Chapter 4
Social machines
SO LET’S LOOK at one powerful entanglement of digital apes and their technology. Not the Irish policeman and his bicycle, but the social machine. Social machines are sets of activities with useful outcomes which harness the abilities of humans with the powers of mechanisms or engines. The two are wrapped together within a combined conscious process. The consciousness is all in the humans. The process is both learned and applied by humans, and built into the structure and operation of the engines. Often, but not always, they involve a project, and institutions of some sort, too, like a website, a club, an online game. A successful example, certainly the star amongst the grand obvious ones, is Wikipedia, far and away the most comprehensive encyclopaedia there has ever been. Also, far and away the most accessible ever, because Wikipedia, of course, uses the World Wide Web as its mechanism, and it is the web which has given huge impetus to the practice and study of social machines.
The history of Wikipedia has instructive stages. Its founder, Jimmy Wales, began with the idea of a comprehensive up-to-date web encyclopaedia, called Nupedia, whose authors would be volunteers with a professional link to the fields in question, all articles being reviewed and certified in a rigorous seven-step process by bona-fide experts. This strict editorial system, based on premises admirable to librarians, led to its downfall. Taking on the authorship of a Nupedia article was like submitting a graduate school term paper, a high-tension invitation to humiliation unless backed up by intense hard work and a genuine feel for the subject. There were nowhere near enough willing unpaid victims to cover the desired, immensely wide, ground, sufficiently quickly. Wales and his co-founders needed to bump into a genuine innovation. They found it in an invention by Ward Cunningham, the wiki. This allowed multiple authors to work on the same web page, the editing software being at the page’s end, not on the machines of the authors. Wales built that into a community of volunteer editors. Walter Isaacson describes what happened:
A peer-to-peer commons collaboratively created and maintained by volunteers who worked for the civic satisfactions they found. It was a delightful, counterintuitive concept, perfectly suited to the philosophy, attitude, and technology of the Internet. Anyone could edit a page, and the results would show up instantly. You didn’t have to be an expert. You didn’t have to fax in a copy of your diploma. You didn’t have to be authorized by the Powers That Be. You didn’t even have to be registered or use your real name. Sure, that meant that vandals could mess up pages. So could idiots or ideologues. But the software kept track of every version. If a bad edit appeared, the community could get rid of it by clicking on a ‘revert’ link … Wars have been fought with less intensity than the reversion battles on Wikipedia. And somewhat amazingly, the forces of reason regularly triumphed.
The Innovators: how a group of hackers, geniuses, and geeks created the digital revolution, 2014
Within two years, Wikipedia had 100,000 articles. Currently there are over 5 million in the English version, and around 40 million in a total of 293 languages. In the ensuing knowledge wars, conventional large printed encyclopaedias were doomed. The oldest English encyclopaedia, Encyclopaedia Britannica, established in the 1770s, whose contributors have included 110 Nobel Prize-winners and 5 US presidents, had little choice except to move online. Initially it did so in parallel to the print edition, but in 2012 finally ceased to be a book at all. Big hardcover editions on paper simply could not update themselves as fast as the web, and the handiness of digital devices with free access to information about everything reduced the desire to own such a large expensive thing at all. Britannica continues to make a case that their articles, composed by professional experts, are more accurate than Wikipedia’s articles. And Britannica disputed an article in Nature which claimed to have compared the two sites and found them much of a muchness, and both on the whole commendably accurate. In reality, the more technical a Wikipedia article is, the more likely that there are reasonably accurate hands with formal qualifications involved at some stage.
Indeed, one of the several astonishing things about Wikipedia is that it has developed into something like a universal agreed corpus of knowledge. It defines, in so far as anything can define, what it is to be an agreed fact in the twenty-first century. They take this responsibility seriously, and have an elaborate verifiability and reliability procedure. It depends in part on mechanised checking that cited sources really are sources and are cited by sufficient others to be so. In principle, this is similar to the PageRank system used by Google, which we will discuss in Chapter 7. And it rests partly on a solidified notion of what the canon of basic agreed science is, at this juncture. Contradicting the canon, or canonical facts, is flagged up, or simply disallowed, by the social machine. The article on gravity begins with the statement that it is a natural phenomenon by which all things with mass are brought toward (or gravitate toward) one another, including planets, stars, and galaxies. If a ranking professor, with all due Wikipedia editor status, were to amend ‘brought toward’ to ‘repelled’, so that Newton’s apple would have fallen upwards, the amendment would be rejected in under a minute. The content is self-repairing, like human skin. Machines are adding value, analysing, and editing content, under ape supervision, in an almost biological fashion.
With the Enlightenment in the late seventeenth and early eighteenth centuries, the Christian church in the West lost much of its authority simply to announce the truth and have it universally regarded as so, on pain of dire consequences for the disputatious. For the first time since then, the western world now has an agency that certifies what is accepted as the truth, across a comprehensive field. It is paradoxical (and healthy) that the machine in question is often doubted. Did you read that on Wikipedia? Really? Crucially, astonishingly, all this knowledge is available to everyone this instant, by touching a button on their wrist or clicking on their screen. Furthermore, the factual social machine is a cooperative, voluntary, unpaid one. Anybody with very basic digital competence can join in. Not by any means a majority of the world population, but a reasonably wide slice of the highly educated part of it. About 100,000 people do so with any regularity, although over 30 million registered with the site, and may have made a couple of edits on subjects they care about. Around 12,000 keen Wikipedians edit intensively.
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Here is another kind of social machine. The Defense Advanced Research Projects Agency (DARPA) is a United States agency specialising in the deployment of cutting-edge technology for military and other governmental purposes. It has a popular reputation for wacky work — goat staring and LSD use and inventing Candy Crush. (The first two are attested to in Jon Ronson’s The Men Who Stare at Goats. We made the last example up, but many of the stories about DARPA are made up.) They have in truth been involved in the early stages of things of great civilian value: global positioning systems, graphical user interfaces, networking, and the internet. As well as many armed service applications: satellite and submarine technologies amongst them.
Shrouded in some mystery DARPA may be, but they really did, very publicly, do a very interesting thing in 2009. They wanted to test whether the many new electronic ways in which people network and share information could quickly track down an important prey. They quietly tethered 10 red balloons, each perhaps a dozen feet in diameter, the cables stretching 30 feet or so in the air, at sites spread right across the United States. Some were in well populated and well-known locations. One was very visible in Union Square in San Francisco, for instance. Others were beyond the far side of nowhere. There were thousands of miles between them, on the east coast, on the west coast, in northern and southern states. With a month’s notice of tethering day, 5 December 2009, they offered a $40,000 prize to the individual or team who could gear themselves up to find all of them the fastest.
They were not trying to solve the US lost balloon crisis. They wanted to know how quickly the public might help them to track down a terror threat, whether that be an evil-doer, an infected person, a suspect car, a dirty bomb. To their surprise, a team found all 12 balloons in nine hours. A dozen other teams found most of them within a couple of days. The winners, perhaps less surprisingly, were from the Massachusetts Institute of Technology. They used a canny incentive scheme, to motivate large numbers of self-recruits to reach out through all their own social media and contacts for information, but also to motivate them to incentivise others. Here is the MIT team’s own description of their scheme:
We’re giving $2000 per balloon to the first person to send us the correct coordinates, but that’s not all — we’re also giving $1000 to the person who invited them. Then we’re giving $500 to whoever invited the inviter, and $250 to whoever invited them, and so on … (see how it works).
It might play out like this. Alice joins the team, and we give her an invite link like http://balloon.media.mit.edu/alice. Alice then e-mails her link to Bob, who uses it to join the team as well. We make a http://balloon.media.mit.edu/bob link for Bob, who posts it to Facebook. His friend Carol sees it, signs up, then twitters about http://balloon.media.mit.edu/Carol. Dave uses Carol’s link to join … then spots one of the DARPA balloons! Dave is the first person to report the balloon’s location to us, and the MIT Red Balloon Challenge Team is the first to find all 10. Once that happens, we send Dave $2000 for finding the balloon. Carol gets $1000 for inviting Dave, Bob gets $500 for inviting Carol, and Alice gets $250 for inviting Bob. The remaining $250 is donated to charity.
Underlying this was a version of the popular small world meme, widely known as six degrees of separation, or the Kevin Bacon game. The mathematics of small world networks are complex, and not as simple as the meme would have them. But there are general truths here, on which all the smart teams banked. Every red balloon in the competition, even the most remote, was visible to at least some few people, who between them would know a lot more people, who … Also, oddly perhaps, except to mathematicians, a small proportion of people know a large number of others, and tend to be super-connectors, acting rather like junction boxes or routers. If only one person sighting a balloon was somehow in contact with anyone in MIT’s long chain of motivated recruits, that balloon was visible to all. The occasional super-connector would ensure the network was huge. That this process found every balloon in nine hours — and that a high proportion of the other serious contenders found most of them in the same timescale and all of them in just a little longer — says an immense amount about the power of the communication technologies involved. An impossible thought experiment: how long would the equivalent challenge have taken to play itself out before the modern era, let’s say in 1950? Using all the available media, the telephone, telegraph, broadcast radio, newspapers, and the US Mail, and perhaps advertising in advance via the Paramount and Movietone cinema newsreels, the urban balloons might just have been located and reported in a couple of days. It would have been easy, surely, to hide some away for weeks. Everybody ‘knows’ that Orson Welles’ radio broadcast in 1938 of his interpretation of H. G. Wells’ The War of the Worlds, in which Martians invade the earth, caused mass panic across the whole of the US. Yet modern historians agree that hardly anybody heard the programme and there was no panic whatsoever, except in the entertainment pages of the New York newspapers. Motivating a truly large network in a very short interval of time is a recent phenomenon. Social machines can and do coordinate people at scale.
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Here is yet another variety of social machine. The Kenyan election on 27 December 2007 was followed by a wave of riots, killings, and turmoil. Rumour and fear spread like a contagion. The African technology commentator Erik Hersman, who was raised in Sudan and graduated from Kenya’s Rift Valley Academy and Florida State University, read a post by fellow blogger Ory Okolloh calling for a web application to track incidents of violence and areas of need. Within a few days, Hersman had organised Okolloh and two like-minded developers in the US and Kenya to make the idea a reality. The result was Ushahidi, software that allowed local observers to submit reports using the web or else SMS messages from mobile phones. These were placed on a Google Map, creating an archive showing the sequence and the geography of disturbing events. Ushahidi focused the eyes of the world on Kenya, and exerted huge moral pressure on the authorities to restore order. It has since been extended and adapted for use around the world, from Washington DC’s previous ‘Snowmageddon’ in 2010 to the Japanese Tsunami of 2011. It derives its power from the principle that no one knows everything, but everyone knows something.
In a similar vein, a few years later, on 12 January 2010, a 7.0 magnitude earthquake devastated Port-au-Prince, the capital of Haiti. As the world rushed to help, the relief agencies realised they had a problem. There were no detailed maps of the city. Because the country is so poor, this piece of digital infrastructure had never been constructed. Relief and aid workers poured into the country with their GPS equipped computers, laptops, and phones. As they walked the ruined streets, their GPS logs were uploaded to the tools of the web such as WikiProject and OpenStreetMap. They were crowdsourcing details of the city’s streets and buildings. Within two weeks, these same relief workers, government officials, and ordinary citizens had access to detailed maps of the entire capital.
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These examples all feature a new kind of collective problem solving. All of them are at web-scale. We would resist too wide a definition of social machines. An amateur football club has equipment (ball, pitch, showers, well-stocked bar), and a set of process conventions both formal (the offside rule) and informal (you lost us the game you can buy this round of drinks). But the technology is crude, and, possibly crucially, the whole apparatus takes place in real time in one place. If a local football or baseball league uses match-arranging software, that might perhaps be a small-scale social machine. So perhaps dispersed geography is a key defining component of a social machine, at least of the ones that will make large differences to our lives, along with the constant interaction of machine and ape, in a combined agreed process. The raw materials are people, data, incentives, trust, open standards, sociality, and a global computing fabric. Understanding the chemistry of these elements requires a science of the web and a structured approach to understanding this new world order. Arguably, the web is only a sub-set of the true field of study, which might be the whole of technological modernity.
The study of social machines has developed a tool-kit of ideas, which can then interestingly be retrofitted to human relationships with technology before the internet came along. A nuclear submarine on active duty alone thousands of miles from base. The metro systems of major cities which transport between them hundreds of millions of people. The narrow definition of machine in neither case leads to a complete picture, let alone explanation, of what transpires in the operation. Trains and submarines move people; but people with purposes move trains and submarines. Colson Whitehead over 20 years has (arguably) investigated further intriguing aspects of this in fiction. His prize-winning bestseller of 2017, The Underground Railroad, turns the centuries-old metaphor about the slave escape network from the southern states to the north into a metaphor about that metaphor: suppose the railroad was physically just that, a shambling steam engine pulling a dilapidated box car bound for freedom. The bestseller was preceded by his (again, arguably) more astonishing first novel in 1999, The Intuitionist, which imagined a world much like 1950s New York, in which elevators are recognised as immensely important, and elevator inspectors, key officials, are riven by ideological dispute over the nature of the relationship between vertical transportation devices and humans. Our heroine, a young black woman, is of the Intuitionist school, bitter enemies of the Empiricists. Read it and find out why.
Also worth noting, for our later discussion of the nature of the relationship between the apes and our digital machines, is that social machines blend human and machine and web-based judgement and intelligent decisions, and that, at present, and for the foreseeable future, the basic form of the teamwork is that the machines do the hard work, and the humans make the sophisticated judgements. Perhaps today most of DARPA’s red balloons would have featured in online photographs. An intelligence agency — possibly DARPA themselves — might have been able to steal all very recent photos on Facebook and Twitter and Instagram and Flickr, and unleash specially trained machines to look for red balloons. Any one of those large corporations could have searched their own content, nearly lawfully. Those two, different, instances of power are worrying in themselves, but would not have found all the 10 balloons in the nine hours MIT managed. People are still better spotters than machines, machines make the network of people a powerful force. And in pursuit of certain objectives, we might say, a magnificent one.
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We should go back in history a little. It has been plausibly argued that the clock is a social machine, or, more accurately, that clocks are many overlapping social machines. There has been a wide variety of physical time measurement devices over a long time, starting with natural clocks — tree-stump sundials, for example, or a gap in the mountains at the morning end of a valley — which were worked up over thousands of generations by our flint-knapping forebears into purpose-built devices, a few of them as sophisticated, enduring, and staggeringly tough to construct as Stonehenge. That kit has no value without a theory planted and nurtured in many human minds simultaneously, a theory based on specific observational detail, then solidified in social conventions about numbers, hours, seasons. Often there has been a religious element, and notions of trade and travel, of binding this community and its work together, and of coordinating that with other worlds, physical and metaphysical. Then, of course, ever more technical apparatus was added to the framework; ever more sophisticated mechanical clocks leading to the beautiful encapsulation of science by Harrison’s nautical instruments, which allowed sea captains, finally, to pinpoint their location on the high seas. And, thereafter, the transition into electronic and digital time. The exact time on everyday computers, perfect time on everyone’s iPhone and watch. And the disappearance of most public clocks.
Christian Marclay’s The Clock is one of the great post-modern artworks of our time, and about our time. A 24-hour film, it won the Golden Lion at Venice Biennale 2011, among many other plaudits. Shown only in galleries, it was spliced together out of clips from at least 3000 other films, all of them including a clock, a watch, a ticking bomb, or a character mentioning the exact time in every conceivable tone. These filmic moments were carefully coordinated so that The Clock displayed the actual time in the gallery on the minute, every minute. It is itself a grand meditation on the social machine of which horological devices are one component, and on the way thousands of film makers have consciously used tropes about timepieces, colluding with their audiences’ sophisticated cultural preconceptions of time passing, past, and future.
The Clock illustrates a deep general fact about social machines: they are reasonably easy to describe, as it were, mechanically and socially, but can be difficult to decode if their subject is itself difficult. To decode Wikipedia, ultimately one would have to decode knowledge, describe what aspects of it are encompassed by the machine, what aspects are limited or disguised, how each bit related to each other, whether those relationships constitute some genuine deep structure of knowledge. Similarly with both the clock and The Clock. The final question is, what is time, how does this relatively small work of art help to explain the vast machinery of worldwide time management, and ultimately how does that encompass, traduce, explicate, how time itself is experienced?
Meghan O’Rourke in the New Yorker:
Ultimately, ‘The Clock’ is a signature artwork of our archival age, a testament to the pleasures of mechanization (and now digitization). It’s an experience, I suspect, that would be nearly entirely illegible to an eighteenth-century time traveller who, curious what modern-day New Yorkers were all wound up about, wandered into the line. ‘The Clock,’ with its obsessive compiling, its miniature riffs, its capacious comic and dramatic turns, speaks to the completist lurking in all of present-day us. If montage is usually as cheaply sweet as Asti Spumante, ‘The Clock’ is Champagne: it’s what the form was invented for, it turns out. Drink it in deeply, and the days just might go on forever.
‘Is “The Clock” Worth the Time?, The New Yorker, 18 July 2012
The Clock not only is a social machine, it was produced by a social machine: Marclay’s previous work and growing status enabled him to pitch the idea to sponsors who paid for a gang of film buff editors under his command to trawl though films, clipping them. The independent film maker and novelist Chris Petit is perhaps the only person to focus on the fact that the constantly accurate time curated with care in the art gallery is a tissue of lies, each constructed by one of the hundreds of industrial concerns which built the original films, each just for once in its life functioning as the truth:
What amuses me (because everyone is so literal about it) is the time shown in clips isn’t of course the time when it was shot. They are exercises in continuity and pretence. In rare instances where ‘real’ time is shown it shows — as in a Godard scene from Sauve qui peut, shot on an early-morning station with a real express train thundering through and a real station clock, telling real time and two actors self-consciously faking it, rather wonderfully; one of the rare scenes that wakes you up, reminds you that you’re alive rather than trapped in a mechanical conceit.
Chris Petit e-mail to Iain Sinclair in The Clock, Museum of Loneliness and Test Centre Books, 2010
Social machines can be difficult to decode, not least because, as we have already discussed, their geography, like the online world they often inhabit, can be very strange. As we now see, their temporality can be dislocated; and no doubt so can every other everyday attribute. Where is Wikipedia? Is Errol Flynn rescuing that fictional woman right now? Can someone on the other side of the world show me a map of the pile of rubble that was my house? Is this your balloon?
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Website-based social machines are now very numerous. Let’s take a quick tour of a tiny proportion of the notable ones. GitHub will be much less well known to the general reader than Wikipedia, but has in fact been important in their lives. The ability of any digital device to do anything, every smart new application, every website, subsists in software programs, which are themselves fabricated out of computer source code, the binary digits that animate the machines. GitHub is a site which hosts vast quantities of software and its source codes, available to developers who want to use or modify it. (Different GitHub repositories allow use of their contents on different licences.) This enables developers to quickly search for and use large parts of the software resources they need to build new applications. The site is a serious social network for the geeks who register to use it, but its public stores can be browsed and downloaded at will by anyone.
A key driver for OpenStreetMap (which does what it says on the tin) was anger at the private proprietary ownership of mapping data in the UK. A similar situation pertains elsewhere in the world. Websites and books that want to use maps need permission, often at a price, from the owners of the maps. In the UK this was, and still is, particularly galling, since the government, on behalf of the people, had established the Ordnance Survey in the eighteenth century, and the taxpayers had been paying ever since for one of the largest and best mapping agencies in the world, whose data seemed now to belong to a semi-private profit-making corporation.
In parallel, the UK Hydrographic Office based in Taunton, Somerset, has a near monopoly on maps of the world’s seas. The Office’s maps are found on over 90 per cent of international trading ships. And are a key secret resource for the UK’s invisible nuclear submarine capability. That also makes a tidy profit for the government, more acceptable if less well known to the average citizen.
The collaborative OpenStreetMap venture relies on two kinds of technology. First, the web’s ability to collate almost anything with anything else, if asked in the right way. Second, the satellite-based Global Positioning System now in many cars, and the uncanny location-finding ability of smartphones. GPS technology allows ordinary people to know exactly where on the planet they are, and the former technology allows them to merge their information with thousands of other people’s, across land and time, using the wiki mechanism.
The result is a collectively owned, very up-to-date map, of many parts of the world. By definition, the more travelled by participants, the better the map. Probably better in New Jersey than New Guinea. It is made available freely to anyone who wants to use it, which now includes many web offerings that would have real trouble paying for Ordnance Survey data.
In a similar vein, the Waze traffic ranking site claims to be the world’s largest community-based traffic and navigation app. Users join up with other drivers in their local area who share real-time traffic and road information, ‘saving everyone time and gas money on their daily commute’.
This is a story of back and forth in a continuing civil war with the official providers in several countries, who have, partly through competitive pressure from small opponents, like OpenStreetMap, and from large opponents like Google, had to repeatedly make their offer more open. Crucial here is the legal apparatus of the state, British in the case of the Ordnance Survey. As we discuss elsewhere, electronic digits have no intrinsic status, humour, doctrine, identity, or any other apish characteristic in themselves. They are placed in frames of meaning by people. Actually, by society, which may have outlived Margaret Thatcher. One of those frames is the extensive corpus of property rights. So what the two new technologies used by OpenStreetMap actually allowed them to achieve was both a new way of creating a map, and a set of foundations for a new way of owning a map.
The same general approach pays dividends for FixMyStreet.com. Here is The Guardian newspaper’s encomium from 2008:
When you’ve just dodged a potentially lethal pothole on your bike, you want to report it there and then. Soon you’ll be able to do just that. The developers of FixMyStreet.com revealed last week that an iPhone interface is in the works.
Fixmystreet already enables anyone with a browser to report potholes, fly-tipping and other nuisances without needing to know which public authority is responsible for them. All you have to do is click on a map and enter the nature of the nuisance, along with a photograph if you like.
Although FixMyStreet was originally funded by the government, it is very much not a government web project. It is one foray in a guerrilla campaign of helpful but often disconcerting websites to emerge from the charity MySociety, which celebrated its fifth birthday last week.
Michael Cross, ‘The former insider who became an internet guerrilla’, The Guardian, 23 October 2008
And every local council in the UK now responds in some degree to the platform, and the platform, which is open source, has been replicated in one form or another in 20 countries. Excellent. Unfortunately, in the nine years since The Guardian lauded FixMyStreet, the number of potholes and other street defects in the UK has soared. A modern nation state is a complex coalition of competing interests.
Other enterprises have sought to use social machines to change that political process, both from within it and from outside, in many countries. TheyWorkForYou tries to hold public officials and representatives to account. Activists use concepts like ‘liquid’ or ‘delegative’ democracy, as opposed to representative democracy. Various software programs are used to enable citizens to express their preferences, accumulated over as many people as possible, directly to their elected representatives. Liquid democracy candidates in elections usually guarantee to follow those preferences if they win and do get to vote in national or local assemblies. Self-titled Pirate Parties in the Netherlands, Germany, Italy, Austria, Norway, and France have embraced delegative democracy using the open-source software LiquidFeedback. The Belgian Pirate Party have made their own software. The Flux Party in Australia has used blockchain technology, and contested several senate seats.
PatientsLikeMe is one of many social machines aiming both to contribute to doctoring, enhancing established processes, and to also replace it with an approach to health more centred on individuals. A number of applications collate official information about the success rate of hospitals or doctors’ surgeries, and make that information more accessible. They also add patients’ own rankings about the experience of care, in the style of ratings sites. Very much like TripAdvisor, the holiday and hotel quality ranker, also a very successful social machine, which convincingly claims to have 60 million members worldwide who have written hundreds of millions of reviews.
PatientsLikeMe applies varieties of that methodology to connect large numbers of patients to a process leading to improved outcomes, and passages through the health care system, for all. It aims also to aid research leading to better treatments. It was founded in Cambridge, Massachusetts, in 2005 by the brothers of Stephen Heywood, who died tragically young of ALS, Lou Gehrig’s disease. Its business model makes it free to ordinary individual users, charging commercial rates to pharmaceutical companies and others who want to use data to improve products for sale on the open market or to health providers.
Here is how their own website stakes their claim:
What is data for good?
It’s symptom, treatment and other health data that you choose to share to track how you’re doing over time, help the next person diagnosed learn, and tell researchers what people really need …
As a member, you have lots of opportunities to get in on data for good. Here’s what you can do today:
Share your experience with symptoms and treatments. Or simply tell us how you’re feeling. You’ll help researchers understand more about what patients are experiencing every day.
Lend your voice on important issues, like how to fight stigma, or what should be in an affordable health care plan. The forum is where you can find like minds, and a lot of support.
Become a pioneer in our most innovative research to date. You’ll start to learn even more about how DNA, biology and experience all contribute to health, disease and aging.
‘What Is Data For Good?’, PatientsLikeMe website
Another collective approach to this is the self-tracking movement. This began in the 1970s, with enthusiasts being a mix of well and unwell people, who attached themselves to what were, in present-day terms, the crude devices then available, and loaded the data grabbed by them into what would now be toy computers. The movement was therefore, in our terms, an early social machine, but once again the huge impetus came with the World Wide Web. The editors of Wired magazine established the company Quantified Self Labs in 2007 to be a focus for the movement. Beautifully designed, attractive devices, dedicated ones like Fitbit and apps on our smartphones, have become very common since then. Fitbit alone sold over 20 million in 2015, in a total world market of around 80 million shipped per year. Hundreds of millions in total on wrists around the world. Google, Apple, Samsung have all produced similar objects, or smartwaches with overlapping functions. About half of purchasers appear to actively use their new toys over a sustained period, which for many of them involves sharing and comparing data with others.
For the overwhelming mass of people, this is a small part of their lives. If the underlying premise is correct, that knowing how much exercise you are taking or hours you are managing to sleep will, in the average person, move it a bit towards the optimal, then sufficient slightly engaged people will make a significant difference to actual health over a large population. And for exercise and sleep read also information about any other vital signs.
But as a matter of fact, is the underlying premise correct? There is, generally, convincing evidence that people who are presented with facts can then be organised to take those facts into account in appropriate ways. Staff in social services departments making decisions about what package of care to allocate to an old person, if presented with information about both the costs and the statistically likely outcomes of different pathways, of residential care as opposed to care in the old person’s own home for instance, make better decisions, and their clients live longer, happier lives. After that fact was established in the 1980s by Professor Bleddyn Davies and colleagues, practice in UK care departments was changed accordingly, eventually by legislation. Studies of what really transpires to the bodies and minds of the millions of people now Fitbit-ing or Apple Watch watching are, at present, more ambiguous, at best. Few of the manufacturers could point to properly conducted, randomised trials. A team at the University of Pittsburgh studied 500 young people on a weight reduction programme. Half had smart devices, half didn’t. Over a full two years, those with devices lost an average of 3.5kg; those without devices lost an average of 5.9kg. That was, of course, the opposite of what the researchers expected. Now, that is one trial; the weight loss of the device users was still significant; we confidently predict that the device producers will soon be funding different research. The fact, though, to repeat one of our key messages, is that the digital ape is an immensely complex biological entity, much more sophisticated than the most amazing devices — much more amazing than the most sophisticated devices. In this instance, Professor John M. Jakicic at Pittsburgh speculates that the device users might have been discouraged by knowing how little they were achieving each day; or might have rewarded themselves for being active by eating a bit more.
For a minority of people, personal bio-statistics can become a way of life. Ian Clements of Brighton, for instance, an 80-year-old engineer and teacher amongst much else, has been self-monitoring for decades. He disagrees with the mainstream about practically everything, partly because the mainstream is too blinkered to see truths he sees, just occasionally because the mainstream is on the whole composed of decent people and Clements can sometimes, to his credit, be a very difficult character. He believes, amongst the many other radical things he believes, that his self-tracking and self-medication are what kept him alive after diagnosis by cancer specialists in 2007 that he had only weeks to live. He has chronicled his delayed demise in a book and online. He has, annoyingly for some, so far been dead right.
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These social machines have several features in common, over and above the definition we began with. They are all decentralised, technically adept, and free to the user. They all open up their processes, data, and results to everyone who wants it, not just as a general matter of principle, but as a core objective. That in part arises from the sociology of the people involved in them, as originators, as active participants, and as end-users. Many of them begin with one or two prime movers, entrepreneurs in conventional terminology, with perhaps a couple of dozen people who roar early approval and participate. Sometimes the philosophy is voluntary, altruistic, and social; sometimes it is commercial and social.
A social machine does not have to be voluntary or collectively owned. Wikipedia more or less is, pleasingly. But arguably it would operate just as well if it had any one of several alternative enterprise models. Certainly, the immense free labour donated to it by voluntary editors is its key asset, but that can happen in commercial organisations, too. Facebook is a massive profit-making corporation, but has all the features of a social machine. In particular, its working capital is, like Wikipedia’s, the information and labour supplied by participants. The topic is every contributor’s self and daily life, rather than facts about the world. On both sites, information has its daily value, either a shared activity in Facebook’s case, a use value in Wikipedia’s. In both cases, it is also immensely valuable as an unparalleled lump of corporate asset. Both have changed how millions of people conduct their lives. People engage because they want to. Pretty much by definition in a democratic society, both are thereby good things.
It is an open question whether, and in what circumstances, in a modern broadly capitalist mixed economy, voluntary or collective social machines, like Wikipedia, are more effective or efficient than privately owned profit-making social machines, like Facebook. PatientsLikeMe, like others, is a private corporation, not even a non-profit, although with very pro-social business practices and ethos. Both Wikipedia and Facebook are the best in class at what they do. No encyclopaedia has ever been as comprehensive as Wikipedia, no encyclopaedia has ever been anywhere near as frequently consulted. Over half of the world’s 7 billion people use the internet. Every month Wikipedia is consulted 15 billion times, five times for every connected person on the planet. Other social network sites have been good and have their fans, but none is on the scale of Facebook. Facebook had over 2 billion active users around the world in 2017 taking active to mean logging in at least once a month. That was a bit less than a third of the world’s social network users, but the largest single site.
Equally, OpenStreetMap and Waze are impressive. They are not, however, truth to tell, in most situations more impressive than the Apple and Google Maps map functions. These use data taken, well perhaps ‘unobtrusively’ would be a fairer designation than ‘secretly’, from tracking the movement of iPhones and phones with Android software, and enriching it with historical patterns and other data sources. This is very nearly a variety of inverse social machine, since it involves intelligent participating devices and unknowing humans doing the rote work, driving about. The traffic information in these apps is very good. If it says your journey from Penzance to Malmesbury should take 3 hours 28 minutes then that is how long it will take, if you disobey speed limits to the exact extent that other users today are disobeying them, and present weather and traffic conditions prevail. (Again, tweaked a little with historical patterns.) Because what the map in the app is doing is telling you a fact, based on hundreds of live observations: this is how long it takes. As artificial intelligence algorithms enter service in more and more areas of our lives, we will spend more and more time as partners in such inverse social machines. Information relayed from our activities and preferences will be hoovered up, processed, and fed back to us as useful heuristics. Our sleep and exercise patterns will help others to sleep and exercise. Our road accident patterns will help others not to have road accidents. The degree of conscious participation by humans in social machines will be highly variable.
One of the longest standing topics in academic social policy is analysis of the view that voluntarily or collectively provided things are, by virtue of the motives in their production, superior to things produced commercially or out of self-interest more generally. Important to distinguish: the claim is not merely that people clubbing together to do something enjoy themselves more than people who are just doing it for the money. The claim is that the activity has more value, and the actual product is objectively better. Specifically, for instance, that public services are likely to be better than the same services delivered by private profit-making organisations. (Possibly because of the attitude employees bring to their work.) This view began — academically, it is ancient in itself — with the early doyenne of British social policy, Professor Richard Titmuss of the London School of Economics. Titmus’ ideal is best laid out in The Gift Relationship, an influential study of the blood donor system in the UK. (Honoured by The New York Times as one of the ten most important books of the year when it first appeared in 1970.) He compares donation favourably to the blood selling system in other countries. He wishes to argue that the altruistic principle of the former is superior to the economism of the latter. That a society which will give, rather than sell, aid to the sick is just plain better, and that edge shows in the service itself. The book is brilliant, but highly dependent on the choice of example. It happens that nasty diseases can be transmitted through blood, and that the main practical way of screening donors is to ask them about their medical history. People selling their blood because they badly need the money naturally give different answers than people who are altruistically taking time off work to do a rather unpleasant good deed. So, at least when Titmuss was writing in the 1960s, the product actually was better. But that is scarcely a generalisable truth. In the nicest possible way, the example cheats.
Later work has demonstrated that public ownership of the means of production, and the employment status of workers, may be important for all kinds of reasons, but those reasons simply do not include the quality of the product. Privately owned hospitals, leisure centres, and care homes for older people vary in quality, inevitably. But the variation is just as great in publicly owned homes, over the same range.
Social machines both on and outside the web, in apps and through game machines, are just beginning to fulfil their potential to affect many other aspects of ordinary life, private and public. Let’s be clear. Even a small proportion of 7 billion brains arranged to work together is an astonishing, unprecedented resource.* A new, disruptive, and exciting way to generate, refine, and execute any thought, any plan, any movement, to build the solution to any knotty problem, to negotiate the resolution of any dispute. The astonishing devices we list here are only scratching the surface of the possible. We will see many steps onward from Wikipedia and Facebook. Individuals are immensely important; the collective with shared objectives can be overwhelmingly positive.
[* Several universities have combined in the academic SOCIAM project to look at all these issues. The interested reader is encouraged to visit their website at https://sociam.org/.]