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We found today's winner of the next Proto.io full year license. Loading Instagram. The name? Oh, you don't have it? M-S-Y-F-A-X? Do we have anybody here named that? It's not working. Yeah. There we go. Who's this? You still here? No? Okay. You're there! Congratulations. Please come up to me afterwards. I need your email. You won Proto.io for a full year. Thank you. Great picture. Yay! Okay. I can't believe these are our last speakers. I want this to keep going. So, hopefully I'll see you guys all in six months again when we do the UX 2016. I'm really proud to announce that Ross Smith and Dana Popa are here. We're here to do our last presentation of the day. I'll start with presenting Dana. Dana has a broad design background that spans from arts to interior design and design architecture. She has lived in Atlanta, Georgia, where Mailchimp is actually at. And on Cypress before becoming Master of UX and Video Game Design at ITU here in Copenhagen. Dana is a senior UX designer at One.com and has been there for about a year. And she specializes in gamification and manages to bring a twist of gamification into her UX methodologies, which to me sounds like a lot of fun. Dana tells me that she met Ross at a gamification conference once. And they're both really into gamification, but what they really bonded on was their shared passion of snowboarding and telling each other crazy snowboarding stories. Ross is, among other things, director of engineer at Microsoft, and he's worked with Skype since 2009, focusing on quality assurance, operational efficiency, and cost reduction. And what's most important to me is focus on employee retention and morale. That's going to be really exciting to hear about. Like Dana, Ross is very passionate about gamification and aims at improving customer experience by applying technical expertise using productivity games and gamification in the workplace. Ross has found that gaming reduces the cost of the game, reduces risks in your company, and especially if you have a hugely diverse population. Again, a huge thank you to our sponsors for flying in Ross. Thank you for being part of it also, Dana. I'm sad that they're our last speakers, but really happy to announce our last speakers of the day, Ross Smith and Dana Poupa. How about with it turned on? Is that better? So thank you. Thank you for the wonderful introduction. My name is Ross Smith. My official role at Skype is director of engineering for customer feedback and data insights. I'm just really happy to be here and have heard such wonderful speakers over the past couple of days and know that we're the last between you and the end of the conference, so hopefully we can keep you awake and keep you interested and send you on your way with some interesting thoughts. And I'm Dana. Nice to meet you all. Actually, we kind of met throughout the coffee break, throughout the lunch break, the dinners. Very nice. Thank you. Thanks for all the learnings for this week. And nevertheless, thank you for the organizers, and I think we should get a round of applause for them. Because it's been seamlessly done. So very, very nice. Thank you. And it was, yes. It's very nice to be here. And learn what you guys have been doing and the problems you've been dealing with. And through the last two days, we've seen a little bit of a reoccurring pattern. And the reoccurring pattern was where, like, how to connect and how to make bridges. Also, Eric was mentioning how to make bridges between the tech and the design, how to bring the stakeholders in. We heard a lot of this. Well, out of all the designers speaking today and yesterday, we have Russ that is coming in our team. And he's part of the tech side. So it's just we should take a better look and see who wants to also join and comes on board voluntarily, rather than thinking that all the time is a fight. So in this regard, we are very lucky. All right. I actually, because you've been a good learning experience, I took some notes of what has been going on for the last two days. And it was very nice to create, to listen from Airbnb of how to create a real connection for a real human connection. Thank you. Thank you. For plan A, how to get on board and maybe create your barista schedule starting January 1, 2016. Go for it. For Volvo, it hasn't been, it's not going to be anymore a bad thing to have your hands full while driving because you have to just trust Drive Me is going to take care of it entirely while avoiding confusion mode. to take care of it entirely while avoiding confusion mode. Possible, Peng will keep you calm while you are enjoying the flow of a conference. Nikki was telling us with driver that no interface is the best interface. So that's something maybe to think about. And also David with BBC creating standards which would be the fantastic catalog for innovators. And he calls it gel. And also Spotify, not sure if it's still here. But thank you Stanley, it was my favorite talk. But of course I'm being biased here. Because you have to be really patient about three years to get awareness around design, around your organization and learn about it and many, many more. Danish Design Center was just telling us of how to do design thinking and how to make cross references from design to business and to look also in other fields. sides rather than just interfaces. And also, thank you for the workshops today. Great learning. I've been part of the human-to-human interaction, and it was very nice. And it was great to see how to be an app. So after... Yes, thank you all for sharing. That's the best part of it. So what we're going to speak today is actually, if I go back to the title, it's human-centered design in the age of the machine intelligence. So why does it matter, and why talk about it? I think everybody has been talking about human-centered design to some extent, and how to do it or why to do it. You call it... User-centered design, you call it different names, but I think we are all speaking about human-centered design. And what is happening with the machine intelligence is... Think about it. Right now we are having our smartwatches and smartphones doing so many different applications. We are thinking of... Like, we spoke a lot about today, about January 2016, about 2017 with Volvo. A little bit maybe farther. In 2020, 2020. How about 2030? Think, what conference are we going in 2030, in 15 years only? Or are we going to have what? A watch? Are we going to have a phone at that time? So it's... Ross and I were looking pretty much at the same problem. And the problem is how we're going to design while the technology is... Developing so fast. And the machine is becoming more and more intelligent. I'll cover the part that I know, which is the design part. And then I will listen and learn from Ross for the part that he knows best about the machines. And the intelligent ones. So, yes. I just wanted to mention one more time. Many more here. What we also seen and what we are doing more and more these days. We are doing informed... Design and informed design decisions. And we are relating to big data or little data. Or we are relating a lot to user research these days. And it's starting to be more and more important. Because we are getting to know more the needs. And also the pain points of the users by understanding who they are. And then we can build what... What... What everybody has been pitching for the last two days. Human-centered design solutions. And the human-centered design solutions, there were... A lot of you said trust. Building trust. With the product, with the organization, with the team. It has been another thing that has been occurring quite a lot. But you also mentioned beautiful. And easy and friendly. And... So on. So what is that? It's... If we are looking at the Maslow Pyramid, we are going higher and higher. As long as Wi-Fi is on. We can get along with our... With our applications or whatever we are designing for. To satisfy more of the social needs, of the esteem needs and self -actualization needs. So it's becoming more and more human. And some good references. Maybe check it from time to time. Start. Or just start with it. Both from IDEO. And then... Or start with people. And starting with people, it's doing whatever you can do. Or whatever you have at hand to get closer to your users. And this is an example what... From a workshop. One.com. What we've done. We didn't have the time or the means to go and talk to the user. To send surveys. To track them. To whatever. So within very fast pace. What we could do is get closer to the user through the customer support. So we invited actually the customer support supervisors. That had also a broader understanding per country. And per different products. To help us understand what the user would be. And it looks quite similar to the tool that Christian from design center was presenting. And I call it business origami. But all it does. It brings people co-designing. But people that for us was the way to get closer to user and empathize with them. So finding what would be the pain point. Of our user through the supporters. Because they will get actually the complaints. Mainly. I'm not sure how many good job or you rock emails they get. And it was a very good discovery tool. And we learned quite a lot. And it was much easier to bring everybody on board. And empathize with what could be some of the pain points. And what could be some of the needs. So you get closer to it. So what the design thinking that everybody is saying. It's so important. And use it. And why using it. For business innovation. For functional innovation. It starts actually with people. You are empathizing with the people you are designing for. You can call them user. You can call them customer. You can call it anything they are. But usually they are people. They are not dogs or cats. I'm not sure if anybody is designing for dogs and cats. We haven't seen any examples. But yes. Look at the needs. Look at the pain points. Maybe also the things that they would desire. If can get on the wish list of what people would like. Then it's going to be. Going to come with some really nice and probably crazy ideas. And what we do. We innovate the experience. And innovating the experience that includes all the parts. So getting on board the business part. And if it's viable or not. Getting on board the technical part. Is it feasible? Can it be built? Of course everything is feasible these days. But it's going to take either six months or two years or ten years. It's a matter of maybe what increments you want to make. And what are going to be later. But if we are starting with the people first. And looking at what is the need. Then yes. We can build on top of it. And then you also have seen it quite a lot. This one. And you probably try it. And you try it all the time. Prototype. And that doesn't mean with any particular tool. With any tool. You feel most comfortable. Learn from it. And iterate on that. And learning can be testing with whoever. You know. And everybody has been mentioning this. So I think it's already common knowledge for all of you. So yeah. Until the first people that had the flight. The Wright brothers. I think they had some falls. So it's fine. Rio falls. Again. Exploring the possible. Solution. And then make the choices. I think you're going to get to. A choice. That has gone through. Also the edge cases. Not just through the sunshine scenario. So the more you diverge at the beginning. And understand maybe. The different angles of the. Of the problem you are solving. Then. The more you are making your choice. You are going to make the choice. That is also probably. Hopefully and most probably will cover. All the edge cases as well. And. With the design thinking. All of this is the design thinking. Method that. Anybody can jump on board. What. How to do it. And how to do it is through a language. And a language can be. It's usually the one that everybody knows. Is the pen and paper. The pen and paper can be. You know. A little playful way. Or it can be in sticky notes. As long as you are getting your idea down. And you structure it. You group it. Yeah. Go at it. Then for the other designers. For the designers that are. Specialized within the field. Of course we have to show it in a visual way. To gain the trust. The professional trust needed. From the other disciplines. And. After. Really thinking through the flows. And after really thinking through the problem. Then when you come to. A beautiful design. That also answers all the interaction. And all the flows. That. Product manager may ask. That a technical person may ask. That a stakeholder may ask. And you can answer all those. Then you are gaining. The respect. And this was actually. A good example. That went through all the way. In my organization. Which was very nice. And then if you can test. In any way. We already talked about iteration. I did some. Guerrilla user testing. And again. If you don't have the means or tools. Of testing or capturing. A lot of data about your user. What can you. What can you have. What do you have at hand. You have the people in your organization. Otherwise you have your mother. You have your grandmother. Probably if you are testing with your grandmother. And she gets through the flow. Then anybody will be able to get through that flow. So use. Whatever you have at hand. But it's nice to have somebody else. Looking it through. From a different perspective. And then. You have to design it. For yourself. And we are designing for. For the people. As we are starting with the people. We should keep them in mind. Throughout our process. Persona or not persona. But we should remember. That we are not designing for. Ourself. Of course. And then work on it. The pixel is not really correct. The alignment is not really correct here. As a designer. I don't know how that slipped. But I will iterate on that. Next time. But the most important. Is to understand. And frame the problem. Then explore the solutions. And then develop. And that can be in cycles of. I think you mentioned Eric. Five weeks. Or it can be. Yes. Or it can be one week. Or it can be even a day. It all depends. Whatever suits you all. Or whatever suits the project intent. And. What. I will sit back. And learn more about it. Is how to get. How to get. More of this. User data. That we are. You guys are all talking. About. To track the user behavior. And you get all kinds of different data. From. With the help of the machines. How to use that. And make a meaningful result. That you could use then in your design. And maybe also. The other stakeholder. Can use. Technically. Or business-wise. And that's what our team is doing. At Skype. Sort of relevant to. You folks. You know. From an engineering perspective. A lot of us tend to think of design up front. But it's. As you know better than most. It's a continuous process. And so our team. We have a small team at Skype. That's focused on customer feedback. We have. A lot of users that might not be. It's an audio video communications tool. We span multiple platforms. All kinds of different user scenarios. And with lots of users. We get lots of feedback. So one of the things. That struck me. When I came. Was the opportunity to provide data. To you folks. To help. You know. Know where the issues are. And it was great to see. What we do. Is we take the text feedback. That we get across platforms. And Skype. And we run. We have a bunch of data scientists. And I saw early on the Airbnb slide. There was data scientists. To look at methods. To cluster this together. And to look at sentiment analysis. And text mining. To understand what are all these users saying. What are they telling us. What are they talking about. And start to help designers. Eliminate any bottlenecks. That customers are seeing. And that they're telling us about. So. See here. Okay. So I put this slide in there. Thinking yeah. I'll talk a lot about data. And how data can be used to inform design. And pretty much every speaker that's been up here. Mentioned it in some fashion or another. Again Airbnb. Usage patterns. Feedback. All these things to inform the design. And really put the users or customers or people ultimately. At the center of the design. And so as we go forward. And Donna mentioned. You know thinking past. So 2017 sounds like a pretty impressive. Wow. Machines are here. Right. That the autonomous car from Volvo. Is something that. Is pretty cool. Right. And somebody mentioned being freaked out. Yeah. That's very interesting. So when we think about these machines. You know whether it's the. Phone in our pocket. The laptop. You know the watch. They're getting more and more intelligent. And the algorithms that we use. To learn. Are getting better and better. And so you think of how. They've made our lives easier. Friction free. You know. It's really having an impact. And it's speeding up. Right. And there's a Gordon Moore. Who founded Intel. Came up with a. In the 1960s. More what became known as Moore's law. Which says the cost and power of chips. Transistors will double every year. And he later modified it to every two years. And it was probably. You know. Significantly less powerful than the cell phone I have. Right. And so the shrinking and the cost. And so for those of you. People seen the movie her. Okay. Most. But this is. You know it's fiction. For now. Right. But going back. 1842. It was essentially the first computer. It was a big contraption. I should put a picture up. Big contraption that was a calculating machine. And she was. She was very insightful. She said that. She predicted at that time that machines would play music. Right. So you think of. Digital music today. That was true. Right. But she also made some comments that machines would never be able to create. They could always copy. And so. About 100 years later. Alan Turing. Anybody familiar with the Turing test. A couple folks. Pretty many. So basically he proposed a test to. As machines. And he worked on early mainframes. As machines were becoming more prevalent. There was a fear. A concern that they would become more. Powerful than humans. And so he developed this. Would not be able to tell. Say behind a wall. Or on a phone or something. That whether they were talking to a machine or a human. And then that machine would be known as passing the Turing test. And you could argue. There's debates. But it hasn't been done yet. You could probably make a case for some things. But Nick Bostrom. Who's a professor at University of Oxford. In the UK. Wrote this book called Super Intelligence. Of sort of the artificial intelligence experts. This came out earlier this year. Who. And asked them to predict. When machine intelligence would equal human intelligence. And then when. When machines would be more intelligent than humans. And so. The experts. The consensus ranged somewhere between. 15 and say 30, 40 years from now. That we would reach. Human level machine intelligence. And then. Metaphorically like the next day. They'd be more intelligent. But within say realistically. Within 5, 10 years past that. Machines will be more intelligent than humans. We'll pass the Turing test. And so. The thing that I'd like to send people. Thinking about is. Okay so. The importance of human centered design. Right as we come to this machine age. So you think about the work of. Travel agents. Right. Does anybody know a travel agent. That's still around. And so then you think about. Sort of this. As machines become more and more powerful. They start to take over more and more things. And these folks. Have all warned about the. Sort of the risks. Associated with. Not keeping artificial intelligence under human control. So. Bill Gates, Elon Musk, Ray Kurzweil, and Stephen Hawking. And Don and I had the pleasure of meeting Steve Mann over there. Who's the. Sort of the first human cyborg. He's a professor at University of Toronto. And started doing wearables. And things like that in the 1970s at MIT. Really interesting guy. If you want to look him up. But the sort of the challenge here. Is that. You know the skills gap. For employers is growing wider and wider. It's harder and harder to find. Whether it's software engineers, designers. Just talented people to fill the growing. Demand. For talented workers. And so. You know if you. As a company. A choice between. Hey let's write a program. Let's have the computer. Let's have the mobile phone. Let's have the user do these things for us. And so. This was very interesting. I'm not sure you can read. I'll read a few of these off. But these are jobs that are predicted to be replaced by machines. In the next 10, 20 years. But I'll give an easy example. Take the autonomous car. That we hear is coming in just a couple of years. And Mercedes is doing. Autonomous trucks. I'm sure Volvo is looking at that too. Is the same technology. And how many truck drivers there are. In the U.S. And mainland Europe. That's a huge industry for employment. Now if we have successful. Autonomous trucks. What happens to all those jobs? So other jobs here. Like bank teller. We talk to a human. And data entry. Travel agents up there. Mail carrier. Dental technician. Real estate broker. A lot of these things are already shrinking. If not gone completely. And then you think about robots. And as we as humans get more comfortable with robots. A robot babysitter. It sounds kind of appalling today. Right? But 10, 20 years from now. People might be accustomed to that. So I wanted to walk through. And kind of to touch back on Ada Lovelace. To see. You know. Can machines really create something original? And what is sort of. Is there work going on there? So Chef Watson. Is a project from IBM. And what they've done. Is they've done a chemical analysis. Of various ingredients of food. And put them all into a big database. Match them up. And they allow you to create. Interesting dishes. Interesting food. From similar tasting ingredients. So. And I don't have some great examples. But basically it says. Okay. Add flour and sugar and water. And do this in a cake. And they've done the chemical analysis. And say okay. I don't know. I'll pick carrots or something. So you know. So you could argue. Okay. That's not really original. Because it's this big bank of data. But if you didn't know that big bank of data existed. It seems original. Right. And going quickly here. This is an interesting study. So they. From fashion week. In New York in 2014 and 2015. And started to do the matching. To see. You know. What was the trend. What was the style changes. And where did they come from. And some interesting look at. You know. What people are wearing on the top. What they're wearing on the bottom. On their arms. That they took postings from that. Where people posted pictures of clothes that they like. And then it allowed you to put in a photo of yourself. And it would recommend a fashion based on the existing machine learning algorithms from the blogger photos. And then map those by region of the country. And allowed you to kind of self select. So you would fit in. In whatever region you were in. So again. You could. You can't really say it's original. Because it's got this big bank of data. But again. It's getting closer. So the point is. You know. The thing that got me thinking. And the whole design matters. Right. It's like. Is designer on that list of jobs to be replaced. Right. And so then you say. Okay. So you have a student from Yale. Had gathered a bunch of. J.S. Bach pieces. As well as some jazz pieces. And put them all in a big database. Analyzed them. Did a whole bunch of machine learning algorithms. And then created original music. And then played it back to. Not experts. But enthusiasts. And played it along with some other Bach pieces. And asked them to identify which were real. Which were original Bach pieces. And she had. I believe about an 80%. I'll call it success rate. Of people who identified the computer generated music. As being written by Bach. All right. So again. Is it original? Don't know. So the point. Sort of in closing here. Is that like. These machines are going to get more and more intelligent. There's more and more data. Understand the sentiment. And what people are feeling. But it's still going to take. My belief. A human to be the outlier. Because the machines are going to be more and more efficient. More and more focused on. You know. The happy path. Or the sunny day scenario. And making things beautiful. But if you know. Just my favorite example up here. Salvador Dali up at the top. So that's why I studied. There you go. coin while you were reading. Hey, trueils. Put all of these together. To like aOT. Yeah. And the same effects. All right. Now's going back here. like you are the ones between the machine and the human. And so it's really important to be empathetic, to really focus in and zoom in on what is the human experience. How do we have the machine support us instead of, you know, us supporting the machines, which if things have been out of control is a real risk. And so I think, you know, again, I come from the engineering side, but I think it starts with the design and really thinking about the people and how do we unlock human experiences with the assistance of machine intelligence and artificial intelligence, data mining, all the great examples we heard the past couple days of how to use data to improve the user experience. And so I just wanted to hopefully send you off thinking and realizing the importance of keeping the user or the human or the person at the center. And thank you very much. Bless you. Thank you very much. And we did want to say design matters. Oh, yeah. That's good. And I'm glad you ended up saying that we couldn't be replaced. All the designers thanked us. And I'm really anxious there. I was like, no, no, no, no. But then again, any questions about Skype, 1.com, intelligent machines taking over the world? Pretty broad spectrum. So do you have a – I'm just going to start because that's my job. Yeah. So at Microsoft? At Skype? Do you have any examples of where you work with – I'm thinking Skype product because everybody knows that. Don't worry about that. Are you working with intelligent machine – I mean, artificial intelligence in the Skype product? In a sense, we do. We do a lot. As I mentioned, the text analysis for phones. Feedback. Also, we've done a – there's been a large project in conjunction with Microsoft Research on language translation. So the Skype translator does real-to-real, real-time, person-to-person translation between multiple languages. And that's all based on sort of training data and running through machine learning so that it can do the translation. And you may have seen Bing Translator, Google Translator, those types of things. And then building on that. And then building on that to do voice recognition and voice synthesis so that we can get real-time communication. Is that something we're going to see in the product? Yes. Actually, you can download a preview now. Oh, you can? Yes. Since last December. Excellent. I will definitely do that. We've got a very tired audience. Hopefully tired and satisfied. Let's – you know what? It's time for – our program is over now. So just to make – you know, be nice to you, let you go on time. So Ross and Dana will stick around for the next 15 minutes, I hope. And you can pick – you can find them in the crowd. And please don't leave yet. It's not something to say. Thank you, guys. Thank you very much. Thank you. Thank you for your time. I have a present for you. Thank you. And I will just add our contact info is in the slides. So please reach out if you have questions later. Great. Thank you so much. Wow. Thank you. I can't believe it's over. That's too bad. Thank you, everybody. Thank you, Dana, for rounding up the whole day. Now we can just pretty much leave. A special thanks to all the international guests for coming. Thank you so much. We really appreciate it. Spread the word. On your way out, we have the MailChimp competition. Vicki will be waiting out there. She's waving already. She's ready to hand out the winning merchandise. We'll be sending out an email tomorrow with links to the available presentations and also to our survey. And please, UXers, send us your comments, anything especially negative, so that we can do it better next year. We're back in March 2016 on the 3rd and 4th of March. And also, we're doing Design Matters again next September. So please stay tuned. Come on over. According to user needs, we've been told that we need drinks tonight. Unfortunately, we don't have that arranged. They're closing. So next year, we'll listen to you guys. We'll have beers ready for you next year. There's a bar down the street called Talbul. We're going. Yeah. We're going. See you there. Down the street. Yeah. All right. That's good. Thank you so much for joining. Thank you for making this an absolutely fantastic conference. And we hope you had as much fun as we did. See you next year, hopefully. Thank you, guys. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. That's great. Have a good weekend. See you next year. Bye. 1 Thank you.
