Ep 22: The Importance of Continuous Learning in the Age of AI with Chuck Hamilton

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[00:00:39] Hey, it's Bob. In this episode, I sat down with my former IBM colleague, Mr. Chuck Hamilton.

[00:00:45] He is the Chief Innovation Officer at a consultancy called M-shaped and the Chief Learning

[00:00:49] Officer at Meet Amy Innovations. We're talking about the intersection of technology, innovation

[00:00:55] and talent. Chuck shares his insights on crowd innovation. He and I did a lot of work

[00:01:00] around crowdsourcing and collective intelligence back in our IBM days. And we're going to

[00:01:08] talk about the actual research of course, effects the education sector. It can help us

[00:01:12] up to my team formation and skills development. And you know, he's helping us really

[00:01:16] think about dynamic workforce ecosystems and the value of market place in the future

[00:01:23] work. So I hope you enjoy this pop-provoking episode and thanks again for listening.

[00:01:30] Hello everyone. Welcome to another episode of LVHRAIQ. I'm your host, Bob Polver

[00:01:35] with me today. This is my old colleague, Chuck Hamilton. How's it going, Chuck?

[00:01:40] Great. How are you? I'm good. I'm good. So Chuck, I mean, yes, we knew each other from many

[00:01:45] years at IBM. But I wanted to just start with a little bit more about your background and

[00:01:52] then how you are managing sort of your dual roles right now. I guess perhaps both are

[00:01:59] fractional Chief Learning Officer at one organization and then Chief Innovation Officer

[00:02:03] at another. So could you just give us that, you know, a few minutes of how you

[00:02:08] not to where you are? A long history kind of a intersection of technology, innovation

[00:02:13] of people, where I spent my career about 19 years of that career at IBM. Sometimes working

[00:02:21] in big tech consulting side a little bit of appetite. And I have always been interested

[00:02:30] in how we can grow talent. But also, how we can pull together smart groups of people

[00:02:39] to do almost anything. I did a lot of work in crowd and that got sourced in innovation.

[00:02:46] That IBM might work on things like IBM Jam technology, but I've also was the head of the global

[00:02:52] mentoring program for IBM. I lost because I'm there. And really that goal or job was to try

[00:02:59] to get type or connection between ourselves to grow our own talent, but to help you learn

[00:03:06] from me and we learn from you. And I think he added, Georgia, the model that we've had in my

[00:03:12] request that there probably wasn't a problem we couldn't solve is where you get to write

[00:03:18] people in the right at the right time in the room at the same time or in the space at the

[00:03:23] same time. And as we started to work more virtually, in fact, that became easier because

[00:03:30] you could get people, you know, where do they work? And you didn't have to call a meeting

[00:03:36] and everybody come to our month and try and figure out how we're going to pull that together.

[00:03:41] So yeah, that's what I've been doing. I'm now Chief Learning Officer with a company called

[00:03:47] me, Danny, and it's kind of that intersection of skills building for financial sector

[00:03:52] in the new digital asset and crypto space. So what we're trying to do is help them understand

[00:03:58] the changes that are going on there and then we need a very excited bat. And I believe

[00:04:04] an idea, I started mentoring companies and see the mentoring systems coming back in my

[00:04:11] history, but startups primarily working through a couple of accelerators, currently

[00:04:17] much mentor six startups in putting them on. I work with it. And three, four of those

[00:04:24] have different flavors of AI which we're now going to talk about and do work in that space.

[00:04:30] But essentially the little there let a lot by, I see my wife got involved in that. She said

[00:04:38] that you know you can help them come and slow around the world. Why wouldn't you help them

[00:04:42] work here in Vancouver, West Coast and generally help them grow. And I thought that was a good

[00:04:48] idea. So I started figuring out how I can do that and lend my time to that. So I'm what's

[00:04:52] called executive and residents and we are and we use me as needed kind of in a fractional way

[00:05:02] we've able to drive and go to business. And it doesn't matter what the business is in terms

[00:05:08] of what the innovation space is but we usually process over and that technology, you

[00:05:13] can strategy, leadership. So that's what I do. And unfortunately I'm a little addicted to

[00:05:19] innovation. And I can't stop doing it so the matter how old or a gray hair you get,

[00:05:26] you seem to want to drive innovation and I get remote. Yeah that's fantastic. So it sounds

[00:05:31] like your first law very busy and it sounds like it's really rewarding. I mean the culmination

[00:05:38] of all those experiences that you've had, you know I can't shake the innovation bug either.

[00:05:45] I guess we're the crowdsourcing bug because I mean I think you and I probably crisscross

[00:05:51] through some of those early crowdsourcing and collective intelligence kinds of projects.

[00:05:56] I was certainly part of mentoring and reverse mentoring back in the advent of social media

[00:06:02] kind of days making sure that executives actually knew how to build their own, you know online

[00:06:07] presence and influence and engagement strategies and things like that. I guess one of the things

[00:06:12] that comes to mind when we think about like learning and upscaling I mean I feel like there's

[00:06:20] either anecdotally or just a lot of the surveys that I see people are recognizing that there's

[00:06:28] disruption coming and they're kind of deer and headlights. They don't actually know where to start.

[00:06:35] And so I guess one of my first questions to you is like as you've kept up with,

[00:06:41] you know the advancements in AI and what people's expectations are to work with it,

[00:06:50] you know on it because everyone is now just not a consumer and you know interacting with AI.

[00:06:57] Everyone has sort of become a builder to an extent as well right and so you know

[00:07:03] well I think there's any company that's not an AI company.

[00:07:06] Anyway, these things that I talked about, you have some aspect that they either thinking about.

[00:07:11] Yeah I mean I think everyone's in some stage of it. I mean you'd really be at a enormous

[00:07:17] disadvantage if you weren't at least starting to you know do your research and figure out

[00:07:23] what your strategy is going to be. I think more organizations of any size still don't have a cohesive

[00:07:29] strategy necessarily but you can't just ignore it and you can't just say we're not going to use it

[00:07:35] because it's not safe for what have you. I mean we've we've seen this movie. Right so

[00:07:42] the transformation that organization are going to go through is bigger than any prior

[00:07:47] you know transformation within a domain or across a set of processes or

[00:07:53] you know any focus area in each specific focus area because everyone is going to be impacted in some way.

[00:07:59] And so I guess I wonder how can we design learning such that we know everyone is being upskilled

[00:08:09] not necessarily at the same pace but everyone has to be upskilled or reskilled to keep themselves

[00:08:17] you know moving forward in their own you know career development. So how do you sort of think about that?

[00:08:23] Well there's so much to discuss there we could be on conversation like this every week for a few

[00:08:29] months and you still would cover it. Well I think I have two approaches I can do both with you

[00:08:37] but I want to talk to you about how we're thinking about AI back even 10 years ago at IBM

[00:08:42] how we were going to fly in learning. I want to talk to you about companies I'm working with today

[00:08:47] that are applying it and you know what on to feed food and why I think both of them are learning.

[00:08:55] And then there's a third level which is what I call need to know.

[00:09:01] No matter where you are on the learning spectrum there's always a part in your journey which is

[00:09:05] I need to know. I need to know about these pieces these parts. It never goes away

[00:09:11] and whether it doesn't matter how you delivery the learning still needs to happen that you

[00:09:17] understand the basics and then build upon those basics. So we're not doing a good job yet

[00:09:22] at even explaining basics and how those basics can be applied and making people understand

[00:09:26] okay here's what it is here's what it isn't here's what it can do or not do in that kind of

[00:09:31] stuff so that all works as long. Let's start with the story first so I'm part of a group of people

[00:09:38] at the time at IBM some of the smartest people in the world called the Center for Advanced Learning

[00:09:44] and it was all the people who understood learning at all its levels in delivery and all forms

[00:09:51] and we're planning out the learning strategies everything from leadership development for IBM through

[00:09:56] to you know what your next coding course right at the beginning and everything you're going to do

[00:10:02] sales and distribution is all part of a learning platform that had a large budget and they

[00:10:08] able to deliver and have a really effective learning program for a lot of work so we're sitting in a

[00:10:13] room and I think it was in New York. As a group of us we're all talking about well how do we

[00:10:24] speed it out how do we get things to go quicker you know the pace at which we do now will be

[00:10:30] off our course as few hours if you reach this and hands on we will people it's still very very slow

[00:10:37] and the analogy we were using was canterries matrix model where they basically put in yet

[00:10:47] a bit of knowledge into the person's head on the fly and they were flying a helicopter within

[00:10:53] 30 minutes you know they're going to know how that was going to go but as a framework it was the way

[00:10:58] we were starting to think and the analogy we used to compare was if you were an athlete and I could

[00:11:05] go to you and let's say you're the 400 meter specialist and I come to you with a new technology

[00:11:12] or a new piece of equipment or anything you can use or a method that allows you to shave

[00:11:18] 10 seconds off your time you're going to be like yes please so you know if I can save

[00:11:25] a tenth of a second after I've sometimes that's going to be enough so you know it's a lighter shoe

[00:11:31] we're going to be able to do something that can actually improve that so we started to ask ourselves

[00:11:35] well what is what is that going to be for learning people about the how I'm taking to

[00:11:39] have it? Is it going to be we're going to have to take a special drug and you know you're

[00:11:45] able to think differently and then be able to learn faster or we're going to be able to have

[00:11:49] something work with us and the consensus I think at the table mostly people that were there at

[00:11:54] time and you know for a long time you're talking about it was said we're going to have to have a partner

[00:11:59] and intelligent partner that learns with us and learns repeatedly and quickly and then be

[00:12:05] able to reframe that for us in another way and we can't be just the only source of information

[00:12:14] and the little things came along the way I think of the tool like pocket which allowed you to

[00:12:20] streamline everything you were eating and observing so you wanted to come a specialist in one area

[00:12:26] it basically started only seeing that kind of stuff of the whole web of information you could see

[00:12:32] and so with that in mind we started to push towards having a partner that would learn with us

[00:12:39] and then tell us a partner and you know looking back at that now it's first start talking about 10

[00:12:45] years ago we're still talking about it in five or six years ago and now we're talking about

[00:12:51] every day off's boat and companies are nurturing and before we move on I need to let you know about

[00:12:59] my friend Mark Feffer and his show people tech if you're looking for the latest on product

[00:13:05] development marketing funding big deals happening in talent acquisition HR HCM that's the show you

[00:13:14] need to listen to go to the work to find network search out people tech Mark Feffer you can find them

[00:13:23] rapid succession do AI system learning many of sister agents all kinds of agents that are

[00:13:29] pre-evident I see that is a really good thing because there's an overall abundance of information

[00:13:35] now and that information needs to be followed and sorted in a way we can be split back to you

[00:13:39] from the store that you're going to ask an addition we've been kind of conditioned by the TikTok world

[00:13:46] of learning I call it where you know like watch a little TikTok video a minute and a half and it shows

[00:13:51] how I can make a pizza and you know speeds of film up the video up I've never been going through

[00:13:58] a different pace but you know in a minute and a half you pretty much have the risk of how to make

[00:14:03] that pizza well we haven't been working and you're going to suck the hat for learning and

[00:14:07] development for people for a long time and we're starting to get into the more micro fit that is

[00:14:12] more like so with the AI tools to help us do in that case is streamline synthesized

[00:14:20] our condensed and pulled together if we make but to follow that analogy on a little further

[00:14:26] if I only gave you little bites it would not get diet you would have to still learn as I said

[00:14:33] some foundational material and you still have to understand what you're doing and the bites are

[00:14:37] only supplemental because every once in a while you're going to be the meaning to say yeah I think

[00:14:43] that's one of the big differences I guess between like that just in time you know kind of learning

[00:14:50] where it may even know the context of what you're doing and maybe it knows it already knows that

[00:14:54] you've got a skill gap in what you're about to try and it could you know prompt you or not

[00:15:00] you or whatever to take the you know stop you know just pause for two minutes and take this

[00:15:05] otherwise you're going to waste 20 minutes trying to figure it out and that versus like the

[00:15:09] matrix one where they didn't just feed it to you and you knew it in 30 seconds they condensed

[00:15:15] you know hours and hours and hours worth of what would take you know in his case you know physical

[00:15:21] you know practice like learning kung fu and or flying helicopter right he didn't put it nearly

[00:15:27] the hours that pilot would normally be right so yeah so one of the things that I think is a challenge

[00:15:35] is when you have to do that kind of personalized learner you want to do that kind of personalized

[00:15:40] learning because you're right everyone is coming from a different starting point in terms of their

[00:15:44] tech you know savviness or you know the domain knowledge of whatever it is and when I look at

[00:15:50] where companies are still not fully investing in L&D you know upscaling, re-scaling I don't know

[00:15:59] what the excuses are I think it was Glenn Kathy from Ron said who just put up a poll the other day

[00:16:04] or stat the other day that said there's still definitely way less than half organizations are actually

[00:16:10] investing in you know AI related you know upscaling my response to him was I hope this is because

[00:16:17] they haven't actually figured out what their AI strategy is and therefore I don't know which tools

[00:16:21] perhaps to train people on as opposed to not thinking that this is a good investment and I say

[00:16:28] that as someone who didn't grow up in HR or L&D so I know getting that investment has actually been

[00:16:35] a challenge for a long time but the fact is isn't it going to cost you a lot more to go out

[00:16:42] side the organization to try to acquire those skills and potentially like replace staff as opposed

[00:16:50] to taking the time to assess who has the right sort of mindset and capacity to learn these new

[00:16:58] skills to either progress further up in their you know current trajectory if they're on a you know

[00:17:03] flinear you know path in a particular domain or the capacity to be reskilled in another domain

[00:17:10] because you know that where that person sits now is going to be largely either automated or

[00:17:18] AI can be applied to that would otherwise cut that staff completely like these are great people

[00:17:24] their loyal or engaged or whatever but businesses business and you know we can say a 80% by doing

[00:17:31] these tasks with automation that's worked together to find another place for these people instead of just

[00:17:38] this knee jerk you know shareholder kind of you know mentality like looking how great we are

[00:17:44] looking how much cost cost we cut but look at what we just did to you know the the loyal you know

[00:17:50] engaged workforce oh no you're without a doubt I think it's worse than that I think you can't do it

[00:17:58] I don't think you're able to do it here's why the baby rumors are all looking for a lot of expertise

[00:18:02] leaving with them there's a whole you know history of knowledge and understanding that isn't

[00:18:08] going to be passed on so even if he went to look for the skills it's going to need some space

[00:18:12] which is not going to be able to find those skills so it the things as to be always constantly growing

[00:18:18] with talent we have in little ways to make people most available and make opportunities for those

[00:18:25] so even not as going to come up expensive I don't I just don't think you're going to find the resources

[00:18:31] you need we're always in a deficit from a development point of view I was happy to tell

[00:18:36] people and pushing forward the fact that people aren't adapting or using a eyes mostly because

[00:18:43] it's still early days we're in a nascent state they haven't seen crook in the application of some

[00:18:49] new things the news is that the tools are coming quickly and you are starting to see

[00:18:54] effective business spaces that will change people might like that but I used to say that

[00:19:00] in my learning game there was no technology that couldn't be used for some way in some

[00:19:08] aspect of learning I did some work with game and play I let a program at IBM called IBM

[00:19:15] like I looked at virtual world technologies we have a virtual world collaboration you

[00:19:21] and I look at the crowd technologies we have looked at every emerging technology

[00:19:26] active technologies allow people to use devices and ways of putting on the view so I don't

[00:19:32] think there's any technology that has come along that certainly is as transformative as the one

[00:19:39] we're about to look at that wouldn't be used by smart people trying to make that a piece of

[00:19:43] smart so I think to you answer your question is I think it's the former of your pieces there

[00:19:50] that most people just don't know what they can apply but once they see the value they will be

[00:19:55] applying and they're not it's not like a fear of implementation there's a small percentage of that

[00:20:00] but I don't think that's the main case yeah there were some recent articles around

[00:20:08] should we really be looking for learning workers and not knowledge workers if knowledge is

[00:20:14] always at your fingertips with generative AI you need to a lot there because you're see even

[00:20:19] IBM announcing in the last year that no longer is a requirement to have a degree to be an IBM person

[00:20:27] it's a are you able to learn are you able to grow are you able to transform you know do

[00:20:33] have some skills in given areas we used to use a model help to each shape and you know a lot of

[00:20:39] people would be shaped and they had some depth they had some breath and really it doesn't matter

[00:20:44] what your background is if you can apply and you can help to grow and learn I taught in the master's

[00:20:51] program and you know have to come into the master's in the media after they had done their undergraduate

[00:20:58] and they came into all kinds of undergraduate groups from anthropology to the history to

[00:21:03] whatever but realize they weren't getting job opportunities with their in public court career

[00:21:09] and so they have dognet that and we would just we'd love that because anything it doesn't

[00:21:15] are where you come from my first degree was our different design and I get into technology

[00:21:19] of second flight and then mother degree and I think they'll be to merge those things and learn

[00:21:26] new so it's basics we have the learning growth that's what we want so we need good learners

[00:21:32] and knowledge workers is I think the way it was applied in the past knowledge worker was

[00:21:38] more working you know labor really well as we're working kind of a white collar and I acknowledge

[00:21:46] that we even know how to serve crossing all the time and maybe

[00:21:55] you know I've been concerned about the different sort of generations in the workforce and certainly

[00:22:02] I empathize with you know college students trying to look at their job prospects

[00:22:09] recent graduates just not not sure what you know their their future holds maybe they haven't really

[00:22:15] because universities maybe haven't embraced AI yet or at least in a lot of majors and

[00:22:22] logic programs you know they have not been prepared just not through necessarily the

[00:22:28] vault of themselves or the university just because this came out as pretty fast it's only you

[00:22:33] know during a day I only entered our vocabulary in the last year and a half so but it's an interesting

[00:22:40] situation now because if you are now all of a sudden putting and then the flip side of that before

[00:22:48] I get there flip side of that is you know gen X there's like us who have a lot of work experience

[00:22:53] you could say well you know we we should be able to work until we're you know well past you know

[00:22:59] official retirement age yeah quotes air quotes there and just because we've accumulated so much

[00:23:07] you know knowledge and what have you but now you know with people saying so these studies I was

[00:23:17] saying knowledge is no longer scarce even potentially institutional knowledge if you set up your programs

[00:23:24] and your data appropriately where AI can access it and learn from it then AI skills become more

[00:23:32] important than the knowledge and experience of some of the more tenured you know parts of the

[00:23:38] of the workforce and then maybe the pendulum swings back to saying well okay well if you're

[00:23:44] using turn of AI you know throughout your higher education you know just graduating with no

[00:23:51] work experience you could actually combine turn of the AI you know inside a company with

[00:23:57] your ability to use it to be productive and effective and to make data informed decisions and

[00:24:05] you come out of there as it you know 22 year old you know ready to roll yeah sure and you can get

[00:24:12] these experiences and you know just under tooling or arsenal um uh tools we bring to the table and

[00:24:18] because we tell our graduates we're teaching them this is going to bring more to table this brings

[00:24:22] us to an interesting topic around mentoring which I mentioned earlier at the global mentoring program

[00:24:28] so one of the ways now that I became a fractional at a guy where you can use my brain in pumps or

[00:24:34] my time people do things like we've been doing a thing called two in a box so two in a box

[00:24:40] only the pyramid but basically a person like me with some new person is coming in the organization

[00:24:45] we're going to cross following our skills we're going to tackle problems in proper way and

[00:24:54] and solve that problem and or work on problems that and we can learn from each other I see the

[00:24:59] reverse mentoring is very valuable as well from the repersoned perspectives of coming and what I need

[00:25:04] to understand about how they see the world and why they see that way so the building to have a person

[00:25:10] come work with a tender person and that's a great upskimming model and we can do that with

[00:25:17] well and there's many AI layers that could fit around that but very first one would be accurate matching

[00:25:25] of skills between people and you have really for an organization to know that I've got ball

[00:25:32] just started and I've got to do some you know brain depth with them and they have cross with

[00:25:37] the skills and they can do more work together and then we have got a match that kind of depth

[00:25:42] of understanding is very rich I mentor a company of picnic brain and basically it's got a series

[00:25:52] of brains you can book in intervals from 15 minutes to a month and you know I get booked and

[00:25:59] all the time for different foods and time and through the CEO Maxi Penningham is you know just driving this

[00:26:08] attitude of we're going to connect the world's people we're going to connect the world's

[00:26:11] brains and that's a fantastic model I didn't have that at my disposal as a full set when I

[00:26:17] was an IBM I would have liked to have better ways to connect with brains but the ability to

[00:26:22] find those connected brains is going to be a phenomenal leap for me so I think that's a great

[00:26:30] opportunity and again you can see it starts with let's get them to keep connected and then

[00:26:37] let's understand what they know and then drive out of. I took your advice I did create a pick my brain

[00:26:44] profanal up I'm up there well hopefully people if you're promoting yourself I'm going to

[00:26:52] help people be following up and it's a benefit for all people this is probably the old

[00:26:59] evaluation that we're working with for the social and stuff. Yeah I think my experiences with

[00:27:09] some of these like gig you know freelance platforms has been I'll just say suboptimal but

[00:27:17] I guess I look at this space from a couple perspectives certainly I have you know some self-interest

[00:27:23] there as an independent advisor and solopranoar you know I think that I would be a good fit for some

[00:27:30] of these you know fractional you know projects and short-term projects but I also think about it

[00:27:36] you know again going back to the ZABM days. I mean one of my if you remember the Biz Tech

[00:27:40] program people would propose an idea someone would say you know as an executive I will

[00:27:47] I'll give you a 50k to fund this and you guys put a team together and go build it let me know how

[00:27:53] it goes and so you know when you would apply to be you'd see the description you'd say we're

[00:27:59] looking for people with these skills and they would hire people not hire but you know I mean it was

[00:28:04] just like this extra curricular project right so if you had your manager's permission you could

[00:28:08] apply and then be part of this team either on the business side but it was all often is today

[00:28:14] hiring these individuals without necessarily assessing how these people might work together

[00:28:21] as a team I mean yes you have your list of skills and you can look across you know six different

[00:28:27] office descriptions and say let's make sure we've got a balance here I must make sure that

[00:28:33] we've got everything covered so there are many gaps but you didn't look at you know person

[00:28:38] out he didn't look at work style and leadership skills and things like that it was just kind of

[00:28:43] this rough cut at it right but today yes I mean that kind of thing can still happen and maybe

[00:28:49] you know these internal talent marketplaces can help to facilitate you know some of that work

[00:28:54] but I still don't know that they have the sort of team intelligence to be able to look at that

[00:29:02] to get all at the same time or let's say okay we're going to go experiment with Gen AI we're

[00:29:08] going to grab an engineering director and a couple devs and you know a PM and maybe project manager

[00:29:16] whatever and we're just going to do like little scunk works thing well you want to go through

[00:29:19] the similar exercise right you want to say we're going to spend this all up but let's use AI to build

[00:29:25] this AI team and let's try to look at complementary skills and not personality but like psychometric

[00:29:31] kinds of things behavioral kinds of things that might say give you a better sense of whether

[00:29:37] these people are going to be working well together because that's going to drive the success

[00:29:43] of the project and it's going to in some ways mitigate some of the risks you may otherwise have

[00:29:48] by trying to do it you know hiring one by one yeah maybe they're going to personally on that team either

[00:29:53] and then you're not going to get ideas of the outside the box and maybe you're going to have

[00:29:57] you know people that only work in self-western US and never work anywhere else it's often the

[00:30:02] case the bottom of the weeks and grads another people work with they never been on team they

[00:30:08] know don't know team dynamics and sort of less they've been growing up in sports related teams or

[00:30:13] other teams that are one of the other companies I mentioned are a weapon and they try to

[00:30:20] a weapon into which will find the following century given experiences in the context of where they

[00:30:25] are most of those are all the soft skills the team skills the growing skills and so on get them

[00:30:31] before they graduate because it's not often a thing you're not in the university department

[00:30:36] out of teams form so I agree with you the magic comes not from a pool of a bunch of really smart people

[00:30:44] but from a pool of smart people who are willing to work on and affect it for this team

[00:30:50] and get a product out of the division up and so often I think you probably share this and

[00:30:59] this to be with big company that we work you know and you're on a good team you know when the

[00:31:07] team has got that same and I wish I could capture and put it in a bottle but I don't know

[00:31:14] what it is exactly but there's chemistry there's similar perspectives there's

[00:31:21] things that they've done with value that they can bring to the project but whatever reason

[00:31:27] a rich team just sort of happens and this is not new everywhere you look in the world we're

[00:31:35] right in the middle of the semi-pop playoffs and often teams that win there are maybe

[00:31:43] enough the best from a skillful on either their best team and it really is best teams at

[00:31:49] when I wish I knew how to capture the magic every time that I know that you just

[00:31:55] see it's I think we've had there had a poster recently around like HR money wall

[00:32:00] that it really is what it's all about I mean you may someone hiring manager

[00:32:05] who I was going to leave the team maybe like oh you know where to find this guy or

[00:32:09] how do you had to pick him or whatever and it's just like it's a large part what the data is

[00:32:16] telling us you've got to trust your data and you've got to gather other you know signals that

[00:32:21] you may not have been gathering before so put those those feelers out and you've got to combine

[00:32:26] some level of you know human intuition I suppose I mean there should be still a human

[00:32:32] in the loop don't let you know an AI completely do all the work but I do think that there's

[00:32:38] there's a lot of human bias that would prevent that team from otherwise forming if you

[00:32:45] you know allowed people to you know free-rande to push back or they're the part of that is

[00:32:50] that we've been growing on a calendar of days meets months availability you know you can talk

[00:32:56] to a person you want to talk to get on your team because they had you know unless you were prepared

[00:33:03] a book on four a week and availability was you know months away you couldn't do that so often

[00:33:10] teams get formed because they were available the right time and theoretically they have the right

[00:33:17] skills and so on and so now I'm not talking if you think a little bit more fractional

[00:33:24] all of a sudden knowledge and be available in team new to the time and there was you know the

[00:33:30] old attitude you wanted to find out about a given topic take you know your favorite develop

[00:33:36] or out for pizza one day or your favorite the leader of the pizza or whatever and you learn more

[00:33:40] now with that person then you never get to do and and I think that that is now an opportunity

[00:33:48] that we've never had to solve something there by better network and we've been through some

[00:33:52] better network still. I guess one of the things that I think about is even if you had all the

[00:33:59] intelligence to do it so you had all the right data points and you had all the integrations with

[00:34:06] extended workforce platforms and gig platforms and obviously your internal availability maybe

[00:34:14] maybe that's in a talent marketplace but not everyone has an internal talent marketplace

[00:34:18] but even if you connected all of these systems and the data was all there and you had the intelligence

[00:34:25] one of the things I think about is that are the intangibles around

[00:34:31] culture of an organization and whether the workforce would feel some animosity that certain

[00:34:43] you know, rise, you know, roles wound up going to you know someone who just basically parachuted

[00:34:50] in because you know some AI said to go in that direction for that particular set of

[00:34:57] of tasks or whatever but I just think about like companies it's just how they would handle

[00:35:04] the cultural things, the the engagement workforce engagement and just how that all

[00:35:11] you know plays out any thoughts on that. Well that's it. It's one of the key examples

[00:35:17] why humans will never be completely displaced by any of the technology because humans make

[00:35:22] some social and cultural decisions that are maybe better for the organization company and

[00:35:28] the people that they know where you know the gene logic is never going to be wrong with the

[00:35:33] code. So I think the first thing is what the organization deal with that culture and make those

[00:35:39] choices and don't be led by the quality of that. So that said though the people that we've been

[00:35:47] hanging around with in the open talent space are starting to argue that it's okay I never wanted

[00:35:56] to be your 19 year veteran of IBM. I wanted to be in this role and I need to be building my skills

[00:36:05] like a portfolio. I'm going to do a little bit of work for this organization a little bit

[00:36:09] work that organizations. So I'm going to grow my portfolio such that I am more

[00:36:15] indispensable, more valuable to all organizations by doing that. In addition,

[00:36:22] there are after some different work life balance or what my friend Dan Pontichak talks about

[00:36:28] the building of bloom is very bar and in the right way. And I think people are shifting their

[00:36:36] values and what they want to do. When we post COVID era, you know some 60% of people in the middle

[00:36:44] of work environments are saying I'll go back a little bit to the I'll be hydrated if you want.

[00:36:52] But I never going back to what I was whenever in the full time work. Then 15% have said

[00:36:57] I'm never going back ever to a full time in office in this situation and want to be in a virtual

[00:37:04] and a more collider mode. And then the other 15 plus percent on the other end is said I must go

[00:37:10] back because they need the off-senvironment of the physical space for the building. So I think that

[00:37:17] the work dynamic has changed so I don't think it's going to be as prevalent, not going to be a

[00:37:26] people losing opportunity for what can consider career track positions. And they would choose to go

[00:37:35] elsewhere and still still also always being in skills coming to YouTube there. The model I've given

[00:37:42] my own company and working with the C2 here is the saying let's go 3070. We're 30% of our employees

[00:37:53] people retired for full time roles needing groups of 70% are flexible and open talent and

[00:38:01] be like the one of them is going to that work. And by doing that it seems to be always

[00:38:09] available to the new skills coming into the pool and not new ideas and yet but also opportunity

[00:38:14] going and we're looking at our research and organization and that's sniffing it share because

[00:38:20] you know would have been 90% we were at when I was at IBM what 400,000 plus employees at 150,000

[00:38:30] contractors so I would say that the board of full time were track mode. So those three dynamics

[00:38:40] are changing all the time plus you've got new and evolving technology that are opening up and

[00:38:46] everyone plays the humans in the system completely then we're going to be fine.

[00:38:51] Yeah I guess there are a lot of dynamics at play right because if you were doing social listening

[00:38:56] or whatever and then please you saw like it was this you know groundswell of back last year or whatever

[00:39:03] I mean you know some of that work may go to maybe automated or you know go to AI anyway right

[00:39:12] but I guess you know just emotionally I'm sure people just have you know it's still a

[00:39:18] not great reaction if they're on you know livelihood is at stake but still to lose it you

[00:39:25] know I don't know what's worth losing your job to you know someone who hasn't been loyal to

[00:39:30] to the company or loyal to or losing it to you know some piece of technology that you know

[00:39:36] just got implemented without your you know nobody asked you there you know automate that piece

[00:39:42] of work but well you you said earlier in conversation we've been here before the further story

[00:39:48] I have lived a lifetime in this space and I've seen technology come that and everyone

[00:39:56] we're all been replaced and if there's no work there's nothing you thousands of people will be

[00:40:01] going to go to hundreds of thousands you could go to a place by some technology I think

[00:40:07] and it's just never as happened it's never done that right in fact they don't come up

[00:40:11] pull off the two weeks in areas we've never seen before up till about two years ago

[00:40:16] we never saw a position advertised for a prompt engineer and then a few years you might not see it

[00:40:23] anything anymore and you might not see it and a couple years of prompt engineer might not be there again

[00:40:28] so the point is that it's at an evolutionary thing ever since in discussion from the motorized

[00:40:36] first motorized vehicles to now whether it was electricity or whatever came along there was always

[00:40:41] an instrument that they're all going to be replaced by a machine of some sort and they're just

[00:40:48] whole growth opportunities and work that I can't put labels on anymore I did a TED Talk

[00:40:54] a while back on the future of work and talked about you know different futures I could see coming

[00:40:59] for work and one of the things I mentioned in that TED Talk was right now we can sort of say

[00:41:06] label the job categories like you mentioned a team and you said a project manager developer

[00:41:12] you know we have a couple of years you have somebody who's a bead area whatever so we had these

[00:41:17] roles I think it's harder than we harder and harder to predict what those roles are going to be

[00:41:23] and to educate people for a specific role so you know we have to really build learners and

[00:41:30] we love to learn and as I mentioned I'm kind of addicted to the innovation process but the

[00:41:37] other thing I've been addicted to my whole life has been learning and there's I just never

[00:41:41] and stop learning I want to continue doing as long as I can I just there's no area that I

[00:41:49] don't want to go off and explore it since and that's what you've got to build you got to build

[00:41:53] people who want to work. Yeah I guess I'm curious about your stance on like using block chain for

[00:42:00] like portable digital you know credentialing and the future of of that when it comes to

[00:42:09] you know hiring sort you know sourcing talent identifying talent and validating you know

[00:42:15] those those credentials because it's really a kind of a disaster to that even with some pretty

[00:42:20] slick tools today but some of them are questionable on their responsibility ethical you know

[00:42:26] front well more chain is going to change all their credentialing to change your medical record

[00:42:32] it's going to change everything you think about in every industry here's a number of really great

[00:42:38] resources talk about all the different industries that are affected by block trade I mean if

[00:42:43] working in two technologies right now working block chain they are because they're transforming

[00:42:48] the way the world thinks I think all of our vaccines and the vaccine you know histories

[00:42:54] of measles and everything you do when my mother passed away kind of lost my record of what

[00:43:00] my vaccination history is that all of that stuff needs to be on the block chain it's a smarter way

[00:43:06] to do it and more of it and of course the big thing that's happened with web three is

[00:43:13] money is moving the block chain and finance was the blockchain and and and that's a smarter way

[00:43:19] of dealing with a lot of money as well with others on awful lot of money lost in the

[00:43:24] tri-fi world that never gets explored and found so it's interesting other companies I met are

[00:43:36] watching they are crossing over quite quickly one of the companies called load LODP and they

[00:43:44] started off as a crypto mining company doing traditional crypto mining work but what they started

[00:43:51] realizes that there was a whole load management problem when you request you may that need to

[00:43:56] shift AI makes huge load requests for new process of power and energy and if you could

[00:44:05] convert those and move them around in a smart way and tell you to move those requests around

[00:44:11] you can really change everything so they're they're leveraging the concept of the club chain

[00:44:16] works and AI and then smarter load management for the whole thing and again with that company

[00:44:23] that exists even five years ago no it's a new one in the space watching is going to be

[00:44:32] always in the background where people don't understand it it's okay it's just a what better we

[00:44:37] imagine the first time I realized that everything could be managed on the blockchain

[00:44:42] when a company approached me to be a mentor and they were tracking salmon from a boat

[00:44:48] to the plate and I didn't know that the outside of a Sam skin is like a fingerprint almost

[00:44:55] and they can track that fingerprint from time and through its delivery process and that Sam

[00:45:01] arrives with like we can say that Sam and came from that boat and that fishing where was happening

[00:45:06] and I went what is not going to be on the blockchain that's fascinating talk we could

[00:45:12] we could talk for a couple more hours but I'm gonna wrap it up with one final question for you

[00:45:18] when you think of an AIQ what do you think of in terms of what people need to to do to get

[00:45:24] turn as smarter around the space well we've covered some of this today but the first one is

[00:45:31] I said there's AI basics the AI understanding AI fundamentals training and development that needs to be

[00:45:37] done around it which should be creating the first 15 modules of what the heck is AI and what is

[00:45:42] it you have to introduce concern areas of safety and understand how you're going to mitigate

[00:45:47] and do those areas that's kind of a learning process as well I guess in summary you know

[00:45:55] my way of thinking of intelligent application of any technology is no something about it

[00:46:02] and learn and play with it what I really liked about some of the early applications

[00:46:09] the chat you can see and other things were going on it was there go play with this and understand

[00:46:14] no doing experiment before you start criticizing what it is and isn't you'll find out what

[00:46:19] you end you know mid journey type activities and generating video and generating videos figure

[00:46:25] of what you can do and then have that discussion later about oh what's what's the concern about

[00:46:31] this and unfortunately there's a lot of hype and on both hands the fear spectrum and the positive

[00:46:39] app you should expect them so what we've got to do outside so that's what I think about

[00:46:44] when I think of the IQ and as a learning person this is just a fascinating space

[00:46:52] let's go off and figure out how you can learn in this space and use the tools to help us learn

[00:46:57] faster so yeah you can build your IQ pretty quick excellent which was awesome talk to you as usual

[00:47:06] thanks for dropping some great insights there thanks so much for inviting me and you don't

[00:47:12] need a fractional guy with do something oh yeah absolutely sounds great all right thanks to

[00:47:19] I'll just leave all thanks everyone for joining