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How Artificial Intelligence Is Changing Our Lives

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William Ammerman, Invisible Brand, Artificial Intelligence Changing Our Lives

With William Ammerman, advertising executive and author of The Invisible Brand: Marketing in the Age of Automation, Big Data and Machine Learning

Steve spoke with William Ammerman about how artificial intelligence, AI, is drastically shaping our world. In his book “The Invisible Brand: Marketing in the Age of Automation, Big Data and Machine Learning, Ammerman explains how AI is already bringing changes to our world and how it may well infiltrate every area of our lives in the future.

The Invisible Brand And Technology

We all experience the invisible brand of AI through technology. We are constantly using our devices: smartphones, tablets, smart televisions, etc. Forces involved with these devices, corporate brands, government, political entities, institutions, are trying to shape and manipulate us, attempting to change how we behave through technology.

Advertisements come at us from all angles, always something new to click on, so much trying to motivate your behavior in a certain direction.

AI In The Marketing World

Here’s what we really need to learn: AI is playing a major role in the marketing industry. Before, information came to us from mass media. The same messages hit everyone, through the TV, the radio, and in print publications. However, the introduction of the internet into our lives changed everything.

Now, we get the information we want. We pick and choose. The internet enables companies to develop and distribute messages on a personal, one-on-one basis. We’ve moved from the age of mass delivery of information to one that is customized and tailored, all powered by AI.

The Major Movements

A few major movements are happening today. One is mass manufacturing. For example, General Motors and Ford manufacture hundreds of thousands of cars, enabling them to flood the market with their production.

Another movement is mass distribution. Proctor & Gamble (P&G) being a great example. Because of AI, companies have been able to shift from localized to mass production and distribution. P&G was a major innovator, streamlining the distribution of consumer-packaged goods and changing the way the industry distributes goods and services.

The final movement is mass customization. Target offers a great example of this. The data analysts at Target examined the consumption patterns of women and used it to determine when they were pregnant. Figuring out that women make vital decisions about what they consume when pregnant, Target launched a campaign by sending out mailing advertisements to pregnant women. One of these ended up going to the home of a 16-year-old girl whose father was angry at Target for their “mistake”. As it turned out, his daughter was actually pregnant.

Target used this as a learning opportunity to understand how to be more careful when targeting consumers and began to camouflage their marketing tactics. Target mixed the pregnancy advertisements in with other ads to make the targeted ad less obvious.

This was essentially the birth of the invisible brand. Consumers don’t want to feel stalked or targeted.

We’re Being Watched

AI is already hard at work. The reality is that we’re essentially being watched everywhere we go. If you take the turnpike and go through the toll booth, there’s a camera to take a picture and you receive a bill in the mail for the toll costs.

If you have Bluetooth turned on on your phone, and you walk into a store, if the retailer has Bluetooth, they can track your path through the store. They can determine where you go and determine the products that are most important to you.

Your phone is truly the key to everything. Companies and other organizations can simply gather information from your phone and learn an incredible amount about you by where your phone has been. Targeted ads can then be sent to you based on that.

An Uneven Playing Field

Companies today, through the use of AI, know what motivates us and drives us to buy. They have a number of manipulation tools they can employ in their marketing, such as reciprocity. For example, if you invite someone for dinner, reciprocity would drive the guest to return the invite. This is reciprocity on the simple level. Used in marketing and commerce, an individual might get a great coupon to use at a certain store. That individual is then more likely to continue shopping at that store.

Machine Learning

Machine learning is a subset of AI. The starting point for all of us – including those who study AI – is machine learning: natural language processing, robotics, etc.

Machine learning is the ability to not only use statistics to predict the future but to begin the development of tools and tactics that will actually change the future. It is figuring out patterns in the data, allowing marketers and advertisers to adjust the way they approach consumers. This maximizes business efficiency and boosts revenues, drawing in and keeping more customers.

Machine learning is a lot about discovering how people behave. But it is also about learning how to shift the approach to target more customers in a new way that is somewhat secretive.

One somewhat chilling example of this is in China where they are using machine learning to monitor how their people behave. They have instituted a credit system, where people are given points for behaviors that are positive towards the Communist Party and demerits for negative behaviors. These social credits are used to deliver everything: food, clothing, housing, etc. This is chilling because, with a system like that, the government can effectively control how people act and what they can and can’t buy.

Machines Are Becoming “People”

Machines are developing at a rapid pace and becoming incredibly good at mimicking people. Stories that have been written entirely by computers that are hard to spot. Avatars and “deep fakes” are mimicking actual people in video and picture form.

Machines can also to imitate some of the greatest artists the world has ever seen. To understand this, machine learning needs to be deconstructed. A generative adversarial network is an algorithm that generates billions and billions of combinations that enable machines to replicate art from the masters.

These algorithms are also used to judge which images would pass as something that an individual might buy, using a dataset of past purchases of, in this case, paintings and then designs images that a person is likely to buy.

We aren’t to the point where robots will seamlessly slip into the human population and begin to take over. Still, new potential applications of AI are being discovered each day. AI will continue to be a major part of our daily lives.

If you’d like to learn more about artificial intelligence or William Ammerman, visit his website, https://wammerman.com/.

Disclosure: The opinions expressed are those of the interviewee and not necessarily United Capital.  Interviewee is not a representative of United Capital. Investing involves risk and investors should carefully consider their own investment objectives and never rely on any single chart, graph or marketing piece to make decisions.  Content provided is intended for informational purposes only, is not a recommendation to buy or sell any securities, and should not be considered tax, legal, investment advice. Please contact your tax, legal, financial professional with questions about your specific needs and circumstances.  The information contained herein was obtained from sources believed to be reliable, however their accuracy and completeness cannot be guaranteed. All data are driven from publicly available information and has not been independently verified by United Capital.


Read The Entire Transcript Here

Steve Pomeranz: If you don’t know it by now, AI, or artificial intelligence, is hard at work changing us and trying to change our lives. If you don’t understand how this is happening, you may end up manipulated by a computer designed to convince you to buy or act in a certain way.

My next guest calls it the invisible brand, and in his book, The Invisible Brand: Marketing in the Age of Automation, Big Data and Machine Learning, he informs us on the ways in which AI is already shaping our world. William Ammerman joins me right now. William, welcome to the show.

William Ammerman: Thanks. It’s great to be here.

Steve Pomeranz: Why did you decide to write this book right now?

William Ammerman: We are all experiencing the invisible brand through technology. We are interacting with our devices, and there are forces on the other end, political forces, corporate brands, governments, institutions who are trying to manipulate us, change our behaviors through the technology. And I want people to be able to see that happening in their own lives. I want them to be aware of these hidden forces and to shine light on this invisible brand operating on us all.

Steve Pomeranz: I think we all do see that to a certain degree if we’re all involved in our smartphones and tablets and so on. We see ads coming on the sidebar, maybe based on a search that we did. We hear about other governments interfering in our elections and so on. So we’re starting to see that, only the subject is so vast, it’s very hard to get a handle on it, and that’s why I think this book is so important.

Why the focus on artificial intelligence, and specifically, what is that for us to learn about?

William Ammerman: Yeah. So artificial intelligence fundamentally changes the marketing equation. Before, we all received information broadly from mass media. The same message came to everybody off the television, off the radio, our print publications. But the internet allows us to tailor and deliver messages on a one-to-one basis. We can just talk to one individual. Your Facebook feed is different from my Facebook feed. The news and information I consume is different. And with artificial intelligence and machine learning, we’re now able to harness A-B testing to deliver messages just to you based on your wants and interests. So we’ve moved from an age of mass delivery of information to the mass customization of information, and that’s powered by artificial intelligence.

Steve Pomeranz: You write about three major movements. You just mentioned one, mass manufacturing, General Motors and Ford manufacturing hundreds of thousands of cars and doing it in a mass way. The second one is mass distribution, and you use P&G as an example. Explain that to us, please.

William Ammerman: Sure. In the consumer packaged goods industry, we’re able to actually shift from localized production and distribution to mass global distribution coordinated by technology. Proctor and Gamble was a big innovator in streamlining the distribution of consumer packaged goods, and it changed an industry, it changed the way we consume products.

Steve Pomeranz: There was a good example of mass customization, which you mentioned, and I think of Facebook when you say something like that or Google. But you have a story about Target, the company Target, sending out mailers for pregnant women. Can you tell us that story?

William Ammerman: Sure. It’s become a marketing 101 story that gets repeated. We were able to look at data … and I say we broadly … the data scientists at Target were able to examine the consumption patterns of women to determine when they were pregnant. That’s an important time in a woman’s life because she makes a lot of decisions about the products she consumes and will consume for the next 20 years, during pregnancy. So Target wanted to target that time in a woman’s life.

They sent out the mailing targeting pregnant women, and one of them went to a 16-year-old, and the father of the young girl who received the mailing was incensed that Target was delivering pregnancy material to a 16-year-old daughter. Unbeknownst to him, his daughter was actually pregnant.

William Ammerman: And so Target learned from this. They said, “Maybe we need to be a little more careful about how much the consumer recognizes that we know about them,” and they started obfuscating their marketing tactics. And I say in the book that that was kind of the birth of the invisible brand, is when the brands learned that people don’t want to feel stalked, they don’t want to feel as though their personal information is being used by companies to deliver advertising messages. And so Target decided, let’s start mixing up the pregnancy ads in with gas grill ads and other ads that would obfuscate or make it less obvious how they were marketing.

Steve Pomeranz: Camouflage them, so to speak.

William Ammerman: Camouflage. That’s a great term. Yes.

Steve Pomeranz: All right, so we all experience this too. I live in South Florida, and we have the Florida Turnpike, and we also have I-95 as the major thoroughfares here. And I know that every time I go through the Turnpike, I’m being watched and I’m being notated. You mentioned in the book that you had a similar experience, and then six weeks later you received bills in the mail. And it’s like, “Well, how did they know where I was?” Well, they do.

So all of these detective programs on TV seem to me to have the tracking of people, they have cameras everywhere, and they know where you’ve spent your money through your credit cards and so on. So this is really pervasive and ubiquitous already, isn’t it?

William Ammerman: Absolutely. When you have your Bluetooth on on your telephone, you walk into a retailer, the retailer has Bluetooth detection in their store to watch your path through the store. They can create heat maps, they can look at the way various consumers move through their grocery store, through a retail center, a mall, an airport or a stadium, to determine where people gather, how they move through the aisle, whether they go to the milk first or the section for frozen products.

So all of this is important information to marketers, and your phone is the key to that. And one of the things that people don’t realize is we don’t actually need your name; we can look at your phone ID, and we can tell a lot about you because we know where that phone’s been, what it’s been looking at. It doesn’t even matter what your name is, as long as we can deliver ads to the device that has visited certain locations or has looked at certain information on the web.

Steve Pomeranz: There’s an uneven playing field here. And I always like to bring this up. For example, quickly, when you buy a car, you buy a car maybe once every 5 or 10 years, and yet the person who’s selling you the car does it every single day. There’s an uneven distribution of power. Now companies have long studied and become experts in the art of manipulating us because they know what motivates us. And I want to go through this … this is from your book … go through this very quickly.

Number one, reciprocity—then scarcity, authority, consistency, liking, and consensus. And we don’t have to actually explain all those now, though I will ask you to, for example, explain reciprocity as something that motivates us.

William Ammerman: Sure. If you invite me over for a dinner party, that’s an indication that I should invite you back. So if you want to go to more dinner parties, invite people to your house and you’ll get invited to more dinner parties. That’s reciprocity at some simple level.

Steve Pomeranz: Oh, so that’s a motivation; that’s a human characteristic. Scarcity, we understand that we more desire things that are scarce than are plentiful. I think I understand that.

Now AI, artificial intelligence, turns these factors that motivate us into a set of rules behind the scenes. So take us through that a little bit and also explain machine learning in this context.

William Ammerman: Sure. Well, let’s start with that. Machine learning is a subset of artificial intelligence. So I did some postgraduate work at MIT in their artificial intelligence, and I think I was taught that machine learning, natural language processing, robotics, these are areas of the larger concept of artificial intelligence. So start there.

So when we talk about machine learning, we talk about the ability not only to use statistics to predict the future but to start developing tools and tactics that actually change the future. So what machine learning is doing, in a very real sense, is it’s figuring out what are the patterns in the data that we can determine and how can we then shift our actions, our marketing messaging, optimize it in a direction that leads towards a specific outcome, a KPI. And by maximizing that key performance indicator, we are bending people’s behavior toward some goal that we have as a business.

So learning how people behave is part of it, but not only learning how they behave but learning how they can be changed is a big part of what we’re using artificial intelligence to do.

Steve Pomeranz: Well, I guess when it comes to buying shoes or watches or dresses, it doesn’t seem to be all that important. But when it comes to adding that to politics or governing, then I think it starts to get worrisome. So are we seeing some of that in use right now, in terms of powerful institutions trying to manipulate us through AI?

William Ammerman: Well, if you want the hair to stand on the back of your neck, I think the obvious case is China. China is developing a social credit system in which they give people points for behaviors that are positive towards the Communist Party and positive towards China, and demerits and deductions if you act in a way that they consider negative towards the party. And they use these social credits, and increasingly they will be able to deliver everything from housing to transportation to food.

And when you have a system that’s big enough to give you all of those things based on social credit scores, they’re big enough to take those things away. And I think that’s a terrifying prospect. And it’s one that we can look at in smaller cases in the West, but one that we should also be paying attention to is Facebook is trying to introduce a currency, the Libra, in which they could potentially … and they say they’re not going to … but they could potentially pair your financial data with your social data. And by doing so, they can create opportunities to monopolize social trading or financial trading through social media. We’re going to penalize the businesses that play by our rules, we’re going to penalize the individuals that don’t play by our rules. We’re going to be able to extend favors and withdraw them.

William Ammerman: So what China’s doing, terrifying on a mass scale, but what American corporations are doing should be watched carefully because there are potential risks involved for all of us.

Steve Pomeranz: William Ammerman joins me. The book is The Invisible Brand: Marketing in the Age of Automation, Big Data and Machine Learning.

I have noticed that there are now news stories that are written by computer that are impossible to discern from human writers. They’re getting that good. Also, videos of, in effect, I guess artificial people, I don’t know what to call them, avatars or visual objects that look like people.

William Ammerman: Yeah. Deep fakes.

Steve Pomeranz: What are they?

William Ammerman: Deep fakes.

Steve Pomeranz: Deep fakes. And you can’t tell the difference now between that type of artificial person and a real person speaking with you.

Also, machines are now creating a level where they can create fine art in the style of the great masters. And I actually have a quote in your book from the president of Christie’s. Let me pull it up here. His name is Richard Lloyd. I’m sorry, he’s international head of prints and multiples at Christie’s. And he said in an interview in Time, quote, “We are all going through this culture shock again and again, where we think we’re talking to or interacting with a human, and suddenly we realize it’s a robot. It’s a light bulb moment that we’ll keep having.”

So they’re starting to see this in an area where it’s kind of a sacred area, you’re talking about the old masters and these geniuses, and now you’ve got machines that can copy them directly. Tell us more about this or take us somewhere with this.

William Ammerman: Yeah. So to deconstruct the machine learning is really helpful for everyone. And I’ll do this very simply. We call it a generative adversarial network, generative adversarial network. On one hand, you have an algorithm that generates lots of different combinations. In the case of art, millions and billions of combinations of different designs from the way humans have painted paintings. So you’ve got this generative function, it generates lots of combinations. It’s adversarial because there’s another algorithm that judges those outputs.

So the second algorithm is designed to judge which images, in this case, would pass as something a human being would buy. So it looks at a dataset of past sales of paintings at auction, and it says, okay, these designs pass the test of looking like something a human would buy.

So you’ve got two things working together. You’ve got an algorithm on one side that’s generating options, and you’ve got another algorithm working alongside it to judge which ones fit the mold. Now we can do this with paintings that we’ll sell at Christie’s, but we can also do it with recommendations for the movies you might watch. We can do it for generating music, we can generate all kinds of things.

And you mentioned something very important. You mentioned writing the news. We can now write news stories using a generative adversarial network that passes as copy that a human being wrote. Think about the opportunity for exploitation if you were writing copy that persuades people to buy a stock, buy a certain product. So there’s lots of opportunity both for good and some risks involved as well.

Steve Pomeranz: Not too long ago, I interviewed Gary Smith. He wrote the book, The AI Delusion. And in it, he makes a strong case for saying that AI will never be able to really act and think like a human. It doesn’t have the capabilities, the neural networks, however you want to put it. And I know that even today, when you go to sign up for a site or something like that, you have a thing called Captcha, where you have to pick the cars in a bunch of, like nine squares. You’ve got to find all the pictures in those nine squares that have a picture of a car. And a computer can’t do this. And it also can’t predict the future.

Unfortunately, we are out of time. I need more time here, but I don’t have it. How worried should we be, William Ammerman?

William Ammerman: The good news is we aren’t there yet, where robots can just blend into society and frighten us all. But the applications are tremendous, and there’s great good that can come of it as long as we’re aware of it. And I’d love people to read about that in The Invisible Brand.

Steve Pomeranz: And it is The Invisible Brand: Marketing in the Age of Automation, Big Data and Machine Learning. The author is William Ammerman. He can be found at wammerman or wammerman, that’s A-M-M-E-R-M-A-N dot.com, so wammerman.com. And to hear this in any interview, again, don’t forget to go to our website, which is stevepomeranz.com. And we put all the links that we mention and that we see in the book that we think are relevant on our website. And while you’re there, sign up for our weekly update, where you’ll get to enjoy all of these segments at your leisure every single week into your inbox. That’s stevepomeranz.com.

William, thank you so much for sharing with us today.

William Ammerman: Great to be here. Thank you.