.

[00:25:31] And I'll tell you a story.

[00:25:33] My dad was in charge of executive resources for the data processing division.

[00:25:37] If you remember, you know, that era and it was the largest source, that particular division

[00:25:45] of chairman of the company, right.

[00:25:47] Of IBM, you know, for a long time.

[00:25:50] So I, you know, he had these boards in the kitchen that he would bring home in preparation

[00:25:57] for a board of directors meeting.

[00:25:58] And it was basically pictures on Velcro that you could move around an organization table.

[00:26:03] Right.

[00:26:03] Right.

[00:26:05] And as a young person, I, you know, so, so what makes one of, one of these folks better

[00:26:13] than somebody else, right.

[00:26:15] For taking a job, he said, judgment.

[00:26:18] So I'm looking for people who have good judgment.

[00:26:22] So what is that?

[00:26:23] Right.

[00:26:24] So you have to have the skills to do the job and you have to have the trust, right.

[00:26:34] Of the people that are around you and are going to be, you know, working for you and, you know,

[00:26:42] who you report to.

[00:26:43] So think about that in the era that we're going into.

[00:26:47] Skills are kind of going to be available on demand.

[00:26:51] Right.

[00:26:52] I mean, so if that's an access, right.

[00:26:54] Skills.

[00:26:55] Oh, I can get those.

[00:26:58] The trust dimension and, you know, being able to, you know, look at it that way.

[00:27:05] Well, wow.

[00:27:07] That, that one's going to, you know, really require a lot more of our time as executive

[00:27:13] development people.

[00:27:14] We're going to have to really be spending a lot of time on that.

[00:27:16] And what does that sound like?

[00:27:18] Character, right.

[00:27:19] It's, you know, it's, it's character and competence leads to judgment.

[00:27:24] I later discovered that all of the, like the Navy SEALs and the Army Rangers and the

[00:27:32] Green Beret and all that.

[00:27:33] All have that same kind of grid, but they select the leaders based on character and trust.

[00:27:42] And they leave the skills to the individuals who are part of the team.

[00:27:48] Right.

[00:27:48] You don't, you know, get someone who is, has all the skills, but at the end of the day,

[00:27:57] nobody trusts that person because you're not going to get anything done.

[00:28:00] I say that because this technology gives you the ability to have skills on demand.

[00:28:06] Right.

[00:28:07] Right.

[00:28:07] And so we're all going to have to be better question askers and we're all going to have

[00:28:13] to be developing the ability to develop our, our competence and deliver it in ways that

[00:28:20] other people can trust because that's the glue.

[00:28:24] You're still going to be in a judgment, right?

[00:28:27] Arena.

[00:28:27] And you want to build your organization based on that.

[00:28:30] And that's what a AI enabled organization has is it's really nimble.

[00:28:38] It's really agile, but the people are highly adaptable because they get the skills when

[00:28:43] they need them, but they can work with each other fluidly to accomplish things.

[00:28:50] And those are, those organizations are going to be remarkable.

[00:28:52] Right.

[00:28:53] And we can only, we're only glimpsing the beginning of, of what that could be like, Bob.

[00:28:57] I think there's some people rethinking how, how they think about leadership development

[00:29:03] and, you know, whether they're, they're promoting the right people.

[00:29:07] Do they really have the right skills when you do have that intelligence and skills on demand?

[00:29:13] What are the truly, you know, sort of durable skills that we need to be thinking about as

[00:29:18] we move forward with a, with a, you know, as our friend Ross Dawson would say humans plus

[00:29:23] AI kind of future, right?

[00:29:25] How are we augmenting our own individual and to your point, collective intelligence with

[00:29:32] AI?

[00:29:33] I put into, you know, both in public domain and my speeches, you'll, you'll find, you

[00:29:39] know, reference to this in, in the book, uh, collective intelligence in the age of AI.

[00:29:44] The idea that what you want to be able to understand at an enterprise level, you know, if you have,

[00:29:52] you know, a lot of things going on is how do we accomplish the tasks that we want to attack?

[00:30:00] And I think that this means that it's the end of the job description as we currently understand

[00:30:07] it.

[00:30:07] Right.

[00:30:08] And that we need to combine a number of different functions under the umbrella of the chief resource

[00:30:16] officer.

[00:30:17] And the CRO is not human resources.

[00:30:21] It's not IT.

[00:30:24] It's not, um, supply chain management.

[00:30:27] It's all of the above because at the end of the day, you have to make decisions about,

[00:30:33] uh, well, Kevin just retired.

[00:30:35] So let's get a, you know, let's go get the, uh, headhunters to go find, you know, or the

[00:30:41] executive recruiters to go find somebody to replace Kevin.

[00:30:46] Well, hold it.

[00:30:47] Stop.

[00:30:48] Do we actually want to do that?

[00:30:50] Right.

[00:30:51] Um, what was he doing?

[00:30:52] Do we think that that is core to what we're doing?

[00:30:56] Boston consulting group thinking, right?

[00:30:58] Is core competency analysis.

[00:31:01] Should that be inside the organization or out in the value chain?

[00:31:04] Right.

[00:31:05] Should we buy it from someone else?

[00:31:06] Should we buy a person outside the business or should we get that as a capability, you

[00:31:12] know, via software or robotics process automation, or, you know, did we model enough of Kevin

[00:31:17] when he was here, you know, that, uh, now some of that stuff is going to be able to, you

[00:31:23] know, fractionally run underneath somebody else's, you know, world.

[00:31:27] Uh, the guy from Gartner, I forgot his name, but the, you know, just did a 2025 forecast.

[00:31:33] And he said that number one prediction, you know, the corporation wants your persona, right?

[00:31:40] And that entry agreements for employment are going to say, Hey, you know, when you work

[00:31:49] here, we're going to be modeling you.

[00:31:51] Right.

[00:31:51] And so all of the legal stuff about, you know, that you've heard from actors and actresses

[00:31:58] about likeness and, you know, capturing, you know, their performance.

[00:32:04] Well, companies want to capture your performance going forward and be able to use it in perpetuity.

[00:32:10] It's coming.

[00:32:13] So that's going to change the nature of how organizations operate, what they're capable

[00:32:19] of doing and how you fit in.

[00:32:22] All right.

[00:32:22] How do you fit in your agile and you have aptitude for, for this space as opposed to you fit a

[00:32:29] job description.

[00:32:30] Right.

[00:32:30] So that's my little rant on that.

[00:32:33] It's a really, really important discussion that I think, I don't know if people are fully

[00:32:40] grasping that, but if people are paying really close attention there, they are recognizing

[00:32:45] this.

[00:32:45] I'm basically, you're basically saying I'm not doing anything wrong.

[00:32:49] I'm a high performer.

[00:32:50] And this isn't like, you know, we're worried about like time tracking and keyboard tracking

[00:32:57] or whatever.

[00:32:58] And instead we're basically, when you, to your point, you're, you've got everywhere now you've

[00:33:04] got this build versus buy versus bot kinds of decisions that you need to make.

[00:33:09] Do we have the talent?

[00:33:10] Do we even need a human, human labor to do this as we reorganize, you know, roles and the

[00:33:17] organization itself, we've got to rethink all of these pieces.

[00:33:21] But essentially, even if you're a high performer, if you're bringing in this advanced, you know,

[00:33:27] automation, we're talking about, you know, AI agents and assistants and agentic workflows

[00:33:32] and things like that.

[00:33:33] Like this is basically mapping everything that you're, you're doing and sometimes what you're,

[00:33:40] what you're thinking.

[00:33:41] Right.

[00:33:42] So everyone needs to move themselves up their own.

[00:33:45] And, you know, if you like what you do, you've still got to, you know, upskill and think about

[00:33:51] how you work with this technology so that you stay in the top quartile of people in that,

[00:33:58] in that role, in that group, you've got to continue to make yourself, you know, in,

[00:34:03] indispensable by work, learning how to use AI to your advantage.

[00:34:08] It's already hackneyed, right?

[00:34:09] The phrase, you know, you're not going to be replaced by AI.

[00:34:12] You're going to be replaced by somebody who uses AI.

[00:34:15] Right.

[00:34:15] Well, all right.

[00:34:15] So that's a, that's a low level thought right now, in my opinion, right?

[00:34:21] Because if you haven't heard it yet, right, it's coming to an article near you or a conversation.

[00:34:27] But my view is that the fitness landscape, let's use a little Santa Fe Institute language here.

[00:34:34] The fitness landscape is changing, which means that if your organization is not changing to be appropriate to, you know, that landscape,

[00:34:47] you're going to hit a cliff, right?

[00:34:50] There will be a point at which, you know, you're somebody else is doing something and you're not as relevant.

[00:34:56] And you have been depositioned, right?

[00:34:59] As, as an organization, you're not doing anything different than you were doing before, but standing still is going to cause you trouble, right?

[00:35:09] You're going to go into survival mode.

[00:35:11] Again, from the keynote world, when I deliver a keynote toward the end, I ask people, how are you responding to these changes?

[00:35:25] Automation in general, AI specifically, robotics process automation as a category, platforms as a category.

[00:35:36] How are you responding, right, to this?

[00:35:40] And some organizations are successful and they're happy and they don't do anything.

[00:35:47] I was very concerned at the beginning of this when I was talking to some of my banking contacts and clients.

[00:35:52] They said, oh, you know, we have these FINRA responsibilities and we're not going to use it.

[00:35:57] We're not going to connect any of this stuff.

[00:35:59] I said, well, boy, you're learning about it though, right?

[00:36:02] No, we don't, we're just state kind of, I said, you need to go back home and get familiar with this on your own computer, right?

[00:36:11] On your own time, because if you're not doing it at work, you need to figure this out and be ready because at some point it'll flip, right?

[00:36:20] You're already using it in your, you know, back shop to do transactions and to do financial trading.

[00:36:27] But that's been around, right?

[00:36:29] And it's kind of a black box and it's been around for 20 plus years.

[00:36:34] Get familiar with it now.

[00:36:38] You know what you should know?

[00:36:40] You should know the You Should Know podcast.

[00:36:43] That's what you should know.

[00:36:45] Because then you'd be in the know on all things that are timely and topical.

[00:36:49] Subscribe to the You Should Know podcast.

[00:36:53] Thanks.

[00:36:53] But you could also go into survival mode, you know, seeing the changes and kind of like put up defenses.

[00:37:01] That's probably not the right response.

[00:37:04] Or you can go from being successful to being significant, right?

[00:37:10] Having a 360 degree view of what's going on and changing the rules for everybody else.

[00:37:17] And perhaps even transcending the current category and going into adjacencies.

[00:37:22] That's what I recommend to people.

[00:37:24] I said, graduate from being successful to being significant with this technology.

[00:37:29] Don't let it challenge you and go into the bunker, right?

[00:37:34] You don't want to go into the box.

[00:37:35] You want to come out of it.

[00:37:37] You want to come out of pyramidal structure and take the KPI blinders off and go into the larger landscape of what's possible.

[00:37:46] And a lot of people respond very positively, you know, to that.

[00:37:50] Because they know what that feels like in their own position.

[00:37:53] And what it would be like if some of the, you know, blinders came off.

[00:37:57] On the collective intelligence piece with the way you've created the digital advisors.

[00:38:04] I'm trying to play out a scenario where, you know, an inquiry comes in or you've got a new client.

[00:38:13] There's a challenge that they're trying to solve and you want to bring the collective intelligence of your community to bear.

[00:38:20] Is it that because of the ease of access that you might as well just go get input from all 30?

[00:38:30] Or do you, has it already been pre-trained to say, based on the context and the use case and all the information that I think is relevant,

[00:38:41] I'm just going to go to these six of the 30 or something like that.

[00:38:47] Like, how do you optimize the aggregate?

[00:38:50] Because one of the things that we studied around collective intelligence back when I was at IBM was around the wisdom of a knowledgeable crowd.

[00:38:59] So you've got cognitive diversity, you've got varied expertise, you've got varied perspectives.

[00:39:06] But the ones where you've got more significant expertise should logically, you know, carry more weight if in a decision-making sort of process.

[00:39:18] So how would that play out?

[00:39:19] So a couple of things.

[00:39:22] You're triggering memory of the 18 advisory boards and advisory councils that I ran around the world for, you know, for ThinkPad, KUM, all the products for PC Company.

[00:39:36] You know, one of the things about those groups is that it would probably have 25 members, but only 15 to 18 of them would show up at any one gathering.

[00:39:46] And that's a very good-sized cohort to be working with.

[00:39:54] And especially if they've been working with each other over a series of meetings, because even though there might be competitors out in the marketplace because they're magazine editors or they're, you know, they're with one of the major industry organizations that follows, you know, information technology, blah, blah, blah.

[00:40:15] You know, the Gartners or IDCs, Foresters.

[00:40:20] Inside these groups, right, you develop trust, right?

[00:40:25] You know, we're showing them product roadmaps.

[00:40:27] Hey, you know, here's what we want to do.

[00:40:29] Well, that's a good idea.

[00:40:30] That's not a good idea, right?

[00:40:31] So that kind of cohesion is really important, right, in terms of, you know, being able to make these kinds of decisions.

[00:40:42] I know that after 20 years and bringing all, vetting all the people who came into the Federation for Content Evolution,

[00:40:51] I know the clusters that can come together and know that they'll work.

[00:40:58] More of this is, can they discover each other and do the same thing without me, right?

[00:41:03] And so that networking effect without a central node, you know, having those nodes distributed is better in terms of being able to act faster.

[00:41:15] The other thing that I would point out is there's a kind of a gateway effect that if a client comes in and says,

[00:41:22] I want you to do something for me, but first you need to sign a nondisclosure agreement.

[00:41:28] If that's the case, that means that we need to spend time working on this as humans to craft the proposal inside the templates that we have.

[00:41:43] Why is that?

[00:41:45] Because I don't want to share proprietary information with open AI, right?

[00:41:51] We already know that Samsung engineers put some stuff in there to write a report fast,

[00:41:59] and a lot of intellectual property leaked out, right, that you can prompt into existence someplace else on the planet.

[00:42:06] And, you know, they did a lockdown in terms of what you can and can't use it for.

[00:42:11] We already know that if it's important to the client that we not, you know, share it broadly,

[00:42:19] then we certainly don't want to use, you know, an AI system, right, to do this that isn't within the confines of our own system.

[00:42:31] Now, in the future, we think that what we would like to have is a small language model running behind a firewall that we own, right?

[00:42:40] And that would be connected to the content evolution knowledge graph.

[00:42:44] And those are that would allow us to do some things nimbly that, like I said, proposal creation or writing reports,

[00:42:54] you know, things that would be confidential, that we would have some confidence in being able to use that.

[00:43:00] Since we're using open tools, we need to stay with open tasks, right, that mirror it.

[00:43:08] So that's kind of the answer is we'll automate and speed up where we can,

[00:43:16] where it's not compromising something that is valuable to us or valuable to the client.

[00:43:23] Yeah, I think as things evolve, I do see a lot of use cases for small language models.

[00:43:30] But, I mean, I think costs has got to come down.

[00:43:33] Well, you're going to have to piggyback on a large language model that was trained in something

[00:43:37] and then take that frozen moment of that training and bring it inside, right?

[00:43:44] And then have it continue to learn just in the context of what we're doing.

[00:43:49] I mean, we're pretty convinced that, you know, one of the ways that we expand our reach

[00:43:59] is that the way we respond, which is authentic.

[00:44:05] We actually did a podcast, right, called Candy Ears, where a person who was running that

[00:44:12] asked questions of our digital advisors and took a sample of our voice so it sounded like us

[00:44:21] and then got us on live and said, well, I'm going to ask you the same question I asked your digital advisor.

[00:44:26] You answer it, then we're going to hear what your digital advisor said.

[00:44:28] It was uncanny.

[00:44:29] It was great, right?

[00:44:31] So it's Emily Shaw's deal.

[00:44:33] You can find the content evolution, you know, showdown, I think was the name of it.

[00:44:38] At any rate.

[00:44:39] Okay.

[00:44:39] When my wife heard it, she goes, you only rated that like seven and a half, right, out of 10.

[00:44:47] She goes, it sounded just like you.

[00:44:48] So since she's lived with me for almost, you know, five decades, I'm going with her, right?

[00:44:55] That it was uncannily, you know, authentic.

[00:44:59] So we know the authenticity is there.

[00:45:02] The knowledge graphs are being built, right?

[00:45:05] As we speak.

[00:45:06] And, you know, how we choose to share and what we choose to build for other organizations is on the table.

[00:45:13] Because that's becoming an offering right now as we speak.

[00:45:19] If you called us today, it would be custom, but we're moving in the direction of being able to make that a knowable, definable process for an organization to create the same kinds of digital advisors that we have.

[00:45:34] By the way, you know, the other thing that's really good about this, Bob, is it externalizes the voice in your head.

[00:45:44] I mean, how many times have you said, well, I wonder whether I want to do this, right?

[00:45:48] But it's fleeting, you know, it kind of goes away because you're just talking to yourself.

[00:45:55] If you do this with a digital advisor, you actually have, you know, a record of the conversation that you had.

[00:46:04] You can kind of be reflective with yourself and work things out just like you would, you know, with a trusted advisor.

[00:46:11] So what's your best counsel?

[00:46:14] Well, one of them is yourself, right?

[00:46:18] Now externalized as a digital advisor of self.

[00:46:21] It's kind of interesting.

[00:46:22] I think that we would need some psychologists and, you know, cultural anthropologists to study what's going to happen when people have more and more of this available to them.

[00:46:36] And how does this, how does this change your ability, right, to, you know, to be healthy?

[00:46:44] It might be the antidote to toxic social media, right?

[00:46:49] Is that you can, you know, have more reflective time in conversations with self.

[00:46:54] But I'm speculating.

[00:46:56] I think it's a great and valuable use case.

[00:46:59] I mean, this gets into the whole second brain kind of concept.

[00:47:02] Except, not that you want it to turn into your therapist necessarily, but sometimes you do have just this huge influx of ideas and thoughts that you can't, you know, like you said, they're fleeting.

[00:47:15] If you don't, you know, jot them down in some way and have a mechanism that helps you sort of play it out a little bit.

[00:47:22] And I think for a lot of people, it's the next generation of rich dad, poor dad, right, of being able to pass something down to the next generation that isn't money, right?

[00:47:38] That is more, here's how I made decisions in my life, right?

[00:47:43] They're documented now, right?

[00:47:45] I mean, they're knowable stories, knowable timelines of decisions.

[00:47:52] And you can start to create a digital inheritance for people.

[00:47:56] And, you know, you can pass it along, you know, just like you do, you know, physical assets.

[00:48:03] You'll have intangible assets that you can pass down that are going to be really valuable.

[00:48:08] And we have only begun to scratch the surface of what that means.

[00:48:13] As a writer, I kind of understand that and have understood that that's another form of mimetic transmission, you know, from one point to another, both in terms of time and distance and, you know, the longevity of them sticking around if they're good.

[00:48:34] It's not that the particular immediate artifact, the article, the book, right, is going to be around X number of years.

[00:48:45] But it's like citations, right?

[00:48:48] That if there are fragments that live on that are mimetic, then those are really strong contributions whether you ultimately are cited or not.

[00:48:58] And so that's how I think about, you know, the work that I do when I'm creating things is you have to kind of be self-effacing and just saying I'm adding to the total body of knowledge, right, that, you know, other people in the future will be able to draw.

[00:49:13] Most people are not posting, working out loud, as we used to say at IBM.

[00:49:18] They're not putting out a lot of these thoughts and beliefs and, like you said, decision-making processes.

[00:49:26] Like, how does this person think?

[00:49:28] Do I really know, you know, who this person is?

[00:49:31] And so I think it's a mechanism to capture some of that if people are comfortable doing so.

[00:49:37] But, you know, you mentioned LinkedIn at the beginning.

[00:49:39] Like, you're right, LinkedIn profiles, that is just a sliver of what makes this person who they are and how they've contributed.

[00:49:48] I mean, even looking back on my 22 years at IBM, my most memorable experiences were doing extracurricular kinds of things.

[00:49:57] And that's not on my, that stuff's not necessarily on my resume.

[00:50:01] It's certainly not in the job description and the job title of all those jobs I had, of which there were at least, you know, 15 jobs across those 22 years.

[00:50:11] So that's not a good encapsulation of what someone's capable of, how they think, and the current version of that person as opposed to the historical record of what this person actually did.

[00:50:24] I mean, my recommendation, you know, to people is, even if you're inside the organization now or are trying to get inside of an organization, you know, to be part of a team is you want to have a role, not a job.

[00:50:48] Right.

[00:51:10] They were not defined by a job description, that they had become legendary in some role.

[00:51:16] Right.

[00:51:17] And they were constantly called upon to do this.

[00:51:19] And I would say that that's exactly what every person needs to be able to do.

[00:51:24] Right.

[00:51:25] Do you remember Red Adair?

[00:51:27] In the first part of my career, Red Adair was the person you called to put out oil well fires around the planet.

[00:51:33] Right.

[00:51:34] He was the emergent.

[00:51:34] And so I was known during the first part as a internal Red Adair.

[00:51:41] If there's a crisis, you know, call Kevin and, you know, he will organize a team and we'll get this done.

[00:51:49] Whether it was a product recall or a, you know, whatever it was.

[00:51:56] Right.

[00:51:56] That, you know, that's the kind of stuff that I was mostly known for.

[00:52:01] And I would, they'd have to put you into a job.

[00:52:04] Right.

[00:52:05] So that you would get paid for X.

[00:52:07] Right.

[00:52:07] But how was I spending my time?

[00:52:08] I was spending my time in the role.

[00:52:10] Right.

[00:52:10] Going from one to another.

[00:52:14] And ultimately, I decided that I wanted to go on offense as opposed to be in a defensive position.

[00:52:21] I said, okay, I know a lot of the senior team now.

[00:52:24] Let me do something, you know, to start to move in the direction of creating value for the company as opposed to being, you know, defensive.

[00:52:35] And that was a great shift, right, for me.

[00:52:37] I don't know whether I would have been as happy as I am today if I had stayed defensive.

[00:52:43] Right.

[00:52:45] That was a really strong shift, you know, for me.

[00:52:49] And from what I could tell, you know, you were doing the same thing.

[00:52:53] Right.

[00:52:53] You were moving your capabilities, your interests, your curiosity into places that were both.

[00:53:02] It was like Ikigai, right, in Japanese, right, where something that the company needed, something that you were good at, something that others wanted, right, all locusts into, you know, the right place at the right time.

[00:53:18] And you invented as many positions for yourself as you took on, right, where there was a predecessor.

[00:53:25] And I had exactly the same experience.

[00:53:27] Yeah, that's exactly right.

[00:53:29] To the point where I had to rein myself in just because I was stretched too thin.

[00:53:35] I was like, if I was ever underperforming, it's probably because I was distracted by three other things that I thought I could provide more value to, you know, performance appraisal be damned.

[00:53:46] These are the things that caught my attention.

[00:53:48] And these are the things that I knew at the end of the day were valuable.

[00:53:52] I think that that's part of the theme of all of this, right?

[00:53:55] Like how you've got to reimagine the organization where people are, you're optimizing human potential.

[00:54:03] And that means putting people in areas where they're most suited, regardless of, you know, a particular title.

[00:54:10] And you've got to break down, you know, some of these silos to give people the visibility to see other areas where they can contribute.

[00:54:16] A hundred percent.

[00:54:18] A hundred percent.

[00:54:19] Yeah.

[00:54:19] So I would just, you know, say, you know, as we come to the end of our time together here, that if you've been experiencing a lot of success in your career, it's time to level up and be significant.

[00:54:36] Right.

[00:54:37] Um, because, you know, the, the fitness landscape, as we talked about before, it's changing.

[00:54:44] And so if you want to, you, you can't just tread water, you know, you're going to drown, you're going to lose, uh, the ability to, you know, keep your head above water because, you know, the water levels rising and your arms are getting tired.

[00:55:00] Your legs are getting tired.

[00:55:02] Yep.

[00:55:02] All of these systems help you create capacities that are like little water wings and other things that keep you afloat, eventually get you back on dry land.

[00:55:14] Right.

[00:55:14] And, you know, is it, are we in turbulence right now?

[00:55:18] Yes, sir.

[00:55:19] Yes, ma'am.

[00:55:20] We are in turbulence big time.

[00:55:22] Yeah.

[00:55:23] I've always kind of thrived on that because again, going back to the beginning when, when things are a little uncertain.

[00:55:31] I get called on more often.

[00:55:34] But with that said, get involved now.

[00:55:38] If you're a leader, don't delegate exploration of this, get your hands dirty, use it, right?

[00:55:44] Use the technology yourself.

[00:55:46] And if that is something that you're not comfortable with because it's been the domain of IT or some other part of the organization, get yourself a reverse mentor.

[00:55:59] Get a young person who's already doing it and spend some time with them, right?

[00:56:05] I found that reverse mentoring was a wonderful, right, capability in my career and, you know, offering it to other people.

[00:56:15] This is a perfect moment, right, to be able to embrace that again.

[00:56:20] And I'll just say that, you know, the AI that we're using right now is the result of humanity's collective intelligence.

[00:56:30] And we're at the starting point.

[00:56:33] It basically has access to the children's library, right?

[00:56:38] It doesn't have access to the really cool stuff that we know how to do that's sitting inside of a skiff or behind a firewall or behind a paywall.

[00:56:51] That stuff is still inaccessible to the way that these large language models and foundations models were built.

[00:56:57] If you pay attention, the most interesting information for your organization is your organization's information.

[00:57:06] And that has yet to be actually organized into a knowledge graph for most, you know, companies.

[00:57:11] So just start, you know, to learn what it's capable of doing.

[00:57:17] Start to organize your information so that it's machine-readable and machine-organized.

[00:57:24] And guess what?

[00:57:25] You'll be significant right before you know it.

[00:57:28] So, Bob, those are my closing thoughts.

[00:57:31] If you have any questions, glad to take them.

[00:57:34] But those are my thoughts to end our time together.

[00:57:38] I'm going to let you have the last word, as Lawrence O'Donnell likes to say.

[00:57:42] That was great, Kevin.

[00:57:43] Thank you so much for sharing all these great insights I've got my head spinning.

[00:57:47] I need to now go jot some of these things down with my own digital assistant.

[00:57:51] It was great reconnecting with you here.

[00:57:54] And don't be a stranger.

[00:57:55] We'll talk again soon.

[00:57:57] Sounds good.

[00:57:58] Thanks so much, Kevin.

[00:57:59] And thanks, everyone, for listening.