by Kevin Kelly
I want my friends to treat me as an individual. To enable that kind of relationship I have to be open and transparent and share my life with my friends so they know enough about me to treat me personally. I want companies to treat me as an individual too, so I have be open, transparent, and sharing with them as well to enable them to be personal. I want my government to treat me as an individual, so I have to reveal personal information to it to be treated personally. There is a one-to-one correspondence between personalization and transparency. Greater personalization requires greater transparency. Absolute personalization (vanity) requires absolute transparency (no privacy). If I prefer to remain private and opaque to potential friends and institutions, then I must accept I will be treated generically, without regard to my specific particulars. I’ll be an average number.
Now imagine these choices pinned on a slider bar. On the left side of the slot is the pair personal/transparent. On the right side is the pair private/generic. The slider can slide to either side or anywhere in between. The slider is an important choice we have. Much to everyone’s surprise, though, when technology gives us a choice (and it is vital that it remain a choice), people tend to push the slider all the way over to the personal/transparent side. They’ll take transparent personalized sharing. No psychologist would have predicted that 20 years ago. If today’s social media has taught us anything about ourselves as a species, it is that the human impulse to share overwhelms the human impulse for privacy. This has surprised the experts. So far, at every juncture that offers a choice, we’ve tilted, on average, toward more sharing, more disclosure, more transparency. I would sum it up like this: Vanity trumps privacy.
For eons and eons humans have lived in tribes and clans where every act was open and visible and there were no secrets. Our minds evolved with constant co-monitoring. Evolutionarily speaking, coveillance is our natural state. I believe that, contrary to our modern suspicions, there won’t be a backlash against a circular world in which we constantly track each other because humans have lived like this for a million years, and—if truly equitable and symmetrical—it can feel comfortable.
That’s a big if. Obviously, the relation between me and Google, or between me and the government, is inherently not equitable or symmetrical. The very fact they have access to everyone’s lifestream, while I have access only to mine, means they have access to a qualitatively greater thing. But if some symmetry can be restored so that I can be part of holding their greater status to a greater accountability, and I benefit from their greater view, it might work. Put it this way: For sure cops will videotape citizens. That’s okay as long as citizens can videotape cops, and can get access to the cops’ videos, and share them to keep the more powerful accountable. That’s not the end of the story, but it’s how a transparent society has to start.
What about that state we used to call privacy? In a mutually transparent society, is there room for anonymity?
The internet makes true anonymity more possible today than ever before. At the same time the internet makes true anonymity in physical life much harder. For every step that masks us, we move two steps toward totally transparent unmasking. We have caller ID, but also caller ID block, and then caller ID–only filters. Coming up: biometric monitoring (iris + fingerprint + voice + face + heat rhythm) and little place to hide. A world where everything about a person can be found and archived is a world with no privacy. That’s why many smart people are eager to maintain the option of easy anonymity—as a refuge for the private.
However, in every system that I have experienced where anonymity becomes common, the system fails. Communities saturated with anonymity will either self-destruct or shift from the purely anonymous to the pseudo-anonymous, as in eBay, where you have a traceable identity behind a persistent invented nickname. There is the famous outlaw gang Anonymous, an ad hoc rotating band of totally anonymous volunteers. They are online vigilantes with fickle targets. They will take down ISIS militant Twitter accounts, or a credit card company that gets in their way. But while they continue to persist and make trouble, it is not clear whether their net contribution to society is positive or negative.
For the civilized world, anonymity is like a rare earth metal. In larger doses these heavy metals are some of the most toxic substances known to a life. They kill. Yet these elements are also a necessary ingredient in keeping a cell alive. But the amount needed for health is a mere hard-to-measure trace. Anonymity is the same. As a trace element in vanishingly small doses, it’s good, even essential for the system. Anonymity enables the occasional whistle-blower and can protect the persecuted fringe and political outcasts. But if anonymity is present in any significant quantity, it will poison the system. While anonymity can be used to protect heroes, it is far more commonly used as a way to escape responsibility. That’s why most of the brutal harassment on Twitter, Yik Yak, Reddit, and other sites is delivered anonymously. A lack of responsibility unleashes the worst in us.
There’s a dangerous idea that massive use of anonymity is a noble antidote to the prying state. This is like pumping up the level of heavy metals in your body to make it stronger. Rather, privacy can be gained only by trust, and trust requires persistent identity. In the end, the more trust the better, and the more responsibility the better. Like all trace elements, anonymity should never be eliminated completely, but it should be kept as close to zero as possible.
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• • •
Everything else in the realm of data is headed to infinity. Or at least astronomical quantities. The average bit effectively becomes anonymous, almost undetectable, when measured against the scale of planetary data. In fact, we are running out of prefixes to indicate how big this new realm is. Gigabytes are on your phone. Terabytes were once unimaginably enormous, yet today I have three terabytes sitting on my desk. The next level up is peta. Petabytes are the new normal for companies. Exabytes are the current planetary scale. We’ll probably reach zetta in a few years. Yotta is the last scientific term for which we have an official measure of magnitude. Bigger than yotta is blank. Until now, any more than a yotta was a fantasy not deserving an official name. But we’ll be flinging around yottabytes in two decades or so. For anything beyond yotta, I propose we use the single term “zillion”—a flexible notation to cover any and all new magnitudes at this scale.
Large quantities of something can transform the nature of those somethings. More is different. Computer scientist J. Storrs Hall writes: “If there is enough of something, it is possible, indeed not unusual, for it to have properties not exhibited at all in small, isolated examples. There is no case in our experience where a difference of a factor of a trillion doesn’t make a qualitative, as opposed to merely a quantitative, difference. A trillion is essentially the difference in weight between a dust mite, too small to see and too light to feel, and an elephant. It’s the difference between $50 and a year’s economic output for the entire human race. It’s the difference between the thickness of a business card and the distance from here to the moon.”
Call this difference zillionics.
A zillion neurons give you a smartness a million won’t. A zillion data points will give you insight that a mere hundred thousand don’t. A zillion chips connected to the internet create a pulsating, vibrating unity that 10 million chips can’t. A zillion hyperlinks will give you information and behavior you could never expect from a hundred thousand links. The social web runs in the land of zillionics. Artificial intelligence, robotics, and virtual realities all require mastery of zillionics. But the skills needed to manage zillionics are daunting.
The usual tools for managing big data don’t work very well in this territory. A statistical prediction technique such as a maximum likelihood estimation (MLE) breaks down because in the realm of zillionics the maximum likely estimate becomes improbable. Navigating zillions of bits, in real time, will require entire new fields of mathematics, completely new categories of software algorithms, and
radically innovative hardware. What wide-open opportunities!
The coming new arrangement of data at the magnitude of zillionics promises a new machine at the scale of the planet. The atoms of this vast machine are bits. Bits can be arranged into complicated structures just as atoms are arranged into molecules. By raising the level of complexity, we elevate bits from data to information to knowledge. The full power of data lies in the many ways it can be reordered, restructured, reused, reimagined, remixed. Bits want to be linked; the more relationships a bit of data can join, the more powerful it gets.
The challenge is that the bulk of usable information today has been arranged in forms that only humans understand. Inside a snapshot taken on your phone is a long string of 50 million bits that are arranged in a way that makes sense to a human eye. This book you are reading is about 700,000 bits ordered into the structure of English grammar. But we are at our limits. Humans can no longer touch, let alone process, zillions of bits. To exploit the full potential of the zillionbytes of data that we are harvesting and creating, we need to be able to arrange bits in ways that machines and artificial intelligences can understand. When self-tracking data can be cognified by machines, it will yield new, novel, and improved ways of seeing ourselves. In a few years, when AIs can understand movies, we’ll be able to repurpose the zillionbytes of that visual information in entirely new ways. AI will parse images like we parse an article, and so it will be able to easily reorder image elements in the way we reorder words and phrases when we write.
Entirely new industries have sprung up in the last two decades based on the idea of unbundling. The music industry was overturned by technological startups that enabled melodies to be unbundled from songs and songs unbundled from albums. Revolutionary iTunes sold single songs, not albums. Once distilled and extracted from their former mixture, musical elements could be reordered into new compounds, such as shareable playlists. Big general-interest newspapers were unbundled into classifieds (Craigslist), stock quotes (Yahoo!), gossip (BuzzFeed), restaurant reviews (Yelp), and stories (the web) that stood and grew on their own. These new elements can be rearranged—remixed—into new text compounds, such as news updates tweeted by your friend. The next step is to unbundle classifieds, stories, and updates into even more elemental particles that can be rearranged in unexpected and unimaginable ways. Sort of like smashing information into ever smaller subparticles that can be recombined into a new chemistry. Over the next 30 years, the great work will be parsing all the information we track and create—all the information of business, education, entertainment, science, sport, and social relations—into their most primeval elements. The scale of this undertaking requires massive cycles of cognition. Data scientists call this stage “machine readable” information, because it is AIs and not humans who will do this work in the zillions. When you hear a term like “big data,” this is what it is about.
Out of this new chemistry of information will arise thousands of new compounds and informational building materials. Ceaseless tracking is inevitable, but it is only the start.
We are on our way to manufacturing 54 billion sensors every year by 2020. Spread around the globe, embedded in our cars, draped over our bodies, and watching us at home and on public streets, this web of sensors will generate another 300 zillionbytes of data in the next decade. Each of those bits will in turn generate twice as many metabits. Tracked, parsed, and cognified by utilitarian AIs, this vast ocean of informational atoms can be molded into hundreds of new forms, novel products, and innovative services. We will be astounded at what is possible by a new level of tracking ourselves.
11
QUESTIONING
Much of what I believed about human nature, and the nature of knowledge, was upended by Wikipedia. Wikipedia is now famous, but when it began I and many others considered it impossible. It’s an online reference organized like an encyclopedia that unexpectedly allows anyone in the world to add to it, or change it, at any time, no permission needed. A 12-year-old in Jakarta could edit the entry for George Washington if she wanted to. I knew that the human propensity for mischief among the young and bored—many of whom lived online—would make an encyclopedia editable by anyone an impossibility. I also knew that even among the responsible contributors, the temptation to exaggerate and misremember was inescapable, adding to the impossibility of a reliable text. I knew from my own 20-year experience online that you could not rely on what you read by a random stranger, and I believed that an aggregation of random contributions would be a total mess. Even unedited web pages created by experts failed to impress me, so an entire encyclopedia written by unedited amateurs, not to mention ignoramuses, seemed destined to be junk.
Everything I knew about the structure of information convinced me that knowledge would not spontaneously emerge from data without a lot of energy and intelligence deliberately directed to transforming it. All the attempts at headless collective writing I had previously been involved with generated only forgettable trash. Why would anything online be any different?
So when the first incarnation of the online encyclopedia launched in 2000 (then called Nupedia), I gave it a look, and was not surprised that it never took off. While anyone could edit it, Nupedia required a laborious process of collaborative rewriting by other contributors that discouraged novice contributors. However, the founders of Nupedia created an easy-to-use wiki off to the side to facilitate working on the text, and much to everyone’s surprise that wiki became the main event. Anyone could edit as well as post without waiting on others. I expected even less from that effort, now renamed Wikipedia.
How wrong I was. The success of Wikipedia keeps surpassing my expectations. At last count in 2015 it sported more than 35 million articles in 288 languages. It is quoted by the U.S. Supreme Court, relied on by schoolkids worldwide, and used by every journalist and lifelong learner for a quick education on something new. Despite the flaws of human nature, it keeps getting better. Both the weaknesses and virtues of individuals are transformed into common wealth, with a minimum of rules. Wikipedia works because it turns out that, with the right tools, it is easier to restore damaged text (the revert function on Wikipedia) than to create damaged text (vandalism), and so the good enough article prospers and continues to slowly improve. With the right tools, it turns out the collaborative community can outpace the same number of ambitious individuals competing.
It has always been clear that collectives amplify power—that is what cities and civilizations are—but what’s been the big surprise for me is how minimal the tools and oversight that are needed. The bureaucracy of Wikipedia is relatively so small as to be invisible, although it has grown over its first decade. Yet the greatest surprise brought by Wikipedia is that we still don’t know how far this power can go. We haven’t seen the limits of wiki-ized intelligence. Can it make textbooks, music, and movies? What about law and political governance?
Before we say, “Impossible!” I say: Let’s see. I know all the reasons why law can never be written by know-nothing amateurs. But having already changed my mind once on this, I am slow to jump to conclusions again. A Wikipedia is impossible, but here it is. It is one of those things that is impossible in theory but possible in practice. Once you confront the fact that it works, you have to shift your expectation of what else there may be that is impossible in theory but might work in practice. To be honest, so far this open wiki model has been tried in a number of other publishing fields but has not been widely successful. Yet. Just as the first version of Wikipedia failed because the tools and processes were not right, collaborative textbooks, or law, or movies may take the invention of further new tools and methods.
I am not the only one who has had his mind changed about this. When you grow up having “always known” that such a thing as Wikipedia works, when it is obvious to you that open source software is better than polished proprietary goods, when you are certain that sharing your photos and other data yields more than safeguarding them—
then these assumptions will become a platform for a yet more radical embrace of the common wealth. What once seemed impossible is now taken for granted.
Wikipedia has changed my mind in other ways. I was a fairly steady individualist, an American with libertarian leanings, and the success of Wikipedia led me toward a new appreciation of social power. I am now much more interested in both the power of the collective and the new obligations stemming from individuals toward the collective. In addition to expanding civil rights, I want to expand civil duties. I am convinced that the full impact of Wikipedia is still subterranean and that its mind-changing force is working subconsciously on the global millennial generation, providing them with an existent proof of a beneficial hive mind, and an appreciation for believing in the impossible.
More important, Wikipedia has taught me to believe in the impossible more often. In the past several decades I’ve had to accept other ideas that I formerly thought were impossibilities but that later turned out to be good practical ideas. For instance, I had my doubts about the online flea market called eBay when I first encountered it in 1997. You want me to transfer thousands of dollars to a distant stranger trying to sell me a used car I’ve never seen? Everything I had been taught about human nature suggested this could not work. Yet today, strangers selling automobiles is the major profit center for the very successful eBay corporation.