ep. 105 - AI Guys:
Reinvention Consultants, Futurists, & Thinkers
Christopher Bishop is passionate about the power of emerging technologies to deliver positive transformation at the intersection of business and culture. He is especially excited about the potential of artificial intelligence to provide solutions to problems once considered the realm of science fiction.
Chris first became interested in ai during a fifteen-year stint at IBM, having joined the company just as their seminal computer Deep Blue beat world chess champion Garry Kasparov. At the end of his tenure, Chris worked with a team at the IBM Foundation to contemplate the use of IBM Watson in social and civic settings. It became clear that ai is poised to become an enabling layer that will improve every business, regardless of vertical or geographic location.
As a futurist, David Houle has always had keen insights into how new and future technologies will affect and change society and business. His high degree of accuracy in his forecasts led him to become known as “the CEO’s Futurist” having spoken to or advised more than 3,500 CEOs and business owners during the last 10 years.
He started writing about Artificial Intelligence in his fourth book “Entering the Shift Age” in 2012 and has spoken to audiences all over the world about the topic since then. In his 6th book “Brand Shift: The Future of Brands and Marketing- named as one of the top five marketing books published in the world in 2014- he wrote about how ai, Big Data, the IoT and the Neurosphere would dramatically change all aspects of Marketing.
Kyle Davis: Okay. With us today on GDA podcast, we have a special follow-up episode, if you will, but it's with David Houle and Chris Bishop, and together, the two of them are the AI Guys. Some of you all may remember the name David [00:01:00] Houle from an earlier podcast that we had, where we were talking about futures, and technology, and stuff like that. But as people know, when I record these by myself, I don't like doing the traditional introductions, and I'd rather have people introduce themselves. So since, Chris, this is your first time on the podcast, tell everybody a little about yourself and how you got involved with David.
Chris Bishop: Okay, great. Will do. And delighted to be here. Thanks, pal.
I describe myself as a nonlinear multimodal careerist. [00:01:30] I've had seven careers so far, from touring rock musician to working in the Django biz, working as a web producer, and spent 15 years at IBM in a variety of roles. Corporate internet programs, and HR comms, and the IBM Foundation. But the way that David and I came together is that we're both futurists, so I now talk about, among other things, what the workplace of the future is going to look like, and implications around artificial [00:02:00] intelligence.
David and I did a presentation together in Sarasota, Florida earlier this year, a sort of social historical perspective on AI, and machine learning, and deep learning, and algorithms and bots, and had such a great time that we decided to partner and do this together as a team. The people in the audience ... We had a sold out crowd at the Einstein Circle even in Sarasota, and people were coming up to us and talking to us, and saying, "You're the AI Guys, huh?" We're like, "Yeah, I guess we are. [00:02:30] We are the AI Guys." That's how we came together.
I wanted to mention that when I was at IBM, I actually joined IBM when Deep Blue was first rolled out, the supercomputer that beat Gary Kasparov at chess in 1997, and stayed, obviously, in touch with big iron, developments in technology and virtual worlds. As I left IBM after 15 years, I was also involved in working with IBM Watson, the current supercomputer that beat [00:03:00] the grand champions at Jeopardy, and I lead a symposium that looked at how Watson might be used in social settings. I was working in Corporate Citizenship at headquarters at the time, and supporting the executive who ran the IBM Foundation.
So, that's how we came together. That's my background.
Kyle Davis: That's awesome. And obviously, for people who may not have listened to the first podcast with you, David, if you can, give them a little bit of your background.
David Houle: Sure. [00:03:30] I'm a futurist. I've been a futurist full time for 12 years. My prior background to that was always doing things that people said wouldn't work, like I left CBS top salesperson and helped join about 30 people at the time to create and launch MTV, Nickelodeon, VH1. CNN Headline News, and then we ended up overseeing CNN as well, so cable is never going to work. And then in the '90s, I was leading a company to create online courses, so again, that's something that wouldn't work. So, that's what lead me to become a futurist [00:04:00] earlier in the century.
I've written seven books. I'm known as the futurist that says we've entered the shift age, having left the information age. As a futurist, I've spoken on all six continents, and I think 14 countries. Obviously, over the last few years, I've been talking about artificial intelligence, but more from the point of view of, as a futurist, what this technology might mean, and what it might provide.
The interesting thing for [00:04:30] me is that there's a great interest/nervousness/outright fear of this, and so when I met Chris at the 50th anniversary World Future Society Conference, we really connected on this topic about, how do you make artificial intelligence understandable in a way that business people can put it into a place and start to prepare for it?
[00:05:00] It's this category that has all this Hollywood imaging about it, Terminator 3 and everything. It's such a ... It's probably the greatest technology humanity has ever invented, and when I got together with Chris, I'm speculating into the future, as I do as a futurist, and then Chris really educated me how far back, centuries, artificial intelligence goes. So, that's why people started calling [00:05:30] us the AI Guys, because we made it comfortable, we gave it a historical past that everyone were nodding their heads on. They were comfortable with it, and then we projected into the future.
I really enjoy working with Chris because he brings all that credibility of IBM, and Big Blue, and Watson, which most people know. Also, I've attended some events where the conversation about artificial intelligence is just way too techy, and so when somebody, [00:06:00] as Chris said, called us the AI Guys, we kind of looked at one another and said, "Well, okay," because that reference is that we're the guys that will make it understandable for you in a positive way.
Kyle Davis: Yeah. I'm sorry to cut you off. I think you made a great point, is that when you go to a lot of these tech conferences, it gets super techy, and it requires you to have some fundamental understanding of APIs, or something like that, and for most non-technical [00:06:30] people, it's just kind of way over the head. That's because the route that most people want to go is super granular, but really, I think it's great that you all two are making this view from a 30,000 foot view, and being able to break it down and really explain it for people.
With that being said, people have an understanding that AI isn't this new kid on the block. What is a little of the historical perspective that is AI, and how did we get to where we are today, and where are we [00:07:00] going?
Chris Bishop: Let me jump in. We typically begin our presentation with a reference to the Antikythera mechanism. We'll take a pause so all your listeners can Google that right away. What that is, in fact, is this ancient device that was discovered in 150 feet of seawater off the coast of a Greek island, and it's a machine that was designed about 2500 years ago. [00:07:30] They're not sure who put it together, but it captured solar eclipses, it measured orbits of the planets closest to the sun, Venus, Earth, Mars and Mercury. We use that as a reference point for man's desire to create machines that will help him perform tasks more efficiently, to gather and manage data more productively.
That's [00:08:00] where it begins, and then we trace it through developments in the '50s around machine learning, that some of the seminal players, like University of Pennsylvania were putting together, introduction of ENIAC, and all the way through to today with lots of ... And even more importantly, the degree to which AI permeated our culture almost without us knowing to some degree. Things like Siri, and Cortana, and [00:08:30] Google Home, and Alexa are all "versions," quote-unquote, of AI that are currently being used by the general population.
The other side of it, too, is that in corporations, in private sector and public sector, you have tools being developed that will do things like determine who gets paroled and who gets sent to jail, and who gets a loan, and who gets approved for a mortgage. I think there's a [00:09:00] quote by Andrew Ang who's a Stanford professor that's quite telling, describing AI as the next electricity.
Also, I think worth mentioning that we really view it as a constellation, if you will. It's not like one thing, right? When you talk about AI, you have to talk about this broader spectrum of a range of ways that machines are learning and being applied in everyday settings to more obscure, specific kinds of deep AI instances, like [00:09:30] the artificial intelligence that beat the champion at go, the very complex ancient Chinese board game. We're saying it's a wide-ranging set of tools and processes that represent the AI constellation today.
Kyle Davis: Yeah. I think - Oh, go ahead, David. Go ahead.
David Houle: Well, if you want to follow up to something he said, go ahead, because I was going to extend that a little bit, but go ahead.
Kyle Davis: Go ahead. No, I think you should probably extend it.
David Houle: [00:10:00] Okay. Before we got on the call, we were talking about how you're an analytics guy, right? There's all this stuff over the last three years that is addressing the Internet of Things, IOT. Big data. Artificial intelligence. All of that, as Chris was saying, is of a piece, and it's all interconnected. It's the coming together of all these trends that is creating what is really machine learning, first of all.
And second [00:10:30] of all, to go a little bit deeper, because audiences always like to hear stories, real quickly, it was '97 that Big Blue beat Kasparov in chess. A chess master plays 36-38 moves ahead, so that's straight mathematical equation. The fact that Big Blue beat the two best Jeopardy champions - crushed them, as Chris likes to say in our presentations - in 2011 [00:11:00] was significant because it's all contextual information. You have to give the question to the answer across a wide variety of topics.
But what really sucked me in, because I always talk about the importance of design in creative thinking, is in 2016, AlphaGo, which is Google's artificial intelligence, beat the best non-Chinese grand master in go in a 4-1 series. Blew him out, and as [00:11:30] Google says, the number of potential moves in the Chinese board game go is equal to the number of atoms in the universe. In other words, it's an infinite amount of moves, and what happened there was that Google programmed the artificial intelligence with a random algorithm, which meant it has intuition. That blew my mind.
And then the next month, Carnegie Mellon's artificial intelligence, [00:12:00] for 20 days, played the best poker players in a certain kind of poker in Vegas, and beat them all. And to a person, all those 20 people said, over the 20-day competition, that they had the sense that the machine was getting smarter each day as they kept playing rounds.
And then the last piece was this year, when the greatest go player in the world, a 19-year-old out of China, came [00:12:30] in and lost 0-3, and basically said, "I am never going to play an intelligent machine again in go. They are my gurus. I go to them to learn." So, in the most infinite, intuitively-driven board game ever created, artificial intelligence has triumphed. [00:13:00] That's an amazing thing. That's what really got me into it over the last two years.
Kyle Davis: So, I think what's an important thing for people to understand is that when we're talking about AI or machine learning, I think machine learning is probably really where it fundamentally starts, at least for my understanding of AI and technology for usage, it's these machines are just starting now to be able to mimic and see what people are doing. And then you mentioned a fascinating part about the go programming [00:13:30] from Google, is that they then allowed it to program for randomness, to then give it intuition. Can you speak as to, now there's other ways in which you can actually use AI, instead of having it be a board game killer, you can also use it to then start to automate certain workflows just by having it watch individuals, and things like that.
David Houle: Let me do a couple, Chris, then you jump in. I've studied and written a book on the future of health care and medicine. There have been several [00:14:00] studies done where artificial intelligence is better than doctors at diagnosing cancers. There's 100 women who had early-stage breast cancer, and 53 of them were diagnosed by the doctors having that, and 72 were artificial intelligence. So, what do those 19 women think who didn't get diagnosed?
Across the board, it is elevating performance, efficiency, knowledge, [00:14:30] and speed. Chris, is there a ...
Chris Bishop: Yeah, and I think just to continue on that thought, I mean, the thing to keep in mind is that this is, AI and deep learning are able to influence positively every sector, every vertical, every industry. From health care, to education, to travel and transportation. And it's becoming more and more pervasive. Again, back [00:15:00] to the constellation idea, that there's a range of applicabilities.
At the very fundamental layer, if you will, it's doing things ... You have chat bots that respond to medical questions. I actually wrote a piece recently, "Talk to two chat bots and call me in the morning," around the ability to pose questions to an algorithmic AI instance that has looked at and rationalized a range of [00:15:30] data, and can come back to you with recommendations or suggestions about diagnoses or treatments.
Certainly in the legal field, I mean, using AI to help lawyers make better decisions, or putting cases together. I was at a meeting late last year, actually, at a hedge fund in New York, where the guy who runs Silver Lake was saying that he had just fired 100 analysts and hired nine data scientists with expertise in AI and deep learning. Because [00:16:00] that's what he needs, is people who can take advantage of these tools to help them generate income for high net work individuals whose portfolios he's managing.
As I was saying, it's a range of applications where AI is going to be valuable.
David Houle: Two things, to jump in there, if I could quickly tell. One is, the phrase is "collar color neutral." Everybody has thought artificial intelligence would replace [00:16:30] the manual labor on the factory floors, and I always get some applause when I mention this, but the number one white collar job category that will be automated out of existence, according to an Oxford 2013 study, is attorneys, followed by accountants.
But I want to come back to something you said in your question, Kyle, which I think is the most important thing. Artificial intelligence, the word artificial is going to go away. If you look at the logo of AI [00:17:00] Guys, it's a lowercase "a" and a lowercase "i," but the "i" is much bigger. We think that the word artificial is a temporary term.
I did a ... I put up a video yesterday that came from a the conversations I've had with Chris that it will be called the "age of intelligence," because there's also a lot of stuff going on in neuroscience. But here is my, the thing I've always said as a futurist [00:17:30] for the last ten years about artificial intelligence, which is, we are the first iteration of humanity to have to psychologically accept an equal or superior intelligence cohabiting the planet with us. We're so top of the food chain, egocentric about that, that I think that the word "artificial" is being brought in to kind of diminish it, like it's not us, it's not human.
What [00:18:00] I did about ten months ago, is I looked up the definition of intelligence, and nowhere in that definition is the word "human." And then I looked up the word "artificial." It means manmade. So, initially, sure, manmade computers and manmade algorithms, but now, as you said, it's going to be called machine learning. That's what we think. We think that it's not artificial, it's intelligence. Dolphins are intelligence. Whales are intelligent. Machines are now intelligent.
I think that there's an underlying [00:18:30] issue of psychological disruption that, for the first time, humanity might be cohabiting with an equal or superior intelligence.
Kyle Davis: Yeah, I think you brought up a brilliant point, which is the renaming of artificial intelligence to intelligence, and if anybody heard that bark in the background, that's my partner, Titan the Belgian [inaudible 00:18:52]. But, anyways, what I think is really important for people to understand, and [00:19:00] I think, David, you brought up a really good point, is that for a lot of these industries, automation on the assembly line was the big fear of a lot of people out there. They're going to take the jobs with robots, and to an extent, they have.
But the real change of the workforce is going to come when automation, and this new use of AI or intelligence comes in, to really get rid of a lot of generalists, let's say, like in the legal field, and then you're really going to have to work [00:19:30] with specialists who really have something. And in all honesty, maybe their days are numbered, too. Generating contracts, or what evidence to bring into the fold, or different things like that.
Chris Bishop: I think it just ended up at a macro level. The thing to keep in mind is that, as David said early on, people are fearful, or apprehensive, or uncertain, but I think the net net is that this is yet another technology - back to the Antikythera [00:20:00] mechanism reference, right - that's going to augment what we as humans do.
I mean, there's certainly Sturm und Drang, and Elon Musk is loudly touting in the press that he's worried AI is going to be the death knell for humankind's dominance, but I think, as humans have done with technology over the centuries, and I'm waxing philosophic here, but we create it, and we manage it, and we use it to help augment [00:20:30] what we do as humans.
I think that's, from a macro, philosophical perspective, that's true, and I think the way that translates to business and private sector is that every company has the potential to take advantage of this technology, these breakthroughs. This whole, back to the idea of a constellation, the range of tools and processes that AI represents. It's exciting. There's tremendous opportunity for all kids of companies and organizations [00:21:00] to exploit this to their advantage.
David Houle: Yeah, and the way I think about it is that all this constellation, Internet of Things, big data, machine learning, is real-time sociology and anthropology. Don't tell me what your sales figures were last month. Tell me what they were last night. In other words, everything can be known, and the beauty of that is ... Well, just think about that. Everything can be known, and it can be accessed.
[00:21:30] What I say, when people say what's going to happen to jobs? Of course, machines were going to eliminate jobs, they created more jobs. Computers were going to eliminate jobs, and they created more jobs. But this is the one where we think that there will be jobs that will go away permanently. The way to think about this is, I've always said technology is not good and bad. It's morally neutral. It's how humans use it. A plane can shorten distances, but it can [00:22:00] also drop bombs.
So, it's not the machine learning that is of danger. It's how humans will deploy it. That's always the case, and I personally think that the future, I think that artificial intelligence, to use that phrase now, machine learning, is the greatest technology invention since electricity, and it will completely redefine economics and business in the next 20 years.
[00:22:30] What will happen when half of the jobs that exist now go away? People see that as a negative, but the positive is that right at the time there's an explosion going on ... We have a chart that shows humanity created 1.8 zettabytes, which is a billion terabytes of data in 2010. By 2040, there will be 12,000. So, we go from 1.8 to 12,000 in 25 years. Our cerebral cortexes [00:23:00] cannot compute that much data, so right at the time that we need it, we have birthed, if you will, machine learning to handle all the stuff we no longer need to handle.
I always say, and this is very waxing into the future, when you go to a party or a meeting, the first question is, "What's your name?" "My name's David." And the second question is, "So, what do you do?" There might be an evolutionary stage that this technology will take [00:23:30] us through where we don't have to answer that. We don't have to say, "I do this work because it pays me well. I do it because it's what I want to do, or what the planet needs."
I truly think that this is a revolutionary technology, as electricity was. If you look at before electricity and after electricity, same thing. Before machine learning and after machine learning. And the key is, and I'll turn it over to Chris, the key is to let business people, executives know [00:24:00] that this is a positive thing, and it's a thing they should pay attention to, not be scared of, and will ultimately make their businesses more efficient, more expansive, move more quickly, and more profitable.
Kyle Davis: Yeah. One of the things I wanted to say, is that I really want to thank you for bringing in the word, that it's going to augment the way that people work. It's going to be, really, a tool that people are going to find useful.
Just recently [00:24:30] I was on the phone with a really good friend of mine, a former colleague, too. He's working for a new company, and what they have is a really interesting software platform that records a call you're having with a prospective client, and then takes the transcript that it automatically does and uses machine learning to then tell you how to better pitch that person, or to come back, and what to take elements, and it's starting to read the emotions of how the conversation [00:25:00] is going. It's a new sales tool to help sales teams deliver better service than they ever have before. It's a tool that comes in and just kind of augments what the next call or next response should be.
Chris Bishop: Yeah. I use a lot of bots to help me manage my social media presence. My feeling is, let the bots do it. Let the AI do it. I've got other things to do with my time, and I think that's a model that translates both personally and [00:25:30] from a more macro, kind of company organizational enterprise perspective. The tools are growing, the ability is improving. Let them do it.
David Houle: To that point, anybody who listens to this podcast ... I'm a Amazon Prime member. That's the epitome of beautifully integrated machine learning. Sitting at my desk, I have a more user-friendly, customer-knowledgeable [00:26:00] experience on retail than anywhere else in the world, because they know what I buy, they know what I like, they know what I might like. Anybody who loves Amazon basically is saying they love machine learning.
Kyle Davis: Yeah, and I think also, just something as simple as another way with Amazon is, what are you seeing when you say machine learning? It's maybe the suggested items. One person looks at this. Let's say I'm looking at a protein [00:26:30] powder. Well, someone who bought this protein powder also bought these lifting gloves. And that's a simplified version of it, but that's machine learning. That's AI bringing something to the forefront, and it's improving their overall cart value, the shopping cart value, so that way they improve their sales, and it improves customer satisfaction.
David Houle: Exactly. So, we just try to ... We've probably gotten a bit technical for this podcast, but basically, [00:27:00] the audience responses to the two of us is very, "Hey, thanks a lot, now I'm not so scared as I was." "Hey, thanks a lot, now I know I have to really pay attention to this." "Thanks a lot, now I know that this will be part of my business in three to five years, and now I know how to think about it." That's what we're trying to do together at the AI Guys, is to get people, business people primarily, but the general public as well, [00:27:30] to feel comfortable with it, embrace it, understand it, and realize that long-term, it has incredible potentials for individuals, businesses, markets, and humanity.
Kyle Davis: I think what would be, and I think this is a good place for us to wrap up, but what I want to leave the audience with, and for them to listen to, is having an understanding of what are some positives that are going to come out of AI? It's really easy to go down the rabbit hole of potential negatives, [00:28:00] but things are only negative because you haven't thought of what the converse might be. So, with that being said, we'll start with Chris. What are one or two huge positives that you see coming, in how it might help business, or academia, or anything else like that, with the evolution of machine learning, and big data, and all the rest?
Chris Bishop: A couple of examples that I'd like to cite. One is certainly IBM Watson, and the implications [00:28:30] for that kind of AI technology. The numbers around how many periodicals, or peer-reviewed papers that are published as regards a specific medical top ranges around 1,200 per week. There's no way that a human physician can do his job or her job, and read and parse and rationalize and make sense of that much information. So, a tool [00:29:00] like Watson, an AI-driven system, can in fact do that, and do it quite easily, actually, and play the role of a digital diagnostician, and represent recommendations and suggestions and guidance, based on being able to being able to consume and parse that amount of data.
Back to the idea, as David was saying, the amount of data that's being created every day is just growing exponentially, and so our brains can't physically [00:29:30] process it, so let's use these tools to do that. That's a strictly kind of health care ... That model could be applied in business, using business stats, as well.
The second example I want to cite, I just read about this the other day, is tied to autonomous vehicles. There's a company called Voyage, and they're running a test program, a pilot, at a gated retirement community in South Bay, San Francisco area, allowing [00:30:00] residents ... I think it's something like 75 and older is the age requirement to live in this community. But to summon autonomous vehicles.
Again, this is an AI instantiation, right? It's rolling AI. Allowing people who would be sort of historically homebound, because they couldn't drive, or they weren't comfortable dealing with parking, or apprehensive about hitting somebody. They can summon these vehicles [00:30:30] and get around this community. It's because the speed limit is 25 miles per hour, and it's a very limited terrain, the LIDAR and the sensors can capture all the data they need to safely navigate in this community.
So, frankly, I'm looking forward to being able to take advantage of that when I'm at that stage of life. I think it's fantastic. And these people are feeling so liberated, again by this AI instance, that they can now get around. They can go to dinner, they can go play bingo, they can visit their friends, [00:31:00] because of this application of artificial intelligence.
Kyle Davis: I think, and one thing I want to add to that, when it comes to automated driving and the use of AI, at least for me in the future, and I know, David, I think we've talked about this before, what the consequences of this might be, that is just automated driving, and its improved safety in the long run. But more importantly, it would just reduce congestion. You're not going to have the traffic issues, because there's going to be no accidents. There's going to be [00:31:30] no weird lane merges or anything else like that. It's going to be orderly and simple. It's going to be awesome, and my dog agrees.
David Houle: He does, really! And what I would add on to that, that it really ... The phrase I use is that 2017 to 2037, reality itself will change. What you just said of autonomous cars, we've got the 21st century infrastructure for transportation, it's the Interstate [00:32:00] highway system, but with 50% fewer cars and no drivers driving. So, there's no drunken drivers driving while texting. But the thing about that is, then there will be no auto insurance business.
What artificial intelligence, machine learning, is really going to do, it's going to transform the global economy. It's nothing less than that. It's going to transform the opportunity for people to not define themselves entirely as part of a cog of an economic machine. [00:32:30] It's going to allow people to live better lives, healthier lives, more efficient lives, more profitable businesses. It is that big a technology. It is like electricity.
I think that quote you said at the top, Chris, is exactly right. It is as profound an invention in terms of transforming humanity as electricity, and that's why we want to be the AI Guys, to make it embraceable, and understandable, and implementable.
Kyle Davis: [00:33:00] Well, like I said, I think that's a good place for us to wrap. I just love how simplified that you all make it. With that being said, I want to thank both David and Chris for coming on here and sharing their thoughts. Look, if you all want to have the AI Guys, or one, or both of them come to your events, you can do by contacting GDA speakers. The number is 214-420-1999, or you can go to GDAspeakers.com. For the transcript of the podcast and everything else, you can go to GDApodcast. [00:33:30] com.
Chris and David, thanks so much, and it was a real pleasure.
Chris Bishop: Thank you. I enjoyed it. Nice talking to you.
David Houle: Kyle, it was a real pleasure, as always. Thank you so much.
Kyle Davis: All right, guys.