This week: big design, keeping up with blockchain, how computers change us and goodbye Walt. Sandra Peter (Sydney Business Insights) and Kai Riemer (Digital Disruption Research Group) meet once a week to put their own spin on news that is impacting the future of business in The Future, This Week.

The stories this week

Want to change the world with design? Work for huge companies

Even academics can’t keep pace with blockchain change

How machine logic infects our tastes

The disappearing computer

Other stories we bring up

Cooking with chef Watson, I.B.M.’s artificial-intelligence app

DARPA hired a jazz musician to jam with their artificially intelligent software

Mossberg: The Disappearing Computer

Yale/UC study finds extensive Facebook usage decreases health & happiness

Does Facebook make us unhappy and unhealthy?

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Dr Sandra Peter is the Director of Sydney Executive Plus at the University of Sydney Business School. Her research and practice focuses on engaging with the future in productive ways, and the impact of emerging technologies on business and society.

Kai Riemer is Professor of Information Technology and Organisation, and Director of Sydney Executive Plus at the University of Sydney Business School. Kai's research interest is in Disruptive Technologies, Enterprise Social Media, Virtual Work, Collaborative Technologies and the Philosophy of Technology.

Introduction: The Future, This Week. Sydney Business Insights. Do we introduce ourselves? I'm Sandra Peter, I'm Kai Riemer. Once a week we're going to get together and talk about the business news of the week. There's a whole lot I can talk about. OK, let's do this.

Sandra: Today in The Future, This week: big design keeping up with blockchain, how computers change us, and goodbye Walt. 

Sandra: I'm Sandra Peter. I'm the Director of Sydney Business Insights. 

Kai: I'm Kai Riemer. I'm Professor here at the Business School, I'm also the leader of the Digital Disruption Research Group. 

Sandra: So Kai, what happened in the future this week?

Kai: Our first story's from Fortune magazine. It's about design and it's titled: "Want to change the world with design, work for huge companies" and it's a short article and it makes an interesting argument about design in general and that we often think of design as being something that is done by people at the fringes, in niche companies. But the main argument is that design is for people and if you want to reach many people you have to work for large companies that have the reach and the production capacity to actually put your design in front of many people. 

Sandra: And we've got a short clip from Jony Ive, I think. 

Audio Clip: One of the things that you knew you'd get a sense of is the degree of care. How much did this group of people care to make this and make it right. And they didn't do it for themselves. It's in service to the people that are going to use or buy the product. And I think there's something... the humanity of.. I think is extraordinary.

Kai: So what we've just heard is that even in large companies like Apple, design it's really centering around what people need how people live their lives and how we touch people's lives. And so the article makes the argument that there's been a tension always between designers who think that mass production is really counter to the idea of designing something bespoke something unique something beautiful. And the article makes the point that really if we think about design in terms of touching people's lives and making people's lives better and we think about design from the people point of view then there's no point designing something that will only benefit very few people but rather that design should be done in large companies. 

Sandra: So indeed the article brings together the Senior Curator for Design at MOMA in New York but also Chief Design Officer at the company like Pepsi to have a conversation about this tension between academic design and corporate design. And if you look at the things that we're surrounded with right here, things like our macbooks or our iPhones or any of the furniture that we have around us, who really is in the position to put these things before us. So if you want to be designing for technology there are actually very few of these companies that you can join. Interestingly if you want to design furniture that impacts you probably the company you would want to work for Ikea. If you look at something like the iconic BILLY and there have been shitloads of BILLYs sold over time we've got... millions and millions... something like 40 million over the last 20 or 30 years. So these are huge numbers. And indeed the design for that has been the design for many people based on what people need. But also what is accessible. And lately we've seen quite a big shift in niche designers moving to large organisations so they can impact many people. A few years ago, clothes designer Isaac Mizrahi designer of very very expensive garments said that he was designing for the American woman and he realised that it's actually not the American woman he was designing for. It was very few American women who could afford his product so he started doing the line for Target dressing the American woman actually means designing for a company like Target. 

Kai: This is the idea of the Volkswagen right. The car for the masses not just the car for the few. And in many ways the German Volkswagen design has become emblematic of this kind of iconic design that impacts the life of ordinary people and has popularised a car in Germany after the Second World War. So this tension between design as a craft, as an artisanal activity and design for the masses which comes with the commercialisation is what this article is about. And the idea here is to, and this is said in the article, is to start respect a little bit more design for the masses and not see it as antithesis, the tension between commercialisation and design but rather see the two go together especially when we make the argument that design is for the people. 

Sandra: This conversation about impact and design kind of brings us back to the frightful five. So if we look at the design of the iPhone or the MacBook or if we indeed think of the conversation we had on our last podcast about artificial intelligence and the way we design beyond the interface. 

Kai: So we often think of these large companies in quite negative terms as the frightful five because they're in a position of power where they can utilise the data to manipulate the masses and all the kind of things that come with this market position. But at the same time they're also a platform for doing good in terms of design. They're also a platform for doing research maybe. There's another article this week in 9 to 5 mag about a study carried out by Yale University and University of California in to the relationship between Facebook use and mental health and happiness. And we won't comment on the actual study it just shows the problems that researchers have in accessing the data and the lengths to which they had to go in putting a panel together and following people and studying their Facebook behaviour. Imagine what Facebook could do with the data they have. So I think looking at this market power and the central position that those five have not only in design but also in research, wouldn't it be great if that data would be available for universities to utilise or if those companies would actually utilise the data to research themselves and publish from it. And there have been some attempts of doing it and Microsoft whose been in this game for quite a while are actually a leading example of combining commercial activity with research. So they're really good but they are just one of those five. We know that Google is doing a lot of research and they are publishing a little bit of it but it really should be an example for how the position that these five have could extend beyond just the commercial activity to give something back in terms of the research that they can do with the data they have access to. 

Sandra: Is this a question of also us as researchers working with the frightful five because in the study that you mentioned that The Wall Street Journal also reports on it they managed to track Facebook habits of only 5000 people. And for us as researchers access to five thousand people... that's not bad...that that's not bad at all but if you think of the data that Facebook has five thousand people is... 

Kai: Minuscule right, they could do this with millions. 

Sandra: It's a rounding up error. So tracking these people for two years checking on their health and happiness levels. And let's remember they agreed to participate via a Gallup Poll and looking at their health and their social lives and Facebook use, what they like, what they don't like, how they're feeling, whether they're sad or lonely or extremely happy. For researchers to have access to that, will there be a similar headline in a few years: "want to change the world with research, work for huge companies" and this goes back to our discussion about artificial intelligence and the money that is being invested in or in these organisations are not only as a matter of who's investing and doing this research but also have access to the data that comes out of it. 

Kai: Absolutely. And this brings us straight to our second story which is about the blockchain. The technology that underpins bitcoin. Now a quick shout out...a quick shout out... for Gianluca Miscione from UCD in Dublin who send us this article so thank you for that. 

Sandra: Thank you so much.

Kai: It's an article about blockchain and bitcoin in a way and we're not going to discuss bitcoin per say but we've already decided we are going to run a special in a few weeks time on bitcoin and we'll be in contact with Gianluca for this. 

Sandra: So we can address this properly and give it its proper attention. So we thought this article had a really interesting idea that we just needed to cover today. So the article is called "Even academics can't keep pace with block chain change". 

Kai: So the argument that it makes is that technology is changing fast and block change is an example of this and it's incredibly hard for academics to keep pace with the technology not necessarily in terms of their research but in the way in which those changes translate into the classroom and in the way in which we can actually keep our students up to date with what is happening out there.

Sandra: The article reports on a workshop held at CoinDesk's Consensus 2017 conference a few days ago and the panel featured people from MIT, from Duke University, from the University of Nicosia in Cyprus and tried to look at how universities develop their young people with the requisite skills to participate in something like blockchain development. 

Kai: Yes and it discussed this from different angles. And the corporate angle comes back in because one of the ways in which universities in the past have tried to keep a pace with the changes is by partnering with large corporations and companies in Silicon Valley with mixed results really. There's a famous case by Carnegie Mellon who created a centre for artificial intelligence. They partnered with Uber, and Uber then just poached the whole team of 40 scientists into their company. 

Sandra: The article also hints at the fact that we've been down this road before, right. If you think of the early 90s and the dot com boom and companies starting to take up huge chunks of academia that were joining the ranks in Silicon Valley and across the world were joining companies to develop what was the next big thing.

Kai: Absolutely. When I studied Information Systems in the late 90s people left right and centre were dropping out of their studies to join start-ups at the time. 

Sandra: Exactly. But this goes back to the conversation we had with the previous article and the previous week of these large organisations today. For some people actually this is not necessarily being a choice of this is a very attractive domain but rather a need to join it to have access to either the technology or the opportunity to develop these things. So maybe a more nuanced and a more speedy development this time around but still not something that we've never seen before. The article also raises another very important point, I think, if we look at the industry that we're in which is the fact that there is a real concern around the rapid pace of change when things like blockchain and the impact they have on academics wanting to teach in that space. 

Kai: So in my discipline we're always faced with the dilemma that universities make us decide on what we're going to teach months, and sometimes years, in advance but technology doesn't stand still. So you're constantly updating your content, you constantly have to find ways to stay current and use recent examples and be on top of the conversation that happens in the media with technology so prevalent and front and centre in our society. But at the same time identifying the kind of things that are lasting principles that underpin technology that go beyond the current type technology. So I think the equation that we have to solve as academics is to teach the underpinning principles. So take blockchain for example. Blockchain is an exciting technology but we don't know whether it's as exciting five years down the track. But blockchain is underpinned by certain principles, it's underpinned by things like network effects, critical mass and diffusion of technology, technical principles such as cryptography, mathematical principles of hashing. So all of these things are computer scientists and information systems scholars would teach their students. So it's then a matter of bringing these things together using blockchain as an example. And then in five years time maybe use the examples at the time but still teaching those principles. So it's really a trade-off between staying current and creating a curriculum that doesn't age. 

Sandra: So I want to jump in there to say that this is not just about information systems, so I teach a unit called The Future of Business which has some technology in it but it's not around technology and the same sort of principles would apply to what I teach. How do you balance the need to have some underlying principles, mindset skill sets that you teach people but then also bringing it into the current day. If you think about what understanding you would need to have to consider what happens in the car industry these days and in the automotive industry, the disciplines that you have to bring together the competition between industries that you needed to consider the dynamics of who is involved in developing the interface collecting the data, privacy issues, security issues, ethics issues funding issues, infrastructure issues and so on are much more complex today and we need to reconsider what fundamental principles do we need to bring into the conversation. So my first point really was around the fact that this is not just around information systems but the around all other disciplines and with technology. People expect that you are current, they expect you to look at blockchain but with smaller incremental things like design thinking I think there's actually a real danger of not staying current. So design thinking is another one of those things that academics need to keep up with. There is limited research into it especially in certain disciplines but we still need to teach it to our students which we do but we teach it in certain courses and the mindset that design thinking or agile brings to the table is quite different to the mindset that gets instilled in students in five or six other courses that they do that are quite traditional. So we need to consider those tensions when we update the curriculum. This is not about what one person does in the class but this is about what we do as an institution.

Kai: And this is not to say that we should pander to certain fashions right. There's been enough examples of degree programs being launched on e-commerce that five years later were completely outdated, right, so this is not about jumping on the hype bandwagon but about finding a balance between lasting principles and staying current to the current conversation which is what makes it so difficult. So university curricula can't just be evergreen content. They have to have the principles that are still relevant and provide students with skills that they can use 10 years from now but also tie in with the kind of topics that students are faced with once they leave university and enter the market straight away. So that's what we're talking about. 

Sandra: And entering into the market straight away is also what we have a responsibility towards. So as educators we also help create shape build that future that we're discussing. So what happens with blockchain, with autonomous vehicles all of these things are a product of the people who exit our institutions. So with rapid change there is also an opportunity to impact these things as they develop. And speaking of evergreen content yes I agree it is so much easier to develop evergreen content. Imagine if we did a podcast that you could just listen to for the next 10 years. And yet the really difficult thing is something like the future of business we do one every week that is current. 

Kai: Yeah so the trade-off again is do you keep on top of the current conversation make something that is interesting and relevant now or do something that has mild relevance at any time but doesnt really tie in with any interests of the audience that you;re trying to address at any moment in time. So my money is on staying current but talking in terms of the lasting principles, incidentally what we're trying to do on this podcast right.

Sandra: Incidentally what we do on this podcast.

Kai: So the next story is one of those.

Sandra: Comes from real life magazine it's called: The domino effect, how machine logic impacts our tastes.

Kai: At the surface it's about artificial intelligence and algorithms in food ordering. But there is a deeper truth to this right. 

Sandra: The story is trying to ask the question if it's really us shaping the algorithms or at the same time are the algorithms also shaping us.

Kai: It uses as an example the ordering of pizza hence Domino's and makes the argument that the more we're relying on apps computers online ordering of food in this instance, the more we're actually restricting ourselves to ordering the kind of food that is well suited for digital abstraction, for algorithmic ordering and pizza is a great example because the algorithm for making pizza is pretty straightforward. You have a base you've got certain toppings. All of this can be put into an algorithm quite easily and if you look at other food groups that are available for take out and ordering they fall into that same category. Burritos, salads they're all easy to configure from a set of ingredients that you can feed into an algorithm. So really the argument that the article makes is that the more we do this for convenience purposes the more our tastes are shaped to comply with what algorithms can do. The more we're actually ordering food that is algorithmically prepared and the more we restrict ourselves to the things that machines can do. 

Sandra: So the question the article asks is are computers shaping us? And interestingly there's another example in there about how Spotify's playlists can flatten the context in which the song was creating so you no longer have the artist's context or their culture or the intention they had when they compose the song or maybe even the album that gives you all the other sounds that came with it or the cues that it would give you or the feelings that would give you. Rather there is a preset mood - this is happy, this is barbecue, this is upbeat or this is lounge music. So these categories get imposed on the listener which no longer makes their own sense out of it but rather draws it from the application itself. 

Kai: So a limited set of so-called moods are there to describe any kind of situation that we might find ourselves in and the argument is that the more we do this we come to think of our own condition of our own life in terms of those categories. And the article says that human experience is delimited incrementally by the limitations of our machines so we absorb this vocabulary we absorb these categories and we come to think of ourselves and our needs and desires in terms of those categories at the expense of a more holistic fuller experience of life.

Sandra: To be fair we've also tried to get that more fuller experience of life. So DARPA hired a jazz musician to help an artificial intelligence system improvise and jazz musician and computer scientist Kelland Thomas tried to teach the computer how to improvise jazz because he saw this as the pinnacle of human and mental achievement. So the idea would be for this computer to on the fly create melodies that are goal oriented and feed on the supposedly emotions of the other musicians playing. Similarly IBM actually tried to feed Watson their famous Watson computer the entire bon appetit archive so that Watson would now create a recipe out of any and all ingredients in one's pantry and a journalist for The New Yorker mentioned that with Watson's help he managed to cook some eggplant fritters that made use of every sad drinking root in his refrigerator. But he didn't try it again. He gave up. 

Kai: So what we learned from this is that computers are not like us. They do not have the same kind of cognition, we touched on this before. But the argument in the article is interestingly that maybe they don't have to because they create us in their image we become more like machines in our thinking. And sometimes for good reason because it's convenient to just order via these apps it takes our complexity from part of our life where we might not want to expend our intellectual energy. And of course you can still engage in cooking and whipping up great dishes that do not comply to the algorithmic nature of computers. But for many people in many situations they quite happily subscribe to this way of thinking because it's a part of their life where they happily just go with the flow in with whatever those apps have in stock for them and maybe they expend their reflective energy in other parts of their life.

Sandra: So maybe it's not all bad maybe having some things that are more streamlined or simplified with the complexity that we have around us and maybe becoming a bit more like machines is not necessarily a bad thing but the underlying principle we were trying to get to is not whether this is good or bad and indeed even though we instinctively say no no we should resist this maybe is something that's not bad for us. So it's not about being good or bad but it's about the need to be aware of it, to recognise the influence that these apps things like Spotify or make your own burger at McDonald's or Pizza Hut. 

Kai: Yeah. I think the awareness of this is important and we've talked about this previously. It's what makes us cyborg the way in which we think and act through our technologies and come to see the world in terms of our technologies. And this is by no means a new phenomenon it happens in other parts of life. Take Google maps for example and GPSs we come to understand our environments in terms of the map and the discussion between the map and the territory is really an old one in the philosophy, in the philosophy of science, geography but this is very much at play here. The idea that we come to see the world through those categories that we initially impose on the world it's a phenomenon that we need to be aware of because it shapes our perception that shapes our lives. Some would say it instills certain biases in how we see the world. And so while we might happily succumb to it and go with the flow, I think stepping back and recognising that the way in which technology configures us also limits our perception of the world is something that is very important.

Sandra: So recognising being aware of the role of technology. Which brings us to our last and very sad story for this week and it has to do with Walt's goodbye. 

Kai: Yes Walt Mossberg a long term commentator for The Wall Street Journal and later for blogs such as The Verge and Recode, host of the All Things Digital Conference is retiring at the age of 70. So well done Walt. And fair enough to retire at this age but a voice that has changed the discussion around technology and the future of business for quite awhile. And so this week he has published his last article. 

Sandra: It's called the "Disappearing computer". It talks about the fact that technology was once in our way but soon it will be invisible. 

Audio Clip: We have this...the big five tech companies the oligopoly which you guys talked about a lot. We have companies whose names we don't even know. And all these people are working on a wide variety of things that I think will come together to once again upend everything and I'm talking about artificial intelligence, machine learning, augmented reality, virtual reality, transmitting power through the air. All kinds of bio and health things.

Kai: So he reflects on the fact that he has talked about technology all his life. And just as he is retiring, technology is disappearing as well. That's not to say that it's becoming unimportant but that instead of us dealing with the computer as this object that we have to wrestle with, I.T becomes what he refers to as ambient computing where technology recedes into the background. You just fade into... Yes you have Alexa sitting in the corner. You can just talk to her and engage with computing in much more natural ways so the future that he sees for I.T. is that it will be just a part of your environment and you can engage with it in much more natural ways than we previously would when dealing with screens and the typical user interfaces that he grew up with.

Sandra: And that applies to things like Alexa or computers or smartphones. But equally to things in the medical industry. So we discussed last week, Apple's secret project to have non-invasive sensors so no more medical tests for instance so ambient computing in all walks of life and he sees a number of building blocks that are coming together quite slowly but they are coming together to build this ambient computing and he mentions artificial intelligence, machine learning, augmented and virtual reality, robotics, self driving cars, wearables.... homes, drones all this kind of technology. So the article provides a nice overview of the long way we have come with technology and the situation we find ourselves in at the moment. 

Sandra: Which is a bit of a lull before the next big thing. So whilst we do have a lot of the building blocks that we mentioned before we haven't had really big dramatic changes since we've had the iPad and the iPhone and some of the technologies that really are almost 10 years into the making now. This has been echoed by Google's conference last week where we haven't seen any ground changing advancement but we've seen things like Tensorflow, we've seen hardware developments, we've seen an increased focus in AI on cameras and other things. All of them building blocks to the next big thing. 

Kai: So as Walt is embarking on his well-deserved retirement the rest of us are hanging in here waiting for the next tech revolution to happen. 

Sandra: So Walt thank you for writing and everybody else. Thank you for listening. 

Kai: That's all we have time for. Thank you very much.

Outro: This is The Future, This Week brought to you by Sydney Business Insights and the Digital Disruption Research Group. You can subscribe to this podcast on SoundCloud, itunes or wherever you get your podcasts. You can follow us online on Twitter and on Flipboard. If you have any news you want to discuss please send them to

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