A look at how A.I. is helping the human race

Artificial intelligence is changing our lives at lightning-fast speed. Now A.I. is used in everything from the workplace, banking to language. James Scott, professor of statistics and data science at the University of Texas, joins Hari Sreenivasan to discuss how to better understand the modern world of artificial intelligence.

TRANSCRIPT

Artificial intelligence is changing our lives at lightning-fast speed.

Now, AI is used in everything from the workplace, banking to language.

James Scott, professor of statistics and data science at the University of Texas, is here to discuss how to better understand the modern world of artificial intelligence.

Thanks for joining us.

Ah, thanks for having me.

So it seems to me... My phone is too far away from me.

I'm a creature of habit.

You know, it seems that there are already examples of artificial intelligence in my phone right now.

In a way, it's reading my e-mails and telling me what's coming up or how long traffic is going to be.

There seems to be little bits of AI creeping into our lives that we're not necessarily aware of because we might have a conception of AI as, you know, some big HAL 9000 robot.

Absolutely.

Yeah.

Just the other day, when I parked at the gym, I noticed a new feature on my phone that would tell me where my parked car was.

I mean, and we tend not to call that stuff AI.

We just call it an app, right, and I think that the ubiquity of AI is actually something that a lot of folks don't appreciate.

You're exactly right that when people think of AI, they're kind of calling on these science-fiction examples, you know, maybe the cute robots from 'Star Wars,' you know, BB-8 or R2D2, that everybody feels an emotional response for, or maybe they're the evil robots from other science-fiction works, but, you know, AI always seems like something that is in the future, and I think you're absolutely right, that in reality it's in the right here and the right now rather than in the distant future, and it's to all of our benefit to understand the technology a little bit better.

But what should we be paying attention to in how these technologies are rolled out to people today?

I'm pro-nuance and also pro-consent, right?

So I think that if I had to say that there's one thing that people should be aware of about artificial intelligence, other than the fact we just discussed that it's here today and it's happening right now, is its dependence on data, and, you know, people have the notion that an AI robot is... You know, there's a genius programmer behind the scenes that's explaining to this robot how to respond to all possible scenarios, and that's not what it is at all.

The kind of AI, for example, that many folks have at home, an Amazon Echo, you know, we call it Alexa, and we tend to anthropomorphize it, but it's a chain of algorithms, all of which rely very heavily upon data, and that's your data.

So, you know, Alexa, when you ask it, you know, to give you a recipe for spaghetti bolognese, it's getting better at that with every interaction, not just yours but all of the ones across the country and the world with people asking it similar things, and I think that dependence on data, it's crucial for the success of these modern AI systems, but there's also the flip side of the coin, that we should certainly be aware of how and why our data is being used for these purposes.

And, yeah, if I had to have the message out there, data, you know... Really, AI is just probability on big-data steroids, and, you know, you got to be aware of how your data is being used, no question.

Right now, there doesn't seem to be that type of transparency.

If I have a Google Home product or an Alexa device, we're sold the convenience factor.

We're not necessarily sold that, 'Hey, by the way, your information is being taken in as part of the aggregate, but it is technically still your information,' or whether I own all of my search queries going forward or whether Amazon is entitled to have a copy of it because I'm using their device.

Yeah, you know, I think you point to an issue with, say, those user agreements that everybody just sort of clicks through whenever they...

I accept.

I accept.

Yeah.

Exactly, and they don't bother to read the 37 pages of legal permissions and constraints and what they're actually signing over.

Like I said, I'm pro-consent, and I think that there's, you know, actually a good movement within AI and machine learning these days coming more from some of the academic side to make those more transparent.

Well, let's also help people understand that there's a difference between kind of narrow artificial intelligence that can do one task really well versus, again, that kind of all-knowing, all-seeing Terminator or Borg that's going to come after us at night.

Yeah, absolutely, and I think that right now, you know, there is nobody on the planet that has any idea how to build any kind of machine with general intelligence in the manner of a human or a Terminator or something like that, and I think that that narrative, actually, and you hear it coming from the Elon Musks of the world and some people that are a little bit more apocalyptic about the future of AI... You know, I'm ultimately optimistic about what AI will bring us, and I do think that there are a lot of concerns that arise from narrow AI.

When I think about those kinds of narrowly tailored applications of artificial intelligence, I do have some concerns, you know, things like jobs.

You know, how can we build a social safety net that's going to be capable of addressing short-term job disruptions?

I think about inequality, you know, how to mitigate the concentration of wealth and power in the hands of large tech firms, and, you know, will the people who own the smartest robots own the future, that sort of thing.

I think about privacy and the things we've talked about, how good AI boils down to finding patterns in data sets about you.

That's your words, your online behavior, your health outcomes and so on.

Well, put this in perspective.

Is the AI evolution/revolution that we're living in now, is it as significant as the industrial revolution was?

Is it our shift from agrarian societies to urban centers?

You know, that's probably a question for a sociology of technology person.

You know, I tend to think that it is.

Generally, how big of a deal is it?

I think it's a very big deal, and here's why.

I think that if you ask what are our capabilities that the industrial revolution radically enhanced, it was our physical capabilities.

You know, you no longer had to be, you know, a person with a hand drill to try to drill through rock.

Instead, you had industrial machinery that would drastically magnify your physical abilities.

And then I think of the technological revolution of the early to mid-20th century that culminated in computers and rockets, and, you know, all those applications of computing technology, those went hand in glove with our own deductive capabilities, you know, just reasoning from conclusions to premises.

All of a sudden, you know, you could add, you know, a billion numbers together at lightning speed that you never would have been able to do just because of the constraints on your own brain.

Well, you know, if you think industrial revolution has our physical capabilities superseded or augmented, the computational revolution has our deductive capabilities augmented, well, the AI revolution is going to augment our inductive capabilities, our ability to see patterns, to learn what kinds of inputs tend to go with what kinds of outputs, and so, you know, those three together, I think, really do make for three fundamental revolutions in the capability of human beings.

Now, in your book, 'AIQ,' you start talking about that we should be familiar with a language to be able to interact.

Give us an example of a lexicon that we should start to familiarize ourself with.

Sure.

So, you know, you've probably heard the term 'machine learning,' right, and that's a brilliant piece of branding by folks that, you know, sort of brought that, those kinds of methods, into the mainstream.

You know, what is machine learning, and how does that relate to artificial intelligence?

I see a tremendous amount of confusion about that.

I mean, it's hard for me to, you know, drive down the street here in Austin without seeing a billboard for a company that's going to bring machine learning and AI to solve all of your business problems and sell more Cheerios and all of this.

So what's the difference, right?

Here's the analogy I like to draw.

Machine learning is like the internal combustion engine.

It's a general-purpose technology that can be dropped into a lawn mower.

It could be dropped into a car.

It could be dropped into a prop plane, whereas artificial intelligence, that's the whole car, right?

That's the whole set of interacting systems of which the internal combustion engine is just one part.

All right. James Scott, author of 'AIQ,' thanks so much for joining us.

Thank you, Hari. I appreciate it.