1. Google Glass is an outgrowth of the mobile phone and operates within the frame of technology, that is, prosthesis. It extends knowledge, shrinks distances and time. Each new technology takes a while to arrive at a point where it’s actually useful, but from the start the language is one of function; the aesthetic functional.
2. Fashion, by contrast, starts from a point of excess. We don’t need fashion, that’s the whole point. It’s pleasure, it’s playfulness, it’s pointless but rather fun. Its very distance from function is how it sets itself apart as fashion, not just clothes – unwalkable shoes, unwashable leather t-shirts, embellished skirts too ornate ever to sit down in.
3. Where fashion is functional it is, I think, no longer fashion.
(Christian Louboutin: “I HATE the whole concept of comfort.”)
Function – or the ideology of functionalism, at least – focuses on the material properties of things. Yet fashion is utterly symbolic: the garment only matters as a set of aesthetic, historic or cultural references, as meaning, as a fantasy, a gesture. Even worn on the body it’s about the imaginary of who I could be today.
3a. Spectacles as a category are too functional – they can be design statements, absolutely, but no-one treats them frivolously enough for them to be fashion. Sunglasses, on the other hand…
4. Fashion engaged with technology in the late 60s, with sci-fi Paco Rabanne futurism and clothes made out of wonderful new synthetics as costumes for a future life on the moon (or the Barbarella filmset). It came back to technology again some point in the late-ish 90s, through sportswear and trousers with a lot of complicated pockets that made rustling noises as you walked. [I don't understand this moment so well.]
4a. Fashion is very engaged with technology now, but at one degree of remove. There’s a lot of technology involved in materials development, but what these materials mean is a matter of difference, or discernment, or a designer being able to create a particular aesthetic – they aren’t interesting for the technology per se. Social media and the internet are revolutionising fashion marketing, fashion distribution, image research, visual stimulus and fashion design – but no-one is making dresses about this directly. (That would be too crude.) Fashion’s energy is more abstract: the pace of change.
5. Technology can be a style marker – the Macbook Pro – and can be aestheticised as street style: I’m thinking Japanese schoolgirl mobile phone accessories. Style as opposed to fashion – style is broader, it’s design, it’s taste, it’s a kind of social communication with the visual materials you’ve got. Whereas fashion is despotic, it speaks only of and to itself.
Ten years down the line when there are 500 different styles of face-mounted display screen and its varied forms aren’t trying to claim any relationship to function – then Google Glass may have a chance to be something about fashion. Or when the technology’s reverse-mounted into vintage sunglass frames. Or maybe fashion is parasitic on other sets of referents: maybe Google Glass will only be able to be fashion when to wear a pair is to be making a visual reference to sci-fi movies of the 1980s, or Taiwanese street style blogs, or a glimmer of a 2014 revival in the pre-fall collections of 2023 — that is, when wearing a pair of Google Glasses ceases to be mostly about “Oh my god I’m wearing a pair of Google Glasses”.
But now(ish), when to wear a pair is to proclaim that “I’m really into being a new adopter of technology”, or “I would like to think I am living in the future” – currently these statements cannot be parsed within the language of fashion, they are irrelevant to it. Google Glass maybe the future of interactive communications, but fashion simply shrugs.
In the last year we’ve done several research projects on mobile money at FACE, as excitement around the possibilities of “mobile wallet” develops. SXSWi was a chance to hear from leading players in the industry – American Express, PayPal, Intuit and more – on where this technology is going.
What is mobile money?
It’s important to think about the category as “mobile money” rather than simply “mobile payment” or “mobile wallet”. What’s at stake is much bigger than just transfering your credit card to your phone, or simply replicating the functions of a wallet (payment, loyalty cards & receipts) on a mobile device. The technologies available – smartphones, geolocation, the development of 4G and widespread wifi, and of course NFC – mean that what’s possible is in fact much greater: re-imagining the whole human-money interface.
What’s this mean? It’s about looking at every way in which we interact with money, and thinking about the transformations in user experience that are possible if we make it mobile. The transactions up for grabs are many and varied:
- payment in a shop (of course)
- paying a friend back for the taxi ride last night
- checking to see if your credit card payment has gone out
- transferring money immediately before making a big purchase to ensure your account doesn’t go overdrawn
- adding up your receipts to see how much you’ve spent on eating out this month
- calculating whether you’ll be able to get a mortgage
- buying a flight (or just a coffee) with reward points – mobile money encompasses stored value, not just legal currencies
- getting a discount email like Groupon and redeeming that online
- searching for the cheapest iPad retailer online
- or searching for a local restaurant offering a discount 2-for-1 deal
- …and much, much more.
Making it mobile doesn’t simply mean “available on my mobile phone screen”. The mobile phone is a smart, location-aware computing device, carried almost always within a metre of our bodies, which is always connected to the internet and keeps us always connected to the people we know. Taking full advantage of these properties is what makes mobile money fundamentally transformative. The word “revolutionary” is overused in business, but making money truly mobile is a much bigger deal than the rise of credit cards in the 1960s, the last biggest step-change in payment methods.
There are however some substantial challenges in rolling out mobile money to its full potential. Here are five:
1. Money is a difficult sector to innovate in
Regulation is a big hindrance on start-ups in the money space: there is both legal incumbrance and a cultural resistance (aka trust) to companies taking risks, trying something new – and perhaps not succeeding. The big incumbents are also an obstacle – banks own the central customer account (current/checking accounts), and Visa, Mastercard & Amex control payments.
Building new back-end processing systems is very difficult, and even the big over-the-top players (PayPal, Google Wallet) are essentially innovating on top of existing card payments infrastructure. Dwolla – a New York peer-to-peer (P2P) money startup – is worth a note here, for one that isn’t.
2. What’s happening with NFC?
NFC stands for near-field communications. It’s a type of radio communications – like wifi or Bluetooth at a different frequency – that allows for short-range (10cm) communication between devices and tagged objects, other devices, and merchant terminals. It is ultimately the key way contactless payment will be delivered – although it’s worth remembering that mobile money means a lot more than just in-store payment.
Unfortunately NFC uptake is moving extremely slowly. So far there are only a handful of NFC-enabled handsets in the UK, and many of them are unappealing low-spec phones. The big player is of course the Apple iPhone, and so far there’s no news as to when or how NFC will be implemented on this device.
Without a standardised technology, merchants are naturally unwilling to invest in NFC payment terminals so these remain in a few chain stores only – MacDonalds since 2003; Pret A Manger, and so on. We’re 5+ years away yet from “leave your cash & card at home”.
3. UX benefits of mobile payment in-store
One eye-opener for me about our US trip was just how annoying magnetic-stripe payment really is. US banks haven’t been able to agree on a Chip & PIN standard (as in Europe). As such payment requires the merchant taking the card away (a security risk) and two stages of receipts. NFC payment would clearly be much quicker than this, providing a clear driver for consumer uptake. However, it’s got minimal speed and thus user experience benefit in Europe over the faster Chip & PIN.
Many commentators rate the chances of the over-the-top tech players (mainly Google, Apple, Paypal) as ahead of the banks. Despite some bank mobile apps getting rave user reviews (RBS and Natwest’s mobile banking apps) and a strong move from Barclays Pingit on peer-to-peer transfers, there’s a suspicion that banks are likely to stick to “mobilifying” what they already do, rather than really innovating and reinventing the category. That transformative capacity – and also slick UX design – would seem to be more the property of the tech companies.
But PayPal has a trust problem: we see consistent and frequent stories of how it freezes people’s accounts for months without explanation or recourse. That’s infuriating when it’s your tool for P2P and small-merchant payments – it’s completely untenable if they’re operating your current account. There’s also increasing consumer suspicion of just how much Google knows about us – so giving them access to our finances may be a step too far.
5. Who’s actually thinking big enough?
This was the core insight from a fantastic solo SXSW presentation by Omar Green, Director of Strategic Mobile Initiatives at Intuit, the payment technology firm. He talked about “creating a mobile wallet worth having”, and said he thought the company who would “win” mobile money would be the one offering every transaction listed above and more.
As suggested above, the risk is that too many of the mobile money launches we can see on the horizon are thinking too small. Credit cards on your phone and no additional functionality – so what’s in it for me the user? A couple of dozen big-brand partners rather than available everywhere – so why use? There will certainly be some early adopters who’ll take-up simply to be first and look ahead, but they’re a minority. Strategically banks, MNOs and tech firms need to recognise that these standalone offers must only be stepping stones to something much bigger if they’re going to get any real traction. (Barclaycard have had an NFC credit card since 2003. No-one cares.)
Omar Green had a vision of what mobile money could be that I’ve not seen from anywhere else in the industry. The goal is a seamless money experience addressing our fundamental financial and emotional needs – balancing the books, saving for the future, feeling in control and feeling like we’ve spent our money wisely.
Question is, how seriously will the various mobile payment and wallet apps launching this year will really address these?
Published in design/architecture magazine ICON, issue 106 on mobile phones:
This year the number of mobile phones will exceed the 7 billion humans on the planet. For this issue we asked novelists, academics, experts and designers to reflect on this communication revolution, in a 22-page special on how cell phones have changed the ways we behave, connect to and navigate the world. And to make their own predictions about how mobile phone technology will look in the future …
Your mobile phone leaks. Behind the user interface, out of immediate view, it’s sharing a lot more data than many people realise.
Take location. In exchange for offering Google Maps as a free service, Google extracts the price of knowing where your phone is at all times, even when the app isn’t running. Your home and work addresses are easy to identify (your habitual locations at 3am and 10am respectively). These can be cross-referenced against MOSAIC (market research company Experian’s consumer classification) or Zoopla house price records to transform location into income and demographic data, allowing users to be sold as micro-targeted ‘market segments’ of high value to advertisers.
Mobile web surfing habits provide another stream of data. Mobile operators use deep packet inspection and redirect mobile web traffic through their own servers to manage network performance, but this also allows them to monitor the websites people visit. Private internet use through VPNs may also be constrained, allowing fewer channels for private browsing – and child protection agreements mean that everyone not verifying their identity as over-18 will be blocked from much of the web. Legally operators must enforce blocks on a small blacklist of domains (e.g. child pornography), but monitoring web history is also data that is highly commercially exploitable.
Information storage is increasingly cheap and data protection laws some distance behind the technology, meaning that companies are building the biggest possible datasets now to hedge against future restrictions.
Less legitimately, mobile phones can also easily be compromised by malware and spyware. Apps may ask for greater rights than they strictly need, allowing remote access to the phone’s microphone and camera, and sharing text entered (e.g. emails, passwords) and location data. Occupy London protestors have been known to remove batteries and keep mobiles in a separate room while meeting to plan future actions. This may seem paranoid, but the Mark Kennedy case has shown police infiltration of ‘domestic extremist’ groups to be commonplace.
Does mobile data sharing matter? Some would argue no: users are knowingly exchanging their data for free access to entertaining and useful services. But the impact of such bargains goes beyond the individual. Companies such as insurers and financial lenders are keen to use whatever data they can to minimise risk. This may mean denying insurance or a mortgage on factors outside the applicant’s control – simply the likelihood that “people like you” (by location, or web use) are more likely to default on payments.
The customised advertising enabled by mobile data also have their costs. By being delivered on the basis of aggregated and probabilistic data, the recommendations made are normative. Does the working class teenager see ads for jobs in McDonalds rather than university degrees? Is pregnancy advice limited by religious affiliation? Personalised services offer convenience at the price of potentially constraining our possibilities for action.
Behind the commercial value of mobile data is network analysis: modelling our social relationships (call histories, social media friends) as the nodes and links of a graph, and analysing patterns and clusters. This has substantial predictive capacities: where one user is unknown to a mobile operator (or to Facebook), many personal details can be inferred from their patterns of interaction with known entities. An individual does not have to be directly known to be present in the network through their relationships with others.
Social media analysts do not only focus on the ‘social graph’ of relationships between people – they analyse ‘interest graphs’ (relationships between profile interests or topics of discussion, e.g. music or technology) in exactly the same way. To what extent does “the individual” remain the primary unit within these assemblages of behavioural data, social, material and semiotic relationships?
“Big data” has been one of the buzzwords of 2011, and grand claims are being made for its power:
The world is becoming data-ized as digital information and numerical measurement is being applied to all aspects of what people do, particularly things that couldn’t be measured before because it was impractical or impossible. (Think: using wireless and GPS in cars to base insurance premiums on where and when people actually drive, as has been possible since 2007.)
The impact will be as profound as the scientific method in the 18th century — which quickly moved past the sciences and left its mark on all areas of human endeavor. For instance, what is “quantitative decision making” in management, if not the scientific method applied to business…. Likewise, the BigData revolution is plowing through the sciences, and also jumped into mainstream areas, such as business and government.
Data; boring but… by Ken Cukier, 6 March 2011
The problem with these claims is that they conflate increased power to capture and store data with (i) being able to extract meaningful insights from it, and (ii) being able to successfully act on and implement these insights, with (iii) no unexpected or adverse effects. Clearly cracking the first part doesn’t save the world on its own.
Further, big data evangelism often trips over into technocratic thinking, a belief that ‘nerdpower makes right’. Excitable blogposts about exabyte datasets, rather than defining the right problems to solve. Wide-eyed admiration for the amount of data that can be gathered, without recognition for the ethical rightness (or otherwise) of doing so.
Which is to say that big data is fundamentally political. Whether we choose to theorise it as technology or knowledge [actually, there's a good PhD proposal...], the act of recording the world in this way privileges particular values, worldviews and types of action.
In his blog post Lessons of the Victorian data revolution, Pete Warden insightfully makes the connection with technocratic thinking and brings in that great study of central planning, James Scott’s Seeing Like A State:
James Scott’s “Seeing Like a State” looks at the legacy of the Victorian scientific revolution, and shows how the very success of its ideas had a dark side. [Similarly,] Creating datasets may help technical people [...] to understand problems and propose solutions, but it also means that [...] other people with deep, lived experience of the domains will be overruled. In the 20th century the prestige of the scientific toolkit was used to justify disasters like the collectivization of agriculture, as technocrats around the world wielded numbers to take power away from “inefficient” smallholders. Those figures were mostly proven bogus by reality, as plans with no knowledge of conditions on the ground failed when confronted with the wildly variable conditions of soil, weather and pests that farmers had spent a lifetime learning to cope with.
Lessons of the Victorian data revolution by Pete Warden
If you’ve not read ‘Seeing Like A State’, incidentally, I recommend it. In it Scott surveys the great utopian schemes of the 20th century, from Le Corbusier’s urban planning in Brasilia to Russian collectivisation of agriculture and China’s Great Leap Forward. Each well-intentioned and yet spectacular failures, with millions of deaths. His argument is that centrally-managed planning does not work because it rides roughshod over the complex interdependencies on the ground.
Perhaps, under ‘big data’ ideology, we might ask – is this not simply a problem of too little information? We have the capacity to measure everything now – did Corbusier or Stalin fail because their data was not sufficiently granular?
Scott would disagree. The problem at hand is not quantity of knowledge but its very type. Common to each central planning disaster is a belief in a high-modernist ideology claiming that science can improve every aspect of human life, and an authoritarian central power willing to effect large-scale re-orderings of society and nature. “Big data will solve everything” can, clearly enough, be another iteration of the same. Scott – and, in fact, Friedrich Hayek’s criticism of centrally-planned economies (The Rule of Serfdom, 1944) – is that this disregards local and personal knowledge (Scott might add, embodied and tacit knowledge), and the complex diversity of organisation required and ends sought. (Hayek may believe that this can be summarised through the price mechanism, but Scott’s metis (local knowledge) is rather less reducible than that.)
Central planning – or big data – may seek to make the complexity of local situations legible to systemised, technocratic thinking – but the two are essentially incommensurable. Talk of ‘big data’ needs to be visible as something bringing with it a particular modernist worldview, and alongside that a particular relationship of power over the specificities – places, people – represented as nodes and datapoints. Technology is rarely value-neutral.
This is not to say, however, that ‘big data’ is necessarily socially oppressive. Perhaps there are alternatives – I am still thinking this through.
In my recent Bugged Planet post, I drew attention to Indy Johar’s tweet where he noted “the asymmetry of personal data, open for the 99% & deep analytics for the 1%” [source]. This raises the question, what if the analytics were open to the 99%? What would this take, what would this look like, and would it actually redistribute power in any way?