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RISE OF THE MACHINES:WHO IS THE ‘INTERNETOF THINGS’ GOOD FOR?In San Francisco, a young engineer hopes to“optimise” his life through sensors that track hisheart rate, respiration and sleep cycle. InCopenhagen, a bus running two minutes behindschedule transmits its location and passengercount to the municipal traffic signal network,which extends the time of the green light at eachof the next three intersections long enough forits driver to make up some time. In Davao Cityin the Philippines, an unsecured webcamoverlooks the storeroom of a fast food stand,allowing anyone to peer in on all its comings andgoings.

What links these wildly different circumstancesis a vision of connected devices now being soldto us as the “internet of things”. The technologistMike Kuniavsky, a pioneer of this idea,characterises it as a state of being in which“computation and data communication [are]embedded in, and distributed through, ourentire environment”. I prefer to see it for what itis: the colonisation of everyday life byinformation processing.

Though it can often feel as if this colonisationproceeds of its own momentum, distinctambitions are being served wherever andhowever the internet of things appears. Theinternet of things isn’t a single technology.About all that connects the various devices,services, vendors and efforts involved is the endgoal they serve: capturing data that can then be

used to measure and control the world aroundus.

Whenever a project has such imperial designs onour everyday lives, it is vital that we ask justwhat ideas underpin it and whose interests itserves. Although the internet of things retains acertain sprawling and formless quality, we canget a far more concrete sense of what it involvesby looking at how it appears at each of threescales: that of our bodies (where the effort isreferred to as the “quantified self”), our homes(“the smart home”) and our public spaces (“thesmart city”). Each of these examples illuminatesa different aspect of the challenge presented tous by the internet of things, and each hassomething distinct to teach us.

At the most intimate scale, the internet of thingsis visible in the form of wearable biometricsensors. The simplest of these are little morethan networked digital pedometers, which countsteps, measure the distance a person hastraversed, and furnish an estimate of thecalories burned in the course of this activity.More elaborate models measure heart rate,breathing, skin temperature and evenperspiration.

If wearable biometric devices such as Fitbits andApple Watches are, in theory, aimed at rigorousself-mastery, the colonisation of the domesticenvironment by similarly networked productsand services is intended to deliver a verydifferent experience: convenience. The aim ofsuch “smart home” efforts is to short-circuit theprocess of reflection that stands between havinga desire and fulfilling that desire by buyingsomething.

Right now, the perfect example of this is agadget being sold by Amazon, known asthe Dash Button. Many internet-of-thingsdevices are little more than some conventionalobject with networked connectivity tacked on.The Dash Button is the precise opposite, a thingin the world that could not have existed withoutthe internet. I cannot improve on Amazon’s owndescription of this curious object and how itworks, so I’ll repeat it here: “Amazon DashButton is a Wi-Fi-connected device that reordersyour favourite item with the press of a button.To use Dash Button, simply download theAmazon app from the Apple App Store or GooglePlay Store. Then, sign into your Amazon Prime

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account, connect Dash Button to Wi-Fi, andselect the product you want to reorder. Onceconnected, a single press on Dash Buttonautomatically places your order.”

In other words: single-purpose electronicdevices, each dedicated to an individual brandeditem, that you press when you’re running low.Pressing a Dash Button specific to yourpreferred pet food, washing powder or bottledwater automatically composes an order requestto Amazon for that one product.

An Amazon Dash button

I don’t for a second want to downplay the valueof such a product for people who have ageingparents to look after, or kids to drop off atdaycare, or for whom simply getting in the car topick up some cat food may take an hour or moreout of their day. But the benefit to the individualcustomer is tiny compared with what Amazongains. Sure, you never run out of cat food. ButAmazon gets data on the time and place of yourneed, as well as its frequency and intensity, andthat data has value. It is an asset, and you canbe sure that Amazon will exploit it in every wayits terms and conditions permit – including byusing it to develop behavioural models that mapour desires in high resolution, so as to targetthem with even greater efficiency in the future.

Again, the aim of devices such as the DashButton is to permit the user to accomplishcommercial transactions with as little consciousthought as possible – not even the few momentsit takes to tap out commands on thetouchscreen of a phone or tablet. The data onwhat the industry calls “conversion” is as clearas it is unremitting: with every box to tick orform to fill, the percentage of users that make itall the way to checkout tumbles. The fewer stepsthere are in a transaction, the more likely peopleare to spend their money.

Manufacturers, enticed by the revenue potentialof conquering the domestic environment, keeptrying to eliminate these steps, in the hope thatone of their connected products will become asessential to everyday life as the smartphone. Therecent industry push toward the “smart home” issimply the latest version of this.

For the moment, this strategy is centred on so-called smart speakers, a first generation ofwhich have now reached the market. Theseproducts include the Amazon Echo and GoogleHome, each of which is supposed to function asthe command hub of a connected domesticenvironment. Amazon’s Echo is a simplecylinder, while the Google Home is a bevelledovoid. But the physical form of such speakers isall but irrelevant, as their primary job is tofunction as a branded “virtual assistant”,providing a simple, integrated way to access thenumerous digital controls scattered throughoutthe contemporary home – from lighting andentertainment to security, heating, cooling andventilation systems.

Google, Microsoft, Amazon and Apple each offertheir own such assistant, based on natural-language speech recognition. Most are givenfemale names, voices and personalities,presumably based on research indicating thatusers of all genders prefer to interact withwomen. Apple’s is called Siri and will, accordingto reports, soon be getting its own device,Amazon’s Alexa, and Microsoft’s Cortana, whileone simply addresses Google’s Home offering as“Google.”

At first, such devices seem harmless enough.They sit patiently and quietly at the periphery ofour awareness, and we only speak to them whenwe need them. But when we consider them morecarefully, a more problematic picture emerges.

This is how Google’s assistant works: youmention to it that you’re in the mood for Italianfood, and then, in the words of one New YorkTimes article, it “will then respond with somesuggestions for tables to reserve at Italianrestaurants using, for example, the OpenTableapp”.

This example shows that though the choicesthese assistants offer us are presented asneutral, they are based on numerous inbuilt

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assumptions that many of us would question ifwe were to truly scrutinise them.

Ask restaurateurs and front-of-house workerswhat they think of OpenTable, for example, andyou will swiftly learn that one person’sconvenience is another’s accelerated pace ofwork, or worse. You’ll learn that restaurantsoffering reservations via the serviceare, according to the website Serious Eats,“required to use the company’s proprietary floor-management system, which means leasinghardware and using OpenTable-specificsoftware”, and that OpenTable retains ownershipof all the data generated in this way. You’ll alsolearn that OpenTable takes a cut on reservationsper seated diner, which obviously adds up to asignificant amount on a busy night.

Conscientious diners have therefore been knownto bypass the ostensible convenience ofOpenTable, and make whatever reservationsthey have to by phone. Bycontrast, Google Home’s frictionless default tomaking reservations via OpenTable normalisesthe choice to use that service.

This is not accidental. It reflects the largelypreconscious valuations, priorities andinternalised beliefs of the people who devisedGoogle Home. As throughout the industry, thatis a remarkably homogeneous cohort of youngdesigners and engineers. But more importantthan the degree of similarity they bear to oneanother is how different they are from everyoneelse.

Illustration: Getty/Guardian Design

Internet-of-things devices are generallyconceived by people who have completelyassimilated services such as Uber, Airbnb andApple Pay into their daily lives, at a time whenfigures from the Washington DC-based PewResearch Center suggest that a significant

percentage of the population has never used oreven heard of them. For the people who designthese products, these services are normal, andso, over time, they become normalised foreveryone else.

There are other challenges presented by this wayof interacting with networked information. It’sdifficult, for example, for a user to determinewhether the options they are being offered by avirtual assistant result from what the industrycalls an “organic” return – something thatlegitimately came up as the result of a searchprocess – or from paid placement. But the mainproblem with the virtual assistant is that itfosters an approach to the world that is literallythoughtless, leaving users disinclined to sit outany prolonged frustration of desire, and ever lesscritical about the processes that result ingratification.

Virtual assistants are listening to everything thattranspires in their presence, and are doing so atall times. As voice-activated interfaces, theymust be constantly attentive in order to detectwhen the “wake word” that rouses them isspoken. In this way, they are able to harvestdata that might be used to refine targetedadvertising, or for other commercial purposesthat are only disclosed deep in the terms andconditions that govern their use. The logicoperating here is that of preemptive capture: thenotion that companies such as Amazon andGoogle might as well trawl up everything theycan, because no one knows what value might bederived from it in the future.

This leads to situations that might be comical,were it not for what they imply about thenetworking of our domestic environments. Thesestories circulate as cautionary tales: one of thebest-known was the time the US National PublicRadio network aired a story about the AmazonEcho, and various cues spoken on the broadcastwere interpreted as commands by Echosbelonging to members of the audience, causingdomestic chaos.

Put aside for one moment the question ofdisproportionate benefit – the idea that you asthe user derive a little convenience from yourembrace of a virtual assistant, while its providergets everything – all the data about your life andall its value. Let’s simply consider what gets lostin the ideology of convenience that underlies thisconception of the internet of things. Are theconstraints presented to us by life in the non-

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connected world really so onerous? Is it really sodifficult to wait until you get home before youpreheat the oven? And is it worth giving away somuch, just to be able to do so remotely?

Most of us are by now aware that our mobilephones are constantly harvesting informationabout our whereabouts and activities. But wetend to be relatively ignorant of the degree towhich the contemporary streetscape has alsobeen enabled to collect information. Thisdevelopment is often called the “smart city”. Ifthe ambition beneath the instrumentation of thebody is ostensible self-mastery, and that of thehome is convenience, the ambition at the heartof the smart city is nothing other than control –the desire to achieve a more efficient use ofspace, energy and other resources.

A broad range of networked information-gathering devices are increasingly beingdeployed in public space, including CCTVcameras; advertisements and vending machinesequipped with biometric sensors; and the indoormicropositioning systems known as “beacons”that, when combined with a smartphone app,send signals providing information about nearbyproducts and services.

The picture we are left with is that of oursurroundings furiously vacuuming upinformation, every square metre of seeminglybanal pavement yielding so much data about itsuses and its users that nobody yet knows whatto do with it all. And it is at this scale of activitythat the guiding ideology of the internet of thingscomes into clearest focus.

The strongest and most explicit articulation ofthis ideology in the definition of a smart city hasbeen offered by the house journal of theengineering company Siemens: “Several decadesfrom now, cities will have countlessautonomous, intelligently functioning IT systemsthat will have perfect knowledge of users’ habitsand energy consumption, and provide optimumservice ... The goal of such a city is to optimallyregulate and control resources by means ofautonomous IT systems.”

There is a clear philosophical position, even aworldview, behind all of this: that the world is inprinciple perfectly knowable, its contentsenumerable and their relations capable of beingmeaningfully encoded in a technical system,

without bias or distortion. As applied to theaffairs of cities, this is effectively an argumentthat there is one and only one correct solution toeach identified need; that this solution can bearrived at algorithmically, via the operations of atechnical system furnished with the properinputs; and that this solution is something thatcan be encoded in public policy, withoutdistortion. (Left unstated, but strongly implicit,is the presumption that whatever policies arearrived at in this way will be appliedtransparently, dispassionately and in a mannerfree from politics.)

Every aspect of this argument is questionable.Perhaps most obviously, the claim that anythingat all is perfectly knowable is perverse. Howeverthoroughly sensors might be deployed in a city,they will only ever capture what is amenable tobeing captured. In other words, they will not beable to pick up every single piece of informationnecessary to the formulation of sound civicpolicy.

Other, all-too-human distortions inevitablycolour the data collected. For instance, peoplemay consciously adapt to produce metricsfavourable to them. A police officer underpressure to “make quota” may focus oninfractions that she would ordinarily overlook,while conversely, her precinct commander,under pressure to present the city as ever-safer,may downwardly classify a felony assault as asimple misdemeanour. This is the phenomenonknown to viewers of The Wire as “juking thestats,” and it is particularly likely to occur whenfinancial or other incentives depend on achievinga performance threshold.

Illustration: Getty/Guardian Design

There is also the question of interpretation.Advocates of smart cities often seem to proceedas if it is self-evident that each of our acts has asingle, salient meaning, which can be

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recognised, made sense of and acted uponremotely by an automated system, without anypossibility of error. The most prominentadvocates of this approach appear to believe thatno particular act of interpretation is involved inmaking use of any data retrieved from the worldin this way.

But data is never “just” data, and to assertotherwise is to lend inherently political andinterested decisions an unmerited gloss ofscientific objectivity. The truth is that data iseasily skewed, depending on how it iscollected. Different values for air pollution in agiven location can be produced by varying theheight at which a sensor is mounted by a fewmetres. Perceptions of risk in a neighbourhoodcan be transformed by slightly altering thetaxonomy used to classify reported crimes. Andanyone who has ever worked in opinion pollingknows how sensitive the results are to theprecise wording of a survey.

The bold claim of “perfect” knowledge appearsincompatible with the messy reality of all knowninformation-processing systems, the humanindividuals and institutions that make use ofthem and, more broadly, with the world as weexperience it. In fact, it is astonishing that anyexperienced engineer would ever be so unwaryas to claim perfection on behalf of anycomputational system, no matter how powerful.

The notion that there is one and only onesolution to urban problems is also deeplypuzzling. Cities are made up of individuals andcommunities who often have competingpreferences, and it is impossible to fully satisfyall of them at the same time.

That such a solution, if it even existed, could bearrived at algorithmically is also implausible.Assume, for the sake of argument, that there didexist a master formula capable of balancing theneeds of all of a city’s competing constituencies.It certainly would be convenient if this goldenmean could be determined automatically andconsistently. But the wholesale surrender ofmunicipal management to an algorithmic toolsetseems to place an undue amount of trust in theparty responsible for authoring the algorithm.

If the formulas behind this vision of future citiesturn out to be anything like the ones used in thecurrent generation of computational models, life-altering decisions will hinge on the interaction ofpoorly defined and subjective values. The output

generated by such a procedure may turn onhalf-clever abstractions, in which complexcircumstances resistant to direct measurementare reduced to more easily determined proxyvalues: average walking speed stands in for the“pace” of urban life, while the number of patentapplications constitutes an index of“innovation”, and so on.

Quite simply, we need to understand thatcreating an algorithm intended to guide thedistribution of civic resources is itself a politicalact. And, at least for now, nowhere in thecurrent smart-city literature is there anysuggestion that either algorithms or theirdesigners would be subject to the ordinaryprocesses of democratic accountability.

And finally, it is difficult to believe that any suchfindings would ever be translated into publicpolicy in a manner free from politics. Policyrecommendations derived from computationalmodels are only rarely applied to questions aspolitically sensitive as resource allocationwithout some intermediate tuning taking place.Inconvenient results may be suppressed,arbitrarily overridden by more heavily weighteddecision factors, or simply ignored.

As matters now stand, the claim of perfectcompetence that is implicit in most smart-cityrhetoric is incommensurate with everything weknow about the way technical systems work. Italso flies in the face of everything we know abouthow cities work. The architects of the smart cityhave failed to reckon with the reality of power,and the ability of elites to suppress policydirections that don’t serve their interests. Atbest, the technocratic notion that the analysis ofsensor-derived data would ever be permitted todrive municipal policy is naive. At worst, though,it ignores the lessons of history.

So, yes: the internet of things presents manynew possibilities, and it would be foolish todismiss those possibilities out of hand. But wewould also be wise to approach the entiredomain with scepticism, and in particular toresist the attempts of companies to gather evermore data about our lives – no matter how muchease, convenience and self-mastery we are toldthey are offering us.

This is an adapted extract from RadicalTechnologies: The Design of EverydayLifeby Adam Greenfield, published this week byVerso.

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