Understanding and Power Skills – Keys to AI Success: Interview with Rich Maltzman, Boston University AI transcript and summary - episode of podcast AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion

Go to PodExtra AI's episode page (Understanding and Power Skills – Keys to AI Success: Interview with Rich Maltzman, Boston University) to play and view complete AI-processed content: summary, mindmap, topics, takeaways, transcript, keywords and highlights.

Go to PodExtra AI's podcast page (AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion) to view the AI-processed content of all episodes of this podcast.

View full AI transcripts and summaries of all podcast episodes on the blog: AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion

Episode: Understanding and Power Skills – Keys to AI Success: Interview with Rich Maltzman, Boston University

Author: AI & Data Today
Duration: 00:19:14

Episode Shownotes

Data is integral at any organization. However, data on it’s own doesn’t provide much value. If we want to get more from our data and AI systems, and if we truly want to get machines to become more intelligent, we need to bridge that gap with at least some understanding

of those patterns. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer interivew Rich Maltzman. Continue reading Understanding and Power Skills – Keys to AI Success: Interview with Rich Maltzman, Boston University at Cognilytica.

Full Transcript

00:00:01 Speaker_00
The AI Today podcast, produced by Cognolitica, cuts through the hype and noise to identify what is really happening now in the world of artificial intelligence.

00:00:10 Speaker_00
Learn about emerging AI trends, technologies, and use cases from Cognolitica analysts and guest experts.

00:00:22 Speaker_03
Hello, and welcome to the AI Today podcast. I'm your host, Kathleen Walsh.

00:00:26 Speaker_01
And I'm your host, Ron Schmelzer. You know, one of the interesting things you might have noticed for those of you who've been listening to our AI Today podcast for a while, and this is our seventh season, Nick, we've been doing this since 2017.

00:00:37 Speaker_01
You're like going to be getting close to that 500 episode mark not too long from now. And what you might have realized is that maybe in the very beginnings of our podcast, we were talking a lot about the core ideas of what is AI? What's it good for?

00:00:51 Speaker_01
We still answer that question a lot. Still, what is AI good for? It's a revisiting question we get. And a lot of the concepts, we had a huge glossary series and a lot of use case series.

00:01:00 Speaker_01
But the thing that we keep coming back to, especially with AI, when we're looking at making AI work into today's real world, is that a lot of it has very little to do with the technology elements of it. Those things are changing very, very quickly.

00:01:14 Speaker_01
A lot of the things we've been talking about are process and people. How do we change the way we're doing it? How do we go about and run AI projects? Of course, that's really important. But then how do AI systems change the way that we work?

00:01:27 Speaker_01
Because it's in changing the way that we work and in changing the way that we use AI in all those things, that's what makes AI useful. Because if it doesn't have any impact in what we do and how we work, then it's kind of a toy.

00:01:41 Speaker_01
And that's been sort of the problem, I think, with AI so many years is that it's been that interesting idea that's got some very unique applications. But for most people, it hasn't impacted their life. I think things are starting to change, right?

00:01:54 Speaker_03
Yeah, I like that, Ron. We don't want it to be a toy, we want it to be a tool. So we always say that AI is a tool.

00:02:01 Speaker_03
So we love to get interviews from people in industry and thought leaders because we really like to get that unique perspective and all those different perspectives on AI today.

00:02:13 Speaker_03
We're so excited to have with us today, Rich Maltzman, who is Master Lecturer at Boston University Metropolitan College. Welcome and thanks so much for joining us.

00:02:23 Speaker_02
Great to be here.

00:02:25 Speaker_03
We'd like to start by having you introduce yourself to our listeners and tell them a little bit about your background and now your current role.

00:02:31 Speaker_02
Sure. Thanks very much. So the very short story is that I have 40 years of engineering and project management experience at the company now known as Nokia, but when I started, it was called Western Electric.

00:02:45 Speaker_02
And it culminated in being a PMO director at Nokia. But in parallel, even since the 1980s, I've been teaching at the university level, mainly in project management. And now, as you said accurately, I am a master lecturer at Boston University.

00:03:00 Speaker_02
And there I'm both writing and teaching a suite of project management courses and laboratories. and I'm representing here for my three co-authors on a book we're working on. All of them are PhDs. I'm the lone non-doctor.

00:03:15 Speaker_02
I'm Howard Wolowitz, to the Big Bang Theory, if you know the reference. Dr. Laura Donna Abramo, Dr. B.J. Conabar, Dr. Dave Silberman, all adjunct or full-time faculty at Boston University's Met College.

00:03:29 Speaker_02
We're really passionate about making sure that AI is properly used, and that word will come up again over and over again here, properly used in education.

00:03:38 Speaker_02
And since our students are mostly in or about to join the workforce, that will be used properly in projects to make projects more successful.

00:03:49 Speaker_01
Well, that's really important, especially a lot of those things. AI is definitely impacting education. We've had quite a few conversations about that with folks in the education space.

00:03:57 Speaker_01
Of course, on the one hand, changing the way people are learning, whether or not they're paying attention, things like lecture summarization and notes. But it brings up so many other opportunities.

00:04:06 Speaker_01
Like, OK, well, maybe one of the conversations we've had is, do you want people's attention or do you want their retention? And what is more important when it comes to education? All sorts of conversations about that.

00:04:18 Speaker_01
I really like how you talk about entering the workforce as well, because at the end of the day, you want to apply what you learn to the real world.

00:04:24 Speaker_01
That's supposedly what you're getting a learning and education and diploma for is, at some point, applying what you learn, which doesn't, we understand, always happen.

00:04:33 Speaker_01
So on that note, you know, I think, you know, other things you're doing is you're taking a lot of your experience and your expertise, and you're going to be putting it soon into a book.

00:04:42 Speaker_01
that's really going to be focused on AI, project leadership, and power skills. So maybe you could tell us a little bit about what you have in mind for this upcoming book and your motivation and some of your thoughts about that.

00:04:53 Speaker_02
Yeah, good question. The book is tentatively titled Project Leaders in the Age of AI, Elevating Project Leadership with AI and Power Skills. At the whole root of our book is two really short one-syllable words with a slash in between them, both and.

00:05:11 Speaker_02
And it's both and in opposition to either or. In project management, we've had this long, ridiculous, worthless battle between Agile and Waterfall.

00:05:22 Speaker_02
We think, anyway, all of us, that it's kind of a useless battle that people really will take sides and, rrr, this side is best, this side is best. It's either Waterfall or Agile. No, no, it's both and. AI is about both humans and their use of AI.

00:05:39 Speaker_02
Just like we say with AI, with Waterfall and Agile, you know, use what works. Just use what works. Here, it's that combination.

00:05:47 Speaker_02
And we think there's significant interplay between these power skills, which I'll talk about, and AI that will make a much better outcome for project leaders.

00:05:57 Speaker_02
One last point here, I think it's like, and for the techies on your show, they'll like this. It's like a laser.

00:06:02 Speaker_02
If you know how a laser works, it's about light bouncing back and forth repeatedly so that you get much, much stronger, more cohesive, same frequency, same phase light out of it. And you get that nice beam that you can point and confuse a cat with.

00:06:18 Speaker_02
So it's that back and forth between the human and AI that makes the difference, a pure, more kind of altogether output that's more powerful than we put in.

00:06:28 Speaker_02
If you compare that to a flashlight's output, that's kind of dispersed and all different colors of light, that laser is one color, it's focused, it's more powerful. That's what we think this is about.

00:06:40 Speaker_02
It's what AI can do for you if you do it right, and it's about the both and. Some bottom line things about the book. There's two things we really want to push for which we think AI can be a real ally.

00:06:53 Speaker_02
Project leaders who use AI the right way can build their power skills and have more successful projects that deliver lasting value, not just a successful ribbon cutting ceremony, but something, a building, a service, an application that is successful in the longterm.

00:07:11 Speaker_02
To paraphrase our book, it's not about incorporating AI into existing workflows or replacing humans with machines. It's about fostering a dynamic and synchronized environment where AI and humans are harnessed together to drive project success.

00:07:28 Speaker_02
AI, we know this from your podcast, thank you. It can process data, identify patterns, predict next words, provide insights with unbelievable, unprecedented speed and accuracy.

00:07:40 Speaker_02
But humans bring unique power, skills, ethical considerations, and uniquely human thinking to the table. And we think that can be amplified and augmented like a laser if we use AI properly.

00:07:54 Speaker_03
Yeah, I think that our listeners will like that analogy. We always like to use analogies. It helps people visualize things. Now, you talk about the power skills.

00:08:03 Speaker_03
So maybe for our listeners that might not be project managers or know what they are, can you just, you know, quickly go over what the power skills are and how do they contribute to project success?

00:08:13 Speaker_02
Sure. I would have to say having been in PMI for a long time, that I don't think many project managers know what could recite these 12 power skills. So here they are, and I'm gonna read them off, just the titles of them.

00:08:30 Speaker_02
I'm tempted to read the descriptions, but just the titles, because that's really where it is at. And I'm gonna read them in the order in which they are considered to be prioritized for the first five and the rest alphabetically.

00:08:42 Speaker_02
So communication is numero uno. Problem solving, collaborative leadership, strategic thinking, and relationship building. These are the top five.

00:08:53 Speaker_02
Then the remaining ones in alphabetical order, accountability, adaptability, discipline, empathy, I think you've talked about that on the show, for-purpose orientation, future-focused orientation, and innovative mindset.

00:09:06 Speaker_02
All of this comes from PMI's Pulse of the Profession 2023, so this is relatively recent. The subtitle is Power Skills, Redefining Project Success.

00:09:16 Speaker_02
Bottom line here, in that Pulse of the Profession report, they surveyed 3,500 project professionals, and they showed that the 10 drivers, key drivers that make projects successful, things like low scope creep.

00:09:29 Speaker_02
So if you're a project manager, you know about scope creep, and that's something you don't want. It's kind of unconscious accepting of new features and functionality that you didn't agree to. but you're tempted to take on anyway.

00:09:41 Speaker_02
And high benefits realization management maturity. These are factors that are considered successful. Studies have shown that. But here's the catch. They're connected to the power skills.

00:09:51 Speaker_02
The studies show that organizations that prioritize power skills have these 10 drivers that in turn yield success. So do you want a couple of examples?

00:10:04 Speaker_01
Yeah, we loved, especially if you have stuff in the real world, that's just fantastic.

00:10:08 Speaker_02
This is real world. These are real statistics from this report. So maturity and beneficial realization management.

00:10:15 Speaker_02
So in other words, thinking past the end of the project to what it is that the project was all about, instead of just trying to be on scope, under budget, and within timeframe. That's the number one driver of project success, believe it or not.

00:10:28 Speaker_02
Project managers, leaders, I would say, who are focused on that end game. For organizations that put a high priority on power skills, 57% of them report high BRM benefits realization management maturity, 18 low BRM maturity.

00:10:46 Speaker_02
But for those that put low priority on project power skills, the picture is almost upside down. 18% report high BRM maturity and 49 low BRM maturity.

00:10:57 Speaker_02
One more example, and a key one that most of you should be familiar with, especially those software developers out there who are familiar with CMMI. So a measurement of software development maturity. Project management maturity is also a thing.

00:11:11 Speaker_02
And in organizations that put a high priority on power skills, 64% have high project management maturity, and 11% low.

00:11:20 Speaker_02
On the other hand, again, almost upside down, organizations that place a low priority on power skills, 32% report high project management maturity, and 40% report low project management maturity.

00:11:32 Speaker_02
In our book, there's one subsection where we walk through each of those power skills, carefully showing and giving examples of how AI can interplay with you as a project leader to improve those skills. You want an example of that?

00:11:47 Speaker_02
Why will I say no to that?

00:11:48 Speaker_03
I know, of course we want more examples.

00:11:50 Speaker_02
Okay. So this is real. So if you remember the list of the top five problem solving was number two on that list. So problem solving. If you ask the question, why are you using AI in the first place? Right. Just ask us, why am I using it?

00:12:03 Speaker_02
It's not, it's not a toy. Remember it's a tool. You're using it to solve a problem. And what's the process of.

00:12:10 Speaker_02
Solving a problem, identify the challenges, analyze and do an identification of root causes, do creative solution development, collaborate to solve, implement and monitor solutions, and continuously improve.

00:12:21 Speaker_02
That's pretty standard problem-solving process philosophy. So let's look at one of those steps, just one of those steps, analyze and do root cause analysis.

00:12:31 Speaker_02
Once a problem is identified, effective problem solvers and project management dive deeper to, and here's the you, understand the underlying causes.

00:12:41 Speaker_02
This analytical approach helps in proposing targeted solutions that address the core issues rather than just symptoms. AI can help us identify, humans understand and can put that understood list back into AI, to help further identify.

00:12:59 Speaker_02
So it's a cycle, it's this human in the loop, it's this idea that AI is a conversation and not Google.

00:13:06 Speaker_01
Yeah, I think that's really interesting, especially because AI is becoming a conversation.

00:13:10 Speaker_01
I mean, quite literally in the, in the context of generative AI, when you're actually having a conversation, you know, we were actually looking at the soft skills primarily as the skills you need to extract the most value from AI systems, not from a project manager's perspective, but just, you got to communicate, you have to collaborate, you have to have critical thinking, and you have to basically have creativity because these are the things machines aren't going to give you any of that.

00:13:35 Speaker_01
Right. You've got to bring it, right? And these aren't technical skills. It's like being a better data scientist, honestly, will not help you be a better prompt engineer. I think we've all learned that.

00:13:45 Speaker_01
It's all these things like breaking up problems and thinking creatively how to do that and whether the results are what you expect. And, you know, these are things that we haven't really taught very well in school.

00:13:54 Speaker_01
And I think people are sort of relearning these soft skills. Soft skills are making a comeback. But I really enjoyed what you were saying, especially when you were talking about all these statistics.

00:14:03 Speaker_01
edit earlier and made the passing comment even though we have really no dog in the fight on ads versus waterfall in this methodology versus another we know that methodologies are important and most likely people implement some flavor of some combination of all the thirty two flavors that are out there for your basket robins reference but right.

00:14:22 Speaker_01
But what was interesting and notable, as you said, really the successes and failures don't come from the methods that you use for running a project, but it comes from all of these power skills. Are you communicating effectively?

00:14:34 Speaker_01
Because Agile versus Waterfall, bad communication, probably project is going to fail. And all the rest of the things you mentioned, very specific.

00:14:42 Speaker_02
That's right, but one interesting thing to point out is that in this entire report from 2023, and you guys have been doing this since 2017, this entire report on power skills, the word AI or artificial intelligence is mentioned precisely zero times.

00:14:58 Speaker_02
So we're talking about the connection, and it's kind of interesting that you mentioned you use your power skills to help you do a better job extracting and conversing with AI.

00:15:10 Speaker_02
We're asserting that it works the other way around, that AI can help you, for example, be more empathetic, which seems counterintuitive. But we have examples and studies that show that kind of counterintuitively, AI can help you build teams.

00:15:25 Speaker_02
It can help you be more empathetic, which again, seems a little weird, but it can.

00:15:31 Speaker_01
Yeah. Don't doubt it at all. We also write for Forbes, so some of you might've read some of our Forbes articles. We did some podcasts as well.

00:15:38 Speaker_01
One of the things we mentioned is that it can help you because you can provide your not-so-great ideas and make you better. That's a way of AI to help you with creativity. I posted a comment recently, like, ideas aren't my problem.

00:15:51 Speaker_01
I can have 25 ideas before breakfast and 50 more before lunch, and I can use GPT to make them 150. The problem is, you know, it's still up to the human to provide some discernment. But I love that AI can really help there.

00:16:04 Speaker_01
Now, of course, one of the challenges, we've talked about this on other podcasts, and you mentioned this as well, one of the things that actually got our attention in the first place, actually, in talking to you, was part of the reason why humans have to apply these soft skills is because machines really, to some extent,

00:16:20 Speaker_01
We say artificial intelligence, but they're still kind of dumb.

00:16:22 Speaker_01
I mean, there's a reason why they don't have creativity, why they don't have critical thinking, why we have to apply our own communication and collaboration skills, because while there may be knowledge of patterns and they're really great pattern identifiers, AI systems that is, and they're really great at pattern repeaters or whatever,

00:16:38 Speaker_01
there's no understanding, that you level is missing, right?

00:16:41 Speaker_01
In the systems, there's no understanding of what these patterns mean, which is why they can't provide, these AI systems can't provide many of these power skills that humans are supposedly much better at.

00:16:51 Speaker_01
So, I mean, from your perspective, it's actually sort of a good sort of follow-up there, which is that, you know, how this you layer, because I know you use it in a couple of different ways, but like, you know, how is important this you understanding layer of making AI more

00:17:04 Speaker_01
powerful in terms of delivering value. And then you mentioned connecting that new layer to the power skills, and then maybe you're using it in a slightly different way, but that's perfectly fine. Just trying to get your perspective.

00:17:14 Speaker_02
Okay. So your podcast kind of really got to me because I've been teaching the DIKW pyramid for a long time.

00:17:24 Speaker_01
I see.

00:17:25 Speaker_02
Notice the lack of you, right? And here I am at BU, leaving out the U, which is leaving me with just a B. And no student wants just a B. I know that from experience. So when I heard the podcast, I did a little bit of research.

00:17:42 Speaker_02
I was inspired by the idea that there's a missing layer. And I ended up finding out that a lot of this originates, at least I found that it originates from a gentleman named Russ Acoff.

00:17:54 Speaker_02
And I looked at his work, I watched some of his videos on YouTube. He's a pretty insightful guy. I really would recommend that folks just look him up, A-C-K-O-F-F.

00:18:06 Speaker_02
That, and your podcast itself, inspired a piece in the book about this understanding layer, and the fact that D-I-K-U-W is the right pyramid.

00:18:18 Speaker_02
So I've actually got a figure here, and I can't show that on audio, but based on what you said, and what I hear from Russ Achoff, he's saying that efficiency is all the layers up to, kind of up to understanding, right? Doing things right.

00:18:34 Speaker_02
I'm sorry, doing things, even the wrong things. This was one, some of his thinking is fantastic. He says, as governments, we tend, governments tend to do a lot of the wrong things really, really right. He uses health care as an example.

00:18:47 Speaker_02
In fact, he says we don't really have a health care system, we have a sickness remediation system. And if you motivated doctors to think more about remediation, instead of getting paid only when people are sick, thing would be better.

00:19:02 Speaker_02
Very interesting perspective. So data, information, knowledge, and to some extent, understanding is in the efficiency, right? It's doing things, even the wrong things right.

00:19:12 Speaker_02
Effectiveness, doing the right things and doing the right things right, that's wisdom, right? And that's the level to which we aspire. Right now it's the level which we think we need human intelligence in partnership with AI to get.

00:19:25 Speaker_02
The other thing is that understanding does not imagine a new future, right? It predicts the next word, but it doesn't predict the whole future.

00:19:36 Speaker_02
It doesn't make it a wise decision based on all the underlying understanding, knowledge, information, and data. So in the book, we're going to be talking about this understanding layer

00:19:47 Speaker_02
with the inspiration from the podcast and with some of the background from Russ Achoff. But basically, wisdom is elevated understanding. It's understanding that has now become decisionable. It ends up with a decision that you could defend.

00:20:04 Speaker_02
And as you mentioned, AI kind of takes you up into the knowledge level and that missing piece is understanding. Knowledge is information that we've collected to be useful, but it isn't useful unless you understand.

00:20:16 Speaker_02
Let me give you an ad libbed example. Let me ask you a question first. Have you used chat GPT 4.0 to create images with text?

00:20:27 Speaker_01
Yeah, and it takes some effort.

00:20:30 Speaker_02
Yes. So I was trying to create a drawing that had just the words, some words at the top, and then a figure underneath it. Actually, it was for the blog post that you looked at, Garbage In, Wisdom Out.

00:20:44 Speaker_02
And I wanted an image that showed garbage and wisdom out at the top and had a figure underneath it. And it kept coming up with these words in the figure that I didn't want. So I kept saying, no words. I don't want any words other than the title.

00:20:58 Speaker_02
I would say, I understand. It's funny that it would say that. I understand you don't want any words in the image. And guess what? Next image had more words.

00:21:07 Speaker_02
more words misspelled and with characters that weren't even from, never mind English, that don't appear to be from any human language. They appear to be from Neptune or a ring of Saturn. I don't know. So it did not understand what I was trying to do.

00:21:24 Speaker_02
It was able to know what I wanted and reflect back what I wanted, but it never understood it. And I ended up having to, you know, basically use PowerPoint and a little bit of the imagery from AI to create it.

00:21:39 Speaker_02
Same for some of the figures in our book, same kind of thing. So I think that's a literal picture of how AI doesn't get to that understanding level. So that's my answer, and I'm sticking with it.

00:21:52 Speaker_03
All right, well, that's great. You know, we always like to hear that.

00:21:54 Speaker_03
We like to get different examples and perspectives from different audiences as well, because it's one thing for us to say it, but it's another thing when other people are experiencing this as well. And that's why we love our interviews so much.

00:22:06 Speaker_03
So I know that you had, you know, we talked about project management, the power skills. We've talked about soft skills, which seem to be a recurring theme that come up, and we love that. And now we've talked about our DIK UW pyramid.

00:22:18 Speaker_03
But specifically when we talk about AI from that project management perspective, our listeners know that we are big advocates for the CPM AI methodology, the cognitive project management for AI methodology for running and managing AI projects.

00:22:33 Speaker_03
And that's how project managers can run and manage AI projects. But there's also another side to this about how AI can impact the project management profession and how it can impact their jobs.

00:22:46 Speaker_03
So how have you seen AI impact the project management profession specifically?

00:22:51 Speaker_02
Sure. So PMI is huge on this. PMI has its own proprietary AI system called Infinity, and it's very good. It's fed with 14, I think they claim 14, 15,000 artifacts from PMI, and it's also firewalled.

00:23:07 Speaker_02
So, I mean, directly, the professional organization for project managers, PMI, has bought into this big time along with training programs and badges and so forth, that some of them are really, really good.

00:23:19 Speaker_02
I would highly recommend that project managers, especially if you're a member of PMI, take advantage of the free resources as a member there. So how have I seen it impact the profession? Well, it's impacted it whether we like it or not. It's already in

00:23:34 Speaker_02
applications that we use day to day. And there are specifically dedicated new programs that are built around AI. So one example is called Keto, K-E-T-O. It's a Finnish company.

00:23:47 Speaker_02
It's a portfolio and program management level software where you pump in data about your family of projects that you're running, keyword family of projects, like group of related projects.

00:23:59 Speaker_02
And you can ask questions like, okay, you see what we're offering now, what kinds of projects we're running, what else should we add to our portfolio? And we'll actually, based on the information you've given, it will rank and rate the projects.

00:24:11 Speaker_02
These are things that project managers tended to do with programs like Meisterplan and so forth. And by the way, Meisterplan, another company I work with, has started to integrate AI.

00:24:21 Speaker_02
Another company that I'm working with, a small company called Raidlog, is a risk management software and they've got AI built into it.

00:24:30 Speaker_02
Originally it was just kind of, you know, helping you put together a good spreadsheet that tracked your risks and issues.

00:24:37 Speaker_02
Now it's actually suggesting new risks and suggesting solutions or responses to your risks and creating heat maps and all this automatically with AI.

00:24:49 Speaker_02
So it's affecting the hard skills of project management, like risk management, but it also comes into play in the so-called power skills or soft skills. Jim Stewart and I wrote a book called Great Meetings Build Great Teams.

00:25:04 Speaker_02
That's out for about a year. And it talks about how project managers can leverage AI and the built-in tools like in Zoom, right? The AI meeting note taker and schedulers and so forth. So even meetings can be made better.

00:25:20 Speaker_02
As again, as long as a human is looking at the output, making sure that it's not just pumping information right into people's emails. It's huge in project management.

00:25:31 Speaker_02
And again, I highly recommend PMI suite of courses, but I also want to take the opportunity to talk a bit about how AI has impacted education, in my case, project management education.

00:25:42 Speaker_02
Of course, as a student, you've been given an assignment to write a managerial report or a paper, and you can go to AI and say, write this paper for me, right? And it will do it.

00:25:54 Speaker_02
It's going to be very tempting for students to do it, and of course they do it. But we have the means to respond to that with tools that can detect AI.

00:26:03 Speaker_02
So what we've done is bought into this and challenged students to, hey, use AI to write this, and your job is to critique the answer. And as a human, come up with what's right, what's wrong with this, what ideas did it have that you didn't have.

00:26:19 Speaker_02
This way they're getting used to this idea of this conversation. And we're not going to put our heads in the sand like an ostrich and say, well, we're not going to worry about AI. It's not there. It's not there. It's there, right?

00:26:29 Speaker_02
So students will use it to try to, and not all of them, But some of them will use it as a shortcut to actually doing research and actually using their own head to come up with solutions. And we say, have a party, go out and use it.

00:26:45 Speaker_02
But the intent is that we're going to look at this to see that you've put the work into it, and we'll even challenge you to use AI as a starting point.

00:26:52 Speaker_01
Yeah, I think that's the biggest. I mean, the tool is here, right? It's hard to put the toothpaste back in the tube, Pandora's box, whatever reference you want to use. Exactly. And I think, yeah, I mean, it's up to us to be like, OK, great.

00:27:06 Speaker_01
Given that the workforce of the future will be using these AI tools to accomplish their work, one of the points we had made earlier when we were doing our vision of the AI-enabled future, we talked a lot about education.

00:27:18 Speaker_01
Actually, education comes up repeatedly. for multiple contexts. One, of course, the way people are going to learn is changing.

00:27:25 Speaker_01
The fact that people can use AI systems actually dive deeper into areas that they may not understand, using AI as an educational assistant. And so it changes, of course, the way perhaps things are taught and maybe the nature of learning materials.

00:27:40 Speaker_01
Of course, when the calculator first came out, that changed a whole bunch of things too. And word processors, everything changes, everything. Handwriting has definitely not gotten any better since the invent of the calculator.

00:27:50 Speaker_01
computer, that is for sure. I look very enviously at how people did calligraphy like 100 years ago. I have no idea how they did that stuff, but they did and everybody had those skills. But you know what?

00:28:00 Speaker_01
Those skills turn out to be quaint these days because most people don't do that anymore, right? There's a reason for it. And I think the other impacts are that in the future,

00:28:09 Speaker_01
Most employers are going to come to expect that their highly productive workforces will be using AI to accomplish their work goals. And so those who do not have the skills may actually be highly disadvantaged in the future.

00:28:22 Speaker_01
So it's a change as to educating the workforce of the future. You know, that's sort of like an interesting idea, because you had some interest. One of the things you posted was not really necessarily when we first came across what you were doing.

00:28:36 Speaker_01
And we saw a post that you had made online in the projectmanagement.com site.

00:28:40 Speaker_01
And you were actually sharing some things that BU students were doing, maybe not necessarily in your department, but other departments that were doing something interesting around. It was sort of like a play on words. It was garbage in, garbage out.

00:28:51 Speaker_01
Now, of course, we refer to that from a data perspective. If you feed data, bad data, garbage data to computers, no surprise, especially when they're learning from that bad data, you will get bad outputs.

00:29:03 Speaker_01
But in this case, it was something a little more physical in nature. And maybe you could talk a little bit about that and how it relates to some of the themes that you were just talking about earlier.

00:29:12 Speaker_02
Sure. So the acronym I was using is, I don't know how to pronounce it, DAIWO, so Garbage In, Wisdom Out. So this is a play on GEIGO, play on Garbage In, Garbage Out, as you described it, except this time it's real garbage.

00:29:25 Speaker_02
It's physical, like, you know, Starbucks cups and lettuce wrap packages and, you know, you name it, chewing gum. It reminds me of, was it Shel Silverstein's song about Sally Stout? You have to look that one up. It's a whole song about Susan.

00:29:42 Speaker_02
Sally Stout would not take the garbage out. Anyway, you have to Google that. It's very, very good. So this blog post that you came across is about the Center for Computing and Data Science. It's a really, really interesting building in Boston.

00:29:56 Speaker_02
If you're sitting at MIT or Harvard, you're forced to look at it because it's right across the Charles River. It is a series of stacked floors that intentionally don't line up with each other. It's really weird looking.

00:30:09 Speaker_02
People call it the Jenga building. Some people think it's terrible because it's not Boston's style of architecture. I think it's fantastic. It's lead platinum. It's actually carbon negative. It actually subtracts carbon.

00:30:24 Speaker_02
from the environment, no gases plumbed into it. We had our project management and practice conference there. It's on the 17th floor. From this floor, floor to ceiling glass, you can look into Fenway Park.

00:30:35 Speaker_02
You can literally look into Fenway Park, but then you look across, you can see into New Hampshire and Rhode Island. And underneath it are 31 1,500-foot wells, twice as deep as the John Hancock Tower is tall.

00:30:51 Speaker_02
So if you know Boston, we don't have the same skyscrapers as Singapore and Dubai, but these are pretty big buildings. So that's a pretty deep well, and the heating and cooling comes from these 31 wells. Again, no gases planted.

00:31:05 Speaker_02
Now, AI has a separate role in here. I'll get back to garbage and wisdom out in a minute. But AI has played into this because the building used what's called construction 4.0 tools, things like digital twins and simulation to build that building.

00:31:22 Speaker_02
So it's almost a course in itself just to walk through the building. I can provide you with a drone tour of the inside and outside of the building. That's really cool. Just came up on BU's website. But my post was called Garbage In, Wisdom Out.

00:31:36 Speaker_02
It was, as you said, a play on Geico. And it features three students who are interning by photographing. Go call mom and dad and, what are you doing at school? I'm taking pictures of garbage.

00:31:50 Speaker_02
They're taking pictures of garbage in 234 purpose-built bins that are connected to databases. There's a company called Wasted. I think it's called Wasted. I can't remember the name of the company. It's in the blog post that compiles this data.

00:32:08 Speaker_02
combined with the photographs that they take, it's looking at how garbage is being disposed of, whether people are following the rules of putting things in the landfill or recycling portions. And this is really a D-I-K-U-W thing, right?

00:32:22 Speaker_02
We're taking data and advancing it to information, to knowledge, to understanding, and to wisdom. So that was the connection to your podcast episode.

00:32:35 Speaker_03
All right, well, that's wonderful. And we'll definitely link to that article in our show notes as well so that our listeners can check that out. And we actually published it in a recent newsletter that we have as well.

00:32:45 Speaker_03
So make sure to check that out on LinkedIn. Thank you. So yeah, it was a great article and it's pretty short, so it's a quick read. I encourage everybody to check it out. This has been such a wonderful discussion.

00:32:56 Speaker_03
You know, we always really like to get these different perspectives. And no matter how many times we interview guests,

00:33:01 Speaker_03
We always ask the same final question because you're able to bring in your own unique experiences and insights, your wisdoms, right, your understanding. So, and everybody answers this a little differently.

00:33:14 Speaker_03
Some people get really philosophical, other people get more practical. So I'd like to hear your experience and, you know, your answer here.

00:33:20 Speaker_03
As a final note, what do you believe the future of AI is in general and its application to organizations and beyond?

00:33:27 Speaker_02
Okay, I would say the future of AI is very hard to predict. You could ask AI what that is, and I have, but my final note would be don't just ask AI what's the future of AI. In fact, never use AI like a Google search engine.

00:33:46 Speaker_02
Again, have a conversation, iterate, converse, question what it gives you. As to the future, with better data, And with more advancement up through and above the U level and with proper guardrails, I think AI will be an outstanding ally.

00:34:04 Speaker_02
I don't think it's, I think it will end up taking jobs. Let's be, it's not sugarcoated, but again, as Ron mentioned, so did the calculator and this, even the slide rule and the, and the car and so forth. The best thing you can do.

00:34:21 Speaker_02
is to stay aware, make yourself a good prompt engineer, understand what this is all about rather than being an ostrich, and be ready for the changes that it's going to bring.

00:34:32 Speaker_02
And you will end up probably with a better job and you will end up with better results if you use AI properly. So that's my story and I'm sticking with it.

00:34:45 Speaker_01
It's a great story. I mean, that's why we keep asking this question. So many people have so many different perspectives on what AI means for them and for the world and just the future.

00:34:54 Speaker_01
I think from our perspective, it's interesting timing on all of this conversation because there has been a lot of press recently talking about, are we going to see any sort of return, positive return on investment from AI?

00:35:07 Speaker_01
There's a lot of doubting right now because of Well, it's like the natural, you know, there's a sugar rush when it comes to AI and AI hype. And of course, this is sort of the, there's always that sugar crash.

00:35:17 Speaker_01
I don't want to really refer to it as a trough of disillusionment or anything like that. It's really not. It's very natural reaction to it.

00:35:24 Speaker_01
And some of it is, of course, is financials because stock, you know, stocks have gone up a lot in price and stocks have not continued to go up a lot in price. And people are wondering, what does this mean?

00:35:34 Speaker_01
Well, the answer is that it really comes down to what it means for the average person who's trying to put AI into practice for the typical things that they care about on an everyday basis.

00:35:43 Speaker_01
And from that perspective, things seem to constantly be moving forward and evolving. Hopefully people are building some real experience and they have some realistic expectations when it comes to AI. That's always been AI's problem.

00:35:57 Speaker_01
Over-promising and under-delivering is the story of AI.

00:36:01 Speaker_01
But I think sort of the trick here is that as people realize, first of all, that many of these tools are very accessible, all these AI tools, to the average person, doesn't require a lot of skill and heavy lifting, don't, of course, prone to a lot of the issues, but people will start to build that experience and expertise.

00:36:18 Speaker_01
And in doing so, realize where these tools will provide I benefit. I think that I just want to refer to everything we've had this conversation has had so far.

00:36:26 Speaker_01
It's been a fantastic conversation because we've gone through a whole gamut here talking about traditional power skills and power in project management, ideas of how AI is going to impact the typical daily life of someone who's doing project management.

00:36:40 Speaker_01
We've brought it all the way to the understanding and the wisdom level as people applying AI to some of these future projects. you know, photographing trash in a lead platinum building, you know, one of a kind.

00:36:53 Speaker_01
So I really want to thank you so much, Rich. You provided so much insight, so much fantastic value here for our AI Today podcast listeners.

00:37:02 Speaker_02
And I thank you for the chance to be here and to talk about what we hope is going to be a really interesting contribution in the form of this book. So thank you.

00:37:11 Speaker_03
Yeah, thank you. This has been such a wonderful discussion. And listeners, stay tuned for that book. Maybe we'll have you back on once it's published.

00:37:18 Speaker_03
So definitely subscribe to AI Today if you haven't done so already so that you can get notified of all of our upcoming episodes.

00:37:25 Speaker_03
We have some additional thought leadership topics that we will be addressing and presenting on some upcoming episodes, as well as some additional interviews. So definitely subscribe. Like this episode and want to hear more?

00:37:37 Speaker_03
With hundreds of episodes and over 3 million downloads, check out more AI Today podcasts at aitoday.live.

00:37:45 Speaker_03
Make sure to subscribe to AI Today if you haven't already on Apple Podcasts, Spotify, Stitcher, Google, Amazon, or your favorite podcast platform. Want to dive deeper and get resources to drive your AI efforts further?

00:37:58 Speaker_03
We've put together a carefully curated collection of resources and tools. handcrafted for you, our listeners, to expand your knowledge, dive deeper into the world of AI, and provide you with the essential resources you need.

00:38:10 Speaker_03
Check it out at aitoday.live slash list. This sound recording and its contents are copyright by Cognolitica. All rights reserved. Music by Matsu Gravas. As always, thanks for listening to AI Today, and we'll catch you at the next podcast.