What is A.I.? Deep-dive with Richard Boyd (Part 1)

What is Artificial Intelligence? How can it be applied in business? What is data exhaust and why is it important? How is AI disrupting and enhancing our lives? These are some of the questions answered by AI expert Richard Boyd in Part 1 of this deep-dive interview series on Artificial Intelligence.

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DISCLAIMER: Below is an AI generated transcript. There could be a few typos but it should be at least 90% accurate. Watch video or listen to the podcast for the full experience!

Alexander Ferguson 0:00
Welcome to UpTech Report series on AI. I’m Alexander Ferguson. For our first interview, I sat down with Richard Boyd, founder of Tanjo. In carvoeiro. Richard is an entrepreneur, author and speaker on a range of topics from education to virtual worlds to machine learning. Here, we ask him, How does he define and apply artificial intelligence in business, as well as it how it applies to our everyday lives?

Richard Boyd 0:36
Well, I mean, artificial intelligence is a technology that’s been around for a long time, and used to mean one thing, especially to us in computer gaming. Right? It was, it was asking, you wouldn’t ask a computer to do something unless or until a human being understood that thing completely. And then you would just program those rules into the computer and tell it what to do. Now that that’s, that’s fine, as long as it’s something we understand. But when you start looking at things like, recall, when we first looked at autonomous vehicles in the early 2000s, right, we were out in the desert, with one of those early DARPA challenges watching as all these vehicles were going across the desert and hitting rocks or losing the GPS signal. It’s because we human beings really still don’t understand how to humans even drive cars, how can we tell a machine to do something we don’t understand. There’s a lot of talk around creating artificial intelligence, right? That mimics human intelligence. But we don’t understand how the brain works. Right? There’s a lot of big efforts out in, there’s the, the Blue Brain Project out in us, I believe it’s in Switzerland, or Austria, somewhere out there, and other big projects, trying to understand all that all those deep constructs of the brain, but we don’t understand how it works. The big breakthrough for autonomous vehicles and everything else, was this new phase of machine learning where a human being doesn’t even have to understand how to do something, you can actually just take some really good machine learning libraries, feed them all of the data, like lots and lots massive amounts of data, and have them infer their own understanding. That’s why we have autonomous vehicles today. And today, you can just take 100 hours of video of driving, give that to some well designed machine learning libraries, and cars can go out there and drive flawlessly. So that that’s the big breakthrough. I always think of it in terms of three stages. The first stage was when you know, we wouldn’t ask a computer to do something unless a human understood it completely. Then you program in like a finite state machine or you know, hierarchical behavior, trees, that kind of that kind of thing. And then in this phase, where now is what we’re looking for data scientists, how do we get enough data? And that’s the real challenge today? How can I find enough data that’s relevant, that can train a system reliably? on whatever it is I’m trying to teach it the organizational knowledge of a law firm? Or how to drive a car, how to, you know how to navigate to Mars, those sorts of things? And that’s, that’s the issue today is how do we get enough data, get it into the right shape, so that machines can derive meaning from it?

Alexander Ferguson 3:22
What is data exhaust? And why is it important?

Richard Boyd 3:25
It’s a term that just applies to you know, as we ramble around the internet, we leave little cookies and little behavioral patterns around behind us of like, what were we interested in? You know, Google is tracking? You know, where we go on the internet? Which pages? How long do you stay at each page? And that ends up being a creating an interesting model around like, what are your real interests? And, you know, their their locations services on your phone that can track the behavior of where you actually go physically in the world? And how often do you spend different places during the day? And how long do you sleep at night, all this, all that all that goes into data exhaust, and it can be used for both good purposes. And of course, you know, nefarious purposes, I guess, is the way to say it. And I think that’s one of the things that’s happening with technology today, when you look at what Cambridge analytic did with that data exhaust in order to identify people who were susceptible to certain kinds of information and then move them from one belief position to another that we’ve seen that can have some deep effects and society. So it’s, that shows that this stuff is powerful. And, you know, how do we use it for good and that’s where we’re really focused is how do I help empower people by helping them take advantage take control of their own data exhaust, so they can direct it to representing their values to government are representative values to the companies that they interact with. If you’re buying a car from a company, or you’re shopping or whatever, we found out that machine learning systems really can’t tell the difference between data exhaust around an organization, or a topic or a person. So now we’re getting to this, this area where we can build models of people and their behavior, if we have enough data exhaust around people, and that’s getting very interesting,

Alexander Ferguson 5:31
how is AI disrupting and enhancing our lives?

Richard Boyd 5:36
It’s the machine age, right? It’s the automation age. And, you know, there’s a lot of concern around displacement of workers and automation a minute started with when we started replacing bank tellers with automated tellers, right? That was a disruptive thing that concerned a lot of people now we have checkout, checkout stations in grocery stores that are automated. And that’s just the beginning of it, just the tip of the iceberg. It’s not just those sorts of really rudimentary tasks that are being automated, we’re automating all sorts of things. And it really that that this discussion today is like, what should and I think every organization, every government, every person, again, should be thinking about every activity they’re involved in and thinking, what should machines be doing? And what should humans be doing? And the answer to that question is changing every single week almost. Now. Now, you mentioned the Industrial Revolution, the industrial age, you know, we had some time, I guess, in 1800 91% of everybody in the United States was involved in agriculture. And in 1900, it was like 41%. Today, it’s too, so we had 200 years or more, to adapt to an automation using industrial methods, right. And we found stuff for people to do. The challenge today is that it’s the same thing is happening, but it’s happening on a very compressed scale. And the positive side of this is, there are things that humans should arguably not be doing assembly line work was a big break big breakthrough in the last century. But when I see human beings standing there, like doing a repetitive task over and over all day, whether or not seen this firsthand in chicken factories, and automobile factories, and elsewhere, I look at that, and I say, Why is a human being doing that today? How fulfilling is that job? And when you talk to those people, they’re like, Well, you know, I’m getting paid. And that’s why I’m doing this, this activity. But but, you know, the real life for them is when they punch out at the end of the day, then they actually enjoy their life. And, you know, people like me and my team who started out and we’ve had this Peter Pan existence of building computer games and working on Hollywood films, and that kind of thing. It’s like the work that you do, where every day you come to work, and some part of your day, you’re in flow, you’re in the flow state, you’re you’re enjoying what you’re doing, right? And why can’t that be that way? Why can’t it be that way for everybody. And I argue that it can, especially today with these technologies implemented, so. But it’s going to be disruptive, it’s going to make people who don’t like change uncomfortable. And that’s why we need really strong leadership, in every community in certainly in the country and in the world. And that’s why that’s critical that we all pay attention to that because that leadership is very important, because we’re gonna have to make some changes to all the government systems and everything to adapt to this and actually make a better world.

Alexander Ferguson 8:35
That concludes the audio version of this episode. To see the original and more visit our UpTech Report YouTube channel. If you know a tech company, we should interview, you can nominate them at UpTech Or if you just prefer to listen, make sure you’re subscribed to this series on Apple podcasts, Spotify or your favorite podcasting app.


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How has A.I. evolved? Deep-dive with Richard Boyd (Part 2)