This week: measure from space, liveable cities, and privacy is not the issue. 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:
Other stories we bring up:
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Intro: This is The Future, This Week on Sydney Business Insights. I'm Sandra Peter. And I'm Kai Riemer. Every week we get together and look at the news of the week. We discuss technology, the future of business, the weird and the wonderful and things that change the world.
Okay let's start.
Kai: Today on The Future, This Week: measure from space, liveable cities, and privacy is not the issue.
Sandra: I'm Sandra Peter. I'm the Director of Sydney Business Insights.
Kai: I'm Kai Riemer, professor at the Business School and leader of the Digital Disruption Research Group.
Sandra: So Kai what happened in the future this week?
Kai: Not much to be honest. There's been a whole bunch of stories about artificial intelligence. Nothing that we haven't discussed before. There's been a few interesting smaller studies that we're going to discuss but it has been a slow week. We'll have a look at what we can learn from satellite imagery about our cities in particular about obesity in cities. We're going to look at what makes a city liveable and how these liveable cities indices are built. What are they for and what do they actually measure? And finally we're going to go back to one of our old favourites: Facebook, Google platforms, data driven business models and why privacy is no longer the main issue here. But our first story comes from the Smithsonian Magazine and it's titled "What can satellite imagery tell us about obesity in cities?".
Sandra: The article reports on a study by researchers at the University of Washington which used satellite images basically street view images from Google Maps to study a number of cities in the US. Places like L.A. in California or San Antonio, Texas, Seattle and Memphis in Tennessee and what they were trying to do is train neural networks to see if they can discover a relationship between the type of infrastructure that you would find in one of these cities and the rates of obesity.
Kai: So they deliberately picked places with high obesity rates such as Texas and Tennessee and low obesity rates such as California and Washington to see if there's a correlation between certain features of the built environment such as sidewalks, parks, gyms, bus stops, fast food restaurants but also things like pet shops, shopping centres and the like.
Sandra: Turns out the researchers were able to estimate an area's obesity rate extremely well simply by analysing the satellite images that they had, looking for green areas, looking for walkways, shops.
Kai: So it turns out that some of these correlations are pretty obvious. If you live near a park you have more access to walkways you do more walking - duh - and it also means that you are less likely to be obese. What was less obvious is some of the other correlations. For example there was a significant correlation between the number of pet shops in the area and obesity.
Sandra: So does that mean that in order to reduce obesity rates the government should just build pet shops all around the city.
Kai: And that's the problem with these studies. We find this correlation. Sure there's more pet shops in the areas which means people have pets, people with pets walk more. So they are less obese. The question is one of cause and effect right just because we find a feature of the build environment doesn't mean that we can improve that feature and then have less obesity.
Sandra: In these sort of instances, turns out machine learning algorithm neural networks might find certain patterns but there are no better able to tell us how to disentangle things like the socioeconomic status of the people who live in the area from the effects that we are observing.
Kai: Because it turns out that obviously the more affluent areas in cities where people have higher incomes also higher education levels are also the ones with more green spaces, parks and the like. And so it's very hard to disentangle what is actually the driving factor here. It might simply be education which drives income which drives awareness.
Sandra: Or wealth. I'm able to buy healthier foods, have more leisure time to engage in physical activities and so on.
Kai: But there's certainly some areas where this information can be helpful. For example urban sprawl, areas where citizens have to take the car to go to shops and everyday amenities are not inducive to the kind of lifestyle that would get people off the couch and actually have them walk everywhere. Whereas in inner city areas for example where everything is accessible by foot you'll typically also find less obesity. So obesity being in many areas a suburban problem.
Sandra: So this study got us thinking about what are other ways that we have successfully used research from satellite imagery to think differently about topics that we used to take for granted. In this case, the researchers tried to use satellite imagery to be able to say something more about obesity but we've seen other pieces of research where actually what we can gauge from satellite imagery has allowed us to rethink some of the ways in which we measure for instance economic output. In a similar endeavour that used satellite imagery, UBS the multi-national Swiss bank's research arm tried to track economic activity. And they did that not only by looking at what you'd normally expect them to look at - shipping terminals or oil refineries - they did that by looking at parking lots in cities, much in the same way that the University of Washington researchers did in the obesity study. In this case UBS looked at Wal-Mart parking lots as they are seen from space and this might not mean a lot to us but for analysts looking at these pictures they started to estimate how occupied these Wal-Mart parking lots were to try to estimate the company's sales. So if you think of a very crowded parking lot in front of a Wal-Mart that might mean that there are many customers inside which might mean increased sales. And by using this technology, UBS was able to tell the earnings of Wal-Mart well in advance of the official numbers being released and it turns out that they were quite on the money with their estimates. In what was a similar study again trying to use cheap satellites and trying to reveal insights into the activities below, another study aimed to estimate China's factory production output by looking at the number of facilities and the fill level of oil tanks that they had on site. Each of these tanks has an adjustable roof that lowers itself as the product is being consumed so what they were able to tell using satellite images of these oil storage facilities was how much production, how much output these factories were having based on the oil that they were consuming.
Kai: In another study published in Science Magazine in 2016 researchers from Stanford University showed that they can reliably train a machine learning algorithm to predict poverty in developing countries. The issue here is that reliable data on economic output and livelihood and poverty in developing countries is scarce which hampers the creation of policies for development in these areas but also for example in the event of natural disasters prevents the deployment of resources in the best possible way because we know that poorer areas are usually hit the hardest when it comes to natural disasters so what the researchers did is they trained an algorithm on satellite images that were marked up with the economic output in certain areas and were able to explain up to 75 percent of the variation in the local level economic output / outcomes thereby showing that simply by using satellite imagery you can make pretty good predictions as to how developed or how poor certain areas are, even in countries where data is not reliably available which will eventually help those disaster relief or development efforts so pretty exciting ways to actually make some progress in really tricky areas.
Sandra: And speaking of data and predicting how liveable some areas are, this brings us to our second story which comes from the World Economic Forum and talks about the problem with ranking the world's most liveable spaces. All of us have come across these studies in the pages of any big newspaper that ranked the most liveable cities in the world. And here in Australia we always see Sydney and Melbourne somewhere in the top five, top two, top three of these studies, we see them in the pages of The New York Times, we see them in the Economist, we see them on TV and some company or other is always making a list of the best places to live in the world.
Kai: And while there are a number of these studies or indices the one reported in this article is probably the most prominent one from The Economist - The Economist Intelligence Unit's Global Liveability Index, that's a mouthful. Melbourne has been on top for the past six or so years but has just been overtaken by Vienna, Austria's capital city as the most liveable city in the world and we thought okay let's take a closer look at what these indices do and what might be alternatives to measuring liveability.
Sandra: Not that we instinctively don't agree with the fact that Melbourne and Sydney must be among the best places to live in the world. But what are these studies actually measuring and what they are actually telling us.
Kai: Let's take a look at what these indices actually measure.
Sandra: So if we take the latest Economist one that puts Vienna in the number one spot followed closely by Melbourne and Sydney, what are they actually looking at because when I think liveable city I think about the weather, I think about how quickly I can get from one place to the other, how cheap or expensive housing is. But you might think about something completely different - you might be interested in whether there are good schools or not or whether there are bicycle paths or how close shopping is to where you live.
Kai: So it pays to take a closer look at why The Economist actually created this index, what is its purpose and a recent article in The Conversation by colleagues from RMIT University in Melbourne discusses just that. It turns out that The Economist created the index to help corporations decide how much hardship allowance they would need to pay employees who relocate to certain destinations, to certain cities.
Sandra: So hang on does that mean that the index actually measures how good these cities are for expats who come over to live there for a couple of years?
Kai: Yeah that's exactly right. So it doesn't actually take into account what it's like to live in those cities permanently so for the residents or citizens, it's actually a measure for how easy it is for employees to relocate to a city. So the top cities in these indices obviously wouldn't need any hardship allowance but if you are ranking quite poorly in the index then The Economist says you should pay employees a certain allowance because you know it's not really nice to live in places like Port Moresby, Tripoli or Karachi named here specifically in the article. And that means that what is being measured by this index is things that are important to expats, not citizens. For example education is one of those measures but it only takes into account private schools in inner city areas not public schools which are most important to most citizens in a country. It doesn't take into account what it's like to commute in a city so what is the transport from the suburbs to the inner cities. It only takes into account inner city CBD infrastructure...
Sandra:...which is where most expats would live in close proximity to their company offices and with access quite often by private transport to their fairly expensive offices.
Kai: That's right. So if you're in inner city Melbourne obviously you have the tram network which is great, in Sydney it's not quite that good, only placed sixth on the index not second, but you've got Uber, you've got the trains, so getting around in the inner city suburbs and the CBD is fine in all of these places whereas traffic and we all know this both in Melbourne and in Sydney because most people have to travel by car because the train network is pretty sparse, traffic is horrendous and the infrastructure is aching in both cities - that never shows up in these indices and this is why people living in Sydney and Melbourne might ask "really? the most liveable city in the world and I'm spending two hours a day on my commute sitting in traffic, how can that be?" Well the answer is that doesn't even show up in these indices.
Sandra: So then obviously the next question is: Is there a way to actually measure how liveable a city is and what would you include in this measure and what would it tell you about that city?
Kai: So that's a great question but it also raises the question who would do the measurement. And given that this is quite costly, why would you do it? Because in the case of The Economist or Mercer who run a similar index, they actually sell this data to corporations who want to make decisions on where to open an office and to relocate staff. So they actually make money from the detailed data that they collect and we also should say that when we say measurement quite often and the article in The Conversation points this out, these are subjective judgements by expats, people living in those cities who come up with a rating so while they use some objective measures quite often it's just their ratings of the city. So it's by no means something that would hold up to any scientific standard but that's beside the point. So given the creation of any such index costs a lot of money and resources, who would actually have the means to create a global index that would help cities and suburbs to improve what they're doing or to benchmark against each other. So that's a question that remains unanswered. Then the question is of course as you say what would we put into such an index. And here the World Economic Forum article has some ideas.
Sandra: Some ideas indeed. So what the World Economic Forum article proposes is that we use the 17 UN Sustainable Development Goals (the SDGs) that try to look at things like climate change, poverty, hunger, sustainability, gender equality, education and wrap all of these goals up to get a better picture of how well countries are doing. So even though the idea is for this data to be reported at the country level, what the World Economic Forum article proposes is that we might want to identify progress made towards achieving the SDGs, not only at the national level but also at the city level. They give the example of one such city that actually stepped up and started to report on these indicators at the city level and let's remember all of these 17 measures actually include a number of different indicators in each of these measures. So for instance if we're looking at gender equality or the quality of education there are a number of indicators that go into assessing the quality of education in a country but there is one city that actually has done a voluntary review and that is of course New York City. And they've been the first one to formally present a plan and the progress towards these goals and the article points out the fact that this has set off a frenzy of requests to build databases on pretty much everything in the world from really useful things like the volume of traffic and how good traffic is in a city to really weird, out there things like the number of urban deer deaths. That would be probably kangaroo or possum deaths in Australia. Even though if we keep the number of dear deaths Sydney and Melbourne would probably do really well. And at first glance this would seem like a really good idea, we've got all these diverse measures on which we could report how well a city is doing. But on closer inspection...
Kai:...the main problem is that depending on which criteria you select and how you weight them you will come to very different rankings of cities. So one such example is mentioned in The Conversation article. The Economist only measures safety, education, quality of living but never actually goes near any ecological measures such as ecological footprint of a city. And so the article points out that Vienna, sitting in number one spot, and Melbourne have very different ecological footprints. Vienna having about a half that of Melbourne or Sydney which are very wasteful in terms of resources and energy compared to what they have to offer in terms of liveability. So depending on which of those measures we include we might come to very different rankings which means any such ranking is always also political.
Sandra: So indeed if we take the UN Sustainable Development Goals this doesn't become any easier because actually this is infused through all of the measures that are in there. The other issue that this highlights is that indeed all of these measures are not only politically infused but also culturally infused. Most of these measures for how liveable a city is are very much western measures, we put a high value for instance on how economically significant the city is, in most of these rankings there are a lot of western cities that have a big influence on the economic or the financial agenda or the political global agenda. There is a question on whether we should put a higher emphasis for instance on how nice the climate is which from an Australian perspective would put us right there at the top. Or is it about how beautiful the cities are. Should we put a high emphasis on cities that have very nice architecture, that have a lot of historical buildings and a lot of cultural values? Is that what would make a city most liveable? Or is it indeed the ecological footprint of the city?
Kai: Is it water security? Because while Australia has nice weather and lots of sunshine on the downside we have very little rain and often droughts and long term water security might be an issue.
Sandra: Or is it something like resilience for instance, how quickly we would be able to bounce back in the case of a natural disaster or in case of an epidemic for instance. How resilient are the cities and how easy would it be to bring it back to a level of liveability that we can all accept?
Kai: And I think that's all we want to say on this story which brings us to our last one, from the New York Times. That's actually a bit of an update on an ongoing issue that we've been discussing on the podcast. The article is titled "Just don't call it privacy" and it comes on the back of more congressional hearings with the likes of Google, Twitter, and Facebook. This time in front of the Senate Commerce Committee in the US. The author of the article makes the point that when it comes to these platform companies we shouldn't refer to the issue at hand as one of privacy or merely privacy. The author makes the point that privacy being 'what data do I have to give up to actually use the service'.
Sandra: And that's indeed the point. So the conversation we had last week was from the point of view of the consumer and the access that these companies have to our data and privacy is indeed one of the defining issues of our time and one that consumers need to be extremely aware of and one that will continue to remain an issue of debate. But raising only the issue of privacy when it comes to companies like Facebook and Google misses much of the point because the point is not only what data they can get from us but the point at hand, and this is what the article highlights, is that focusing just on the privacy isn't enough.
Kai: So the article says what is at stake here isn't privacy, the right not to be observed, it's how companies can use our data to invisibly shunt us in directions that may benefit them more than us. She calls it the surveillance economy and she points out that in order to use any of these platforms we take it for granted that we are giving up a lot of our information after all Facebook is all about sharing information with other people so we naturally give up a lot of information just to be able to use the platform. When we use Google for example we give up information on what we search for. So quite naturally they will learn a lot about us, the matter at hand then is the extent to which they can exploit that data and what they can do with the data and what they tell us in specific terms about what they do with our data.
Sandra: So in simple terms while publicly we have started to address the amount of data that these companies collect and that is indeed a very very important issue, less discussed has been the aspect of the control that a company like Facebook has on how they exploit that data. For instance the article gives the example of Facebook's advertising platform deciding to show certain job ads only to men or only to people between the ages of 25 and 36 which anywhere else would be considered a type of discrimination, yet this is the way the companies monetise their data. So looking only at things like privacy policies tells us very little about how the companies are influencing consumer decision making and how they're exploiting the data as part of their business models.
Kai: So Natasha Singer the author is concerned that much of the hearings in the Senate Commerce Committee is focused on scrutinising the privacy policies of these companies rather than their business practices. And she points out that there's a big gap between what she calls the innocuous ways in which companies explain their data practices to consumers and the details that on the other hand they devulge about their targeting techniques to advertisers. So while they make it sound as if they do very innocent things in their privacy policies when they sell their services to their advertisers they point out in quite specific terms the frankly at times scary levels of detail at which they can target individual customers and therefore offer advertisers to sell ads and therefore drive their sales in ways that are completely nonobvious to the consumers.
Sandra: So what it comes down to is not really the privacy policies that these companies have or their data practices which are at the focus of these hearings but rather their ability to either infer or make decisions about things like our financial status or our emotional status. The article quotes Assistant Professor of Computer Science and Public Affairs at Princeton called Jonathan Mayer who points out that the conversation in Washington at the moment and in a lot of other places around the world is around policy and law. So those involved in the conversations are lawyers and policy experts rather than the engineers who understand the mechanics of these algorithms and who would be involved in conversations around a different set of issues that go at the heart of the business models that these companies are based on.
Kai: So the way in which we interpret this is that companies like Google and certainly Facebook have not really changed the way in which they go about business. They are pressing on with creating more ways in which they can monetise their data all the while they send their lawyers and policy experts to these hearings obfuscating and frankly bullshitting the Senate hearing.
Sandra: About it is here that we should mention that there is actually a counter trend and people are starting to take a stand against this. Earlier this year the second WhatsApp co-founder left Facebook and incidentally also left behind eight hundred and fifty million dollars because he disagreed with the way in which Facebook wanted to monetise the data of WhatsApp users.
Kai: And in news from just this week, Instagram co-founders Kevin Systrom and Mike Krieger have left the company. It is still unclear what has caused the sudden departure but it is presumed that they are taking a stand over Facebook increasingly interfering with Instagram's business - just to remember the founders were assured when Facebook took over Instagram that they would remain autonomous in their decisions about the development of the platform - it turns out though that it is increasingly Mark Zuckerberg and Facebook who wants to make decisions as to how Facebook and Instagram are interlinked and how Instagram is being monetised by Facebook. The problem here though is that while these co-founders take a public stand they are also quitting the companies that they leave behind in the Facebook empire and it is presumed that the change at least in Instagram will lead to Facebook integrating its advertiser network much more closely with the Instagram platform thereby driving advertising growth by monetising Instagram data in much the same way as they already do in Facebook itself.
Sandra: And incidentally this is what was at the heart of the WhatsApp fallout as well where the founders of WhatsApp were militantly pro-privacy and they felt that the encryption and the privacy promise that was at the heart of WhatsApp was at stake with Facebook's determination to pursue ways of making money out of WhatsApp either by showing targeted ads in WhatsApp features or by finding other ways to up-sell people who are using WhatsApp.
And whilst companies like Facebook don't seem yet to be taking a fundamental stance on the way their businesses are built...
Kai: And we want to point out that given the business model they don't have much choice in growing their business and therefore satisfying their shareholders than pressing on with monetising the platforms that they have.
Sandra: People like WhatsApps' co-founder are backing other companies that do have security or privacy at their heart. For instance 50 million dollars went to a small messaging app developed by a security researcher and allowed it to turn into a foundation so that it could continue to focus on privacy and encryption and have no obligation to transform it into an ad platform.
Kai: And while The Verge calls it the end of Instagram as we know it, it is early days for the Instagram co-founders but it is presumed that they too will go and create a new venture. Maybe also putting money where their mouth is and creating something that embodies different ideas to what Facebook obviously has in mind for Instagram.
Sandra: And that I think is all we have time for today.
Kai: Thanks for listening.
Sandra: Thanks for listening.
Outro: This was The Future, This Week. Made awesome by the Sydney Business Insights team and members of the Digital Disruption Research Group. And every week right here with us our sound editor Megan Wedge who makes us sound good and keeps us honest. Our theme music is composed and played live from a set of garden hoses by Linsey Pollak.
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