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Podcast: Network of the future, part I

Illustrated brain made from computer nodes

 

By 2020, we'll have more conversations with bots than our own spouses. With the growth of artificial intelligence, the line between human and machine is getting so blurry you might not even know you're talking to a bot.

Sounds scary, right? Well, putting aside pop culture fears, this is where the world is heading. And it's an exciting opportunity for the logistics industry and companies looking for innovative ways to better serve their customers.

Derek Banta and Katie Duffy are at the forefront of UPS efforts to build AI into package delivery. In the first episode of a four-part podcast series, Network of the Future, the UPSers will separate fact from fiction on AI - pulling back the curtain on the technology and breaking down what it really means for forward-looking businesses.

They'll explain the origin of the UPS chatbot, illuminate the relationship between AI and language, predict the future of artificial intelligence and provide their personal Holy Grail for the technology.

Is the human touch always better? How has AI changed their buying habits? And could we one day send a package emoji to a chatbot to initiate a delivery?

They'll explore these questions and more in the inaugural episode of Longitudes Radio, the first of many discussions in coming weeks and months on trends shaping the world of today and tomorrow.

Transcript: Network of the future, Part I

Brian: 00:00:27 - This is Longitudes Radio, a podcast with today's leading experts about the future of technology, global trade, sustainability and logistics. From Atlanta, I'm Brian Hughes.

James: 00:00:40 - And I'm James Rowe.

Brian: 00:00:42 - Brian Hughes here with UPS Longitudes. I'm joined by James Rowe, also with UPS Longitudes. And James, today we're going to be talking about machines.

James: 00:00:50 - Yeah.

Brian: 00:00:50 - And more specifically, we're going to be talking about AI.

James: 00:00:53 - Yes. Artificial intelligence.

Brian: 00:00:55 - Yeah. It evokes a lot of different things, not all of them good. I know a popular cliché is the rise of machines. But what I like about the conversation we just had with some UPS experts is they were able to separate fact and fiction. They were able to say how we can use AI, what it is, what it isn't, and perhaps most importantly how it'll transform the way we move goods around the world.

James: 00:01:20 - Yeah. I mean you mentioned there's a little bit of a dark side to it. But there's also some history. So, before the podcast, I did a little bit of reading and there's pretty interesting stuff here. It really kind of started off as a myth and fiction in the past. The Greeks talked about it thousands and thousands of years ago, about machines that were endowed with human consciousness. Fast forward to the medieval time. They kind of had the same thing. They, the alchemists thought that they could actually put consciousness into metal objects and things like that.

00:01:56 - But where it really took off was in the ‘50s. Back in 1956, there was a conference that was called the Dartmouth Conference and there were several of the big hitters at the time, very smart people who got together and they branded the name artificial intelligence and that's kind of where it started. And then after that, you saw a really rapid increase of activity of people trying to create simple algorithms that could - you could communicate with a computer like that. It was very basic. But now you see it in movies now where it's much advanced like Hal in the ‘70s.

Brian: 00:02:34 - Close the pod doors.

James: 00:02:35 - Right. Close the pod doors.

Brian: 00:02:36 - That's very important.

James: 00:02:37 - What's another movie that we could throw out?

Brian: 00:02:40 - Terminator.

James: 00:02:41 - Oh, yeah. Well, Skynet went live...

Brian: 00:02:43 - You hear the Skynet extra _____ you told me...

James: 00:02:44 - I think we've already passed that date actually. There was a minor celebration on that.

Brian: 00:02:49 - So, before we have a movie podcast, let's introduce our listeners to our experts. The first one is Derek Banta. He's our Director of Mobile and Digital Engagement here at UPS. And what I really liked about Derek is he was able to apply some real world scenarios for the next few years, not just about what UPS is doing, but how AI could transform international commerce as a whole. And we also have Katie Duffy. She was our Solution Architect for Chatbot. You might be familiar with Chatbot. It's the technology that UPS uses to answer our customers' questions. When they go online, when they use Skype, when they use all technology today, they're sometimes talking with Chatbot, which is not a human but has been programmed and designed in a way to both maximize efficiency and mimic the human qualities that we like best.

James: 00:03:40 - Yeah. And specifically, we'll talk about in this podcast about how some of these technologies are being rolled out at UPS. You're going to hear some terms like My Choice, which is an app that we have that helps you track your package and individualize your shipping experience. Sometimes they call the - when you get on the telephone and you're waiting in line to either talk to a customer service rep or you're getting kind of the recordings, I think they call that IVR. But we also have Orion, which is a algorithm that UPS developed to help predict what's the best course of traffic to take when you're taking your delivery route to make it most efficient and cost effective. So some of those technologies use AI and I think we're going to talk about that, right?

Brian: 00:04:27 - Yeah. And beyond products, we'll be talking about philosophies in general. This doesn't amount to a whole lot if you can't get consumers to trust AI. So, we're going to ask both Katie and Derek about how you do just that. So, without further ado, we hope you guys enjoy this conversation.

00:04:45 - Thanks for being here, Derek, and thanks for being here, Katie. We're really looking forward to this conversation on AI today.

James: 00:04:50 - Yeah. This is exciting.

Katie: 00:04:51 - Yeah. Absolutely.

Brian: 00:04:52 - Yeah. So I think a good place to start is there's a stat from Gartner, the research firm, that predicts that by the year 2020 we'll have more conversations with bots than our own spouses. Now, for some people that might be scary. For others, I don't know. Depending on their marriages it might be a welcome development. I'm not sure. But, how do you, Derek, kind of process that shift? It's kind of remarkable the degree to which bots will be omnipresent in our lives.

Derek: 00:05:19 - Yeah. For me, I just have to watch my kids interact with their devices and they go to Siri. They both have Apple phones. But they go to Siri as their go-to and I find that very challenging. So, to watch that shift happen with the sort of digital natives growing up, you see that that is evident and it's not something we're going to be able to sidestep.

Brian: 00:05:40 - Its inevitable and Katie, is there, I mean does that surprise you, the degree to which bots are just going to be a part of everyone's everyday interaction, even more so than their spouses?

Katie: 00:05:52 - Well, it's really interesting because I was just attending a webinar last week and someone threw out a statistic that said 40% of people use voice searches at least once per day. And it's precisely what Derek was talking about. You look around us and we are surrounded by Siri, Cortana, Alexa, Google Home. And the average human is supposed to be able to speak up to 150 words per minute, but only type on average 40 words per minute. So, this whole idea that we're going to use conversation as a platform to engage with our customers is just the next logical leap.

James: 00:06:31 - And then if you translate that to a mobile device, how many words can I type with just my thumbs? It's certainly not 150 words per minute.

Katie: 00:06:38 - Yeah. So, it's exciting to think that we can use natural language to engage with our customers now.

Brian: 00:06:43 - Just for framing purposes for this conversation, Derek, how do you define AI? I know there's lot of definitions out there for what AI is and isn't. How do you look at this space?

Derek: 00:06:54 - So, I hear machine learning and artificial intelligence kind of being used synonymously and they're not. AI is a large faction of computing that really is about simulating human behavior within computers and machine learning is a component of that. So, if I show a computer a picture of a bulldozer and another picture of a bulldozer and another picture of a bulldozer, eventually it will learn what a bulldozer looks like and can predict that the next thing coming is a bulldozer. So, that's sort of how I would couch machine learning. It teaches something to a computer that it can then pick up on later.

00:07:32 - Artificial intelligence is a little bit different in that AI is actually teaching that computer to act and react more like a human being. So, I consider machine learning sort of a subset of AI and I think that's regularly accepted, but I often hear them being used interchangeably and they're not.

Brian: 00:07:49 - I am guilty as charged. So thank you for educating me. Is that how you look at it, too, Katie?

Katie: 00:07:54 - Yeah. Precisely. I, in general I like to think of artificial intelligence as an umbrella that kind of encompasses everything that machines do that we consider smart and then machine learning is that subset of artificial intelligence where machines, they use data to draw intelligent conclusions and learn for themselves. So, yes, consistent views there.

James: 00:08:18 - So, let's break this down a little bit. A lot of people kind of know what AI is, but how does it actually function? Like how do these programs come about?

Derek: 00:08:27 - So, that's a great question. I think one of the easiest use cases you can look at is Waze. So, if you leave this building that we're in and you go home, there's probably 150 different routes that you can take and you would simply - Waze, one, at the time of day that you're leaving recognizes you're in all likelihood going home and it gives you the best route to get home. That's using the internet of things, artificial intelligence, traffic cams, all of these different things sort of converging into one to optimize your route home. And then you can, of course, step in and override it as a human and decide, no, I need to stop at the store so I'm going to take a different route. Or you could even tell Waze where you wanted to go and it would actually optimize that route for you.

00:09:07 - So, it's sort of all of those things coming together to optimize. It starts as an evolution of humans telling it what it should be doing and then it learns over time and becomes really, really good at it. So, they all are sort of built on networks and the more you have, so the more people updating traffic the better.

00:09:27 - The most recent interaction I had where I saw leveraging AI is actually the map function on my Apple phone. I was looking for a fish tank store and I Googled two of them. They were about the same distance apart and one of them said the average person there spends 30 minutes, the other one said 25 minutes. So, I looked at those two and said I'm going to the one where the person spends more time because my idea would be they would have more inventory or it's really poorly laid out. I'm hoping that it's better inventory since the average person is spending more time there. So, it invades every - it's pervasive in every segment of our life and sometimes it's just happening in the background and we don't even realize how much we're actually interacting with AI.

James: 00:10:08 - So, those of us with a little bit of background in programming, like Basic and some of those from many years ago, would remember the if/then statements in there. So, when you look at AI does it really boil down to like an if/then statement, if they say this then these are the variables that we could throw back at them? How does that work?

Katie: 00:10:30 - So, sometimes it's based on knowledge basis. But in other cases, like the UPS Chatbot that we developed it's actually based on something called natural language understanding, where you can actually train a linguistics model as you're having your conversation. You can train that model to recognize that a package maybe synonymous with a shipment or a home may be synonymous with a house. So, in some sense there may not actually be code involved if you can train your natural language understanding as you go. So, we now have those capabilities outside of hard coding a lot of the things that you consider natural language.

Brian: 00:11:18 - So, Katie, for the uninitiated can you explain what UPS Chatbot is?

Katie: 00:11:23 - The UPS Chatbot started out as a summer intern project in the summer of 2016 where we were trying to leverage a new technology that Microsoft had just unveiled in the spring of last year called the Microsoft Bot Framework. And the Bot Framework allows us to create chatbots that operate across multiple platforms like Skype and Facebook, for example, and you can chat with UPS now almost as if you're just chatting with a friend. You can add the Chatbot as a contact in your phone, in your Facebook Messenger, as one of your Skype contacts, and you can simply text to it and ask it questions about UPS.

00:12:09 - We also added a voice feature to the Chatbot whereby you can chat with UPS via the Alexa device. So we built a UPS Alexa skill that lets you now talk to UPS and ask it questions such as, "Alexa, ask UPS where the nearest UPS location is."

Brian: 00:12:29 - So, Katie, I can't be certain of this at all, but I would imagine in the early days of Chatbot there were some speed bumps. Were there any lessons or stories that stand out to you from just, I don't want to say glitch, but just some things that you had to get past in the early days of Chatbot.

Katie: 00:12:47 - Well, one of our hurdles came from just simply being a very early adopter of the technology when we first went to market with the Microsoft Bot Framework. It had only been introduced several months prior. So, in terms of that, we had to do a lot of learning on our own. But even in terms of the voice experience specifically, we have kind of a funny story about the Alexa voice experience.

00:13:13 - So, as you know, the vast majority of UPS tracking numbers start with the number one followed by the letter Z and then a series of 16 letters or numbers. So, this is an 18 digit tracking number that the customer would have to speak to the Alexa device in order to track the package. So, you would say, "Alexa, ask UPS to track," and then you would say, "1ZX5R6," and so on and so forth.

00:13:45 - Well, what was happening, and this just kind of showcases that some of this voice technology is not yet perfect, but what was happening is Alexa was interpreting the one and the Z as a onesy, as if it was the baby's outfit onesy. So, by the time that voice interaction had got interpreted into text, we were receiving the word onesy. So, we weren't able to track the vast majority of shipments that the customers were asking for.

00:14:17 - So, I guess the moral of the story is that this sort of hiccup that we encountered was actually a really strong motivator for the implementation of My Choice in the Alexa voice experience because now instead of you having to read the entire tracking number to Alexa, all you have to do is say, "Alexa, ask UPS if I have any incoming packages," and it avoids the need to speak the entire 18 digit number.

Brian: 00:14:46 - Let me ask you this, because I think this is probably a fundamental question as it relates to AI. I've got to be honest that when given the option, I think if someone said you can either talk to a machine or talk to a human, I would probably defer to the human. Maybe I'm old-fashioned. How did that natural instinct shape how you developed Chatbot, this idea that people want to talk to other people?

Derek: 00:15:10 - There's nothing more frustrating than being caught in IVR hell. You call your bank or your cable provider and they ask for the maiden name of your mother or your date of birth, your Social Security number. You provide all of this information and then you get to a dead-end and get disconnected or, worst case, they transfer you to a human being who then starts...

James:00:15:33 - And you're asked again.

Derek: 00:15:34 - ...entirely over and you're asked for everything. It's like well why aren't these things communicating with each other? So, I sort of think of that as IVR hell. So that's like the worst case scenario that you get to.

00:15:46 - And in the other case, we're trying to get to where our customers are. And so that was sort of us as a backdrop is how do we, a, get to market first and, b, do it in such a way that it's pleasing to use. If you've ever been on Facebook or Skype, you won't gravitate towards things that are not useful.

00:16:03 - So the idea is meet customers on their terms in their space and be useful. So that really got us to our first enhancement, which was integrating My Choice, asking the Chatbot do I have any packages coming to my home. So now, that's something that's useful and allowing customers to interact in their space on their terms without leaving their application but still getting the necessary answers that they're looking for. And then, of course, Katie and her team programmed it to do all of that. We simply provided the guidance of, look, this has to be a cool, fun if you want to use it personal experience. So, we want the Chatbot to have a little bit of personality. It can't be just vanilla.

Brian: 00:16:42 - Katie, how did you go about injecting some of that personality into the Chatbot?

Katie: 00:16:47 - Marketing helped us kind of add that personality in its responses. So when you ask the Chatbot something, we map that inquiry to an intent and then we, behind the scenes, devise an answer for you. But then prior to giving a human readable response back to the customer, we were collaborating with Marketing on what those responses should really be. And, of course, we want them to have personality and be reflective of our brand. So that's really where Marketing stepped in to help us craft what that personality should be.

Brian: 00:17:23 - Derek, we've kind of talked about what AI is and what it isn't and I think the Chatbot is a great example of its capabilities. But can you talk a little bit about how AI applies to the network of the future itself, this idea that we're going to seamlessly move goods faster than people ever thought possible?

Derek: 00:17:42 - So, it's definitely an interesting question and I think you have to hearken back to the early days of UPS. I mean we're an engineering company at heart. We engineer everything to be as efficient as possible and how could we not look at AI to help us do that? So, with that sort of as the backdrop, you can go back to Orion. Orion is our basically dynamic dispatch tool. It gives us the ability to be more efficient and save miles on every route driven. And if you think about it, four miles a day doesn't sound like a lot. But when you apply that to four miles a day per driver times thousands of drivers a day, you get enormous savings.

00:18:19 - So, Orion is actually using both machine learning and AI. So, in a clustering algorithm it actually says these packages should all be delivered together to be efficient and that's really using machine learning. But at the same time it's actually treating the Orion system to think and act like a driver to optimize their route. So, instead of having a time sensitive delivery, a driver - we call it break trace - stops the route, goes off route, delivers a package and comes back to where they pick off. Orion actually has them break trace, go make that delivery, and then re-optimizes the package car from that point forward, saving us miles.

00:18:56 - So that's sort of the tip of the iceberg. And I think as we get better with Orion we'll see those savings get compounded. So there's a tremendous amount of untapped space in the logistics world in addition to the customer experience world.

James: 00:19:09 - One of the things, and I'm not sure which of you could really respond to this, but when we talk about predictive analytics and you get into AI that is predicting things that it needs to do. So like in Edge, we've got PM sort that we're working on and developing that can judge, okay, well this package car needs to be unloaded first because it needs to go to air and that needs to go out quickly. So, there's predictive technology at work here. How do you think that that AI will start to impact UPS's network as we develop it for the future?

Katie: 00:19:47 - In terms of how it's going to impact us, it's obviously going to create efficiencies that we've never seen in the past because these predictions are based on actual data. So even in terms of trying to predict when the package is going to arrive at someone's home, you have a wealth of data based on past experience that's going to help us with that. So, I think it's just going to make us a lot more accurate in terms of delivering the kind of service that our customers need and expect.

Brian: 00:20:17 - This really doesn't amount to a whole lot if you can't get consumers to trust AI. At the end of the day it's a question of trust. And, Katie, how do you go about maybe building that trust and getting people to the point where they almost look at dealing with machines in the same way that they might another human?

Katie: 00:20:37 - Well, I think what it's really going to boil down to is this evolution of natural language understanding. So, as the evolution happens it's going to become harder and harder to tell the difference between human and machine. I'm not sure if some of our listeners have ever heard of the Turing Test. But fun fact for the day, in 1950 Alan Turing developed the Turing Test, which is this test where an interrogator tries to determine if they're speaking, they're interacting with a human or a machine. I'm not convinced we're quite there yet with any of the products that we've put out. But I think that the natural language understanding is such an important aspect of that and there are also services that help to detect the customer's emotion today.

00:21:29 - So, not only are we making strides in understanding the customer's intent in these very natural conversational ways, but we're also making strides in that if we can detect that a customer is very upset, maybe sometime in the very near future we'll be able to immediately route your conversation over to a live customer service agent. So, I think it all has to do with just kind of making the customer feel more comfortable in that interaction and because conversation is being more widely adopted as a very accepted platform, so we're kind of using language as the user interface with all these virtual personal assistants. I think there's this culture that's kind of been brought up around us where the general public does feel comfortable with a lot of these things and just kind of using conversation as a means to interact.

James: 00:22:28 - But there is - you're touching on this - there is a positive aspect to this where, like you were saying earlier, Derek, you're on the phone. You're punching in the numbers. You're advancing. You think you're going to actually get to a human and you hit a dead end. And with machines, if we get the trust factor up and we get the intelligence up, hopefully that ends in a much more positive experience, right?

Derek: 00:22:52 - Well, I think Katie touched on this a little bit, which is the concept of getting people to interact and read that emotion, so knowing when it's time to hand over to an agent. So the beauty of a chatbot is I can actually pick up where I left off. So let's say I'm on the phone with my cable provider for say two hours trying to resolve an issue that happened on a Saturday right before a football game. I'm still bitter. The idea is if I get disconnected with them, I have to start from scratch.

00:23:21 - If I'm interacting with a chatbot, I can come back at any time to that point in that conversation and pick up where I left off. So, if we can read the intent right, like Katie was talking about, and see levels of frustration being escalated, I can actually hand off to a representative and that representative can catch up to exactly where I am in that conversation, understand what my point of frustration is and be empowered to take action. And companies that get that right will separate and differentiate themselves from all the other companies in the world.

00:23:51 - But I did want to go back to your the fear of machines. I look at my grandmother. She never had an ATM card. I look at my mother. She had an ATM card, had an issue with the bank and will never go back to the ATM. I can't live without my ATM card. I don't know that my kids will ever live without the Cash App or Venmo app or whatever it is. The reality is we have digital natives that are growing up in this space where all they know is technology. Watch a two-year-old walk up to a TV. They think they're interactive. They try to swipe them. So, this is engrained in what they do on an everyday basis.

00:24:25 - So that fear of interacting with machines comes with successful interactions with machines over time. So, at the same time my mom is afraid to use her ATM card, she's more than happy to take recommendations from Amazon, which is recommending, hey, other people who bought this bought that. What is that? That's AI giving predictive analytics of what she might buy. So she's interacting with a machine but not thinking about it as interaction with a machine. So as those lines get blurred, trust gets built. So you have good experiences every day with machines.

Brian: 00:24:59 - And Katie talked about not being able to tell the difference between machine and human. Our listeners might be surprised to learn that one of us is in fact not a human. I'll let them figure that out as they listen to the rest of this podcast.

James: 00:25:13 - Yes, Brian.

Brian: 00:25:16 - Hopefully I don't sound so robotic that I'm the one they anticipate. But, I digress. Katie, you've been working at UPS you said for two decades and you're at the forefront of some of the most futuristic things that we're working on. Has anything surprised you, the degree to which it's moving?

Katie: 00:25:35 - I will admit that things are moving faster than ever before. I was just reading a statistic that there will be ten million self-driving cars by 2020 with one in four cars being self-driving by 2030. And that sounds like a pretty outrageous prediction, but the premise behind that prediction is that technology is just taking off at a pace that's unprecedented. The article also mentioned that when you think about the number of years it took for the public to adopt I think it was just like electricity and then you look at just the short amount of time that the smartphone has really just boomed and that was more of a period of like maybe five to ten years, that new technology is just being adopted at an exponential rate. So, in the next ten years it's really exciting to think about how much change can occur in the next decade.

Derek: 00:26:43 - To build on that, I believe Facebook introduced their chatbot functionality in May of 2015 and by July of 2015 - it could be 2016 - they had 43,000 bots that already had been developed. So, in a period of months we went from no market whatsoever to 43,000 chatbots being in the marketplace. That is breakneck pace.

James: 00:27:11 - Yeah. And when you talk about the difference between the quality of those bots too, I was listening to something on Radiolab where they were talking about AI technology. You've got things like Watson that are well-established, have a very rich and deep database, and then you have more current ones that are just rolled out. So, is there a differentiation between the quality of those bots and what kind of experience they can offer?

Derek: 00:27:39 - So, my interaction with bots has been just sort of learning about what they are, going out and experiencing them and the quality varies. There could be a joke of the day bot to sophisticated travel bots. So, it really depends on what you're doing. I think Amazon is trying to set the pace. I'm not going to remember the name of what they just introduced. But it basically gives you feedback on your outfit. That's pretty remarkable what they're trying to do...

Brian: 00:28:09 - I don't want that feature.

Derek: 00:28:11 - That's what they're trying to introduce to the marketplace. And they're going to have some things that are ahead of their time and they're going to have some other things that just hit homeruns. And I think the key here is to get something up and get it at a good enough quality that it's market-ready.

Brian: 00:28:28 - This is a philosophical question for both Katie and Derek. Katie, I'll start with you. With any technology there's both low hanging fruit and the Holy Grail. By low hanging fruit, I'm talking about the things that we can do right away that perhaps might not require a ton of legwork. But I'm curious from a logistics perspective what do you see as the Holy Grail for AI?

Katie: 00:28:50 - So, in terms of really kind of pushing the envelope with AI in the Chatbot and the voice arena, it would be really cool if you could send the Chatbot like a package emoji, like a picture of a package and we could instantly interpret that as meaning I want to ship a package with UPS. Or if you said to Alexa, "Alexa, ask UPS to ship a ten pound package to mom and I'd like it delivered by Tuesday," and then we go ahead and send that shipping label immediately to your email address or your mobile device and we charge your credit card right there on the spot, all based on that single voice command.

Brian: 00:29:37 - Yeah. And do you have a Holy Grail, Derek?

Derek: 00:29:39 - Yeah. I think for us it's meeting our customers on their terms in their space in ways that are probably not yet imagined. If you think about the way that Uber disrupted the taxi community, that's an avenue that I think AI has the ability to disrupt the transportation world. We need to be thinking about ways in which we can apply artificial intelligence in other things, internet of things, etcetera, all working together to create a unique customer experience that may not be imagined today.

00:30:11 - So, there's things that Katie's talking about, which is going down the path of continuing to ship packages from A to B. But the idea of being completely disruptive leveraging this type of technology I think is super exciting. I think I read a stat the other day that said 90% of the data that's been created in the world has been created in the last two years. So, that is powerful. There are ways in which we can leverage artificial intelligence to, and predictive analytics and other things to create customer experiences that would help UPS deeper engrain themselves in our customer supply chains that are super exciting. Imagine the ability to reorder with a tracking number. Imagine the ability to learn from everybody's shipping experience across the globe for imports and exports. Those are things that AI gives us the ability to do and it's super exciting.

Brian: 00:31:06 - Well, Derek, Katie, thank you so much for being here today. If you've accomplished nothing else, you've taught me to embrace the machine. So, I don't know about you, James, but I'm getting there.

James: 00:31:16 - Yeah. One with the machine. I appreciate it.

Brian: 00:31:19 - Thank you so much, guys.

Derek: 00:31:20 - Great. Thank you.

END

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