What Technology Wants (49 page)

Read What Technology Wants Online

Authors: Kevin Kelly

BOOK: What Technology Wants
3.41Mb size Format: txt, pdf, ePub
According to a calculation Hal Varian, an economist at Google, and I made, total worldwide information has been increasing at the rate of 66 percent per year for many decades. Compare that explosion to the rate of increase in even the most prevalent manufactured stuff—such as concrete or paper—which averages only 7 percent annually over decades. At 10 times faster than the growth of any other manufactured product on this planet, the rate of growth of information may even be faster than any biological growth at the same scale.
The quantity of scientific knowledge, as measured by the number of scientific papers published, has been doubling approximately every 15 years since 1900. If we measure simply the number of journals published, we find that they have been multiplying exponentially since the 1700s, when science began. Everything we manufacture produces an item and information about that item. Even when we create something that is information based to start with, it will generate yet more information about its own information. The long-term trend is simple: The information about and from a process will grow faster than the process itself. Thus, information will continue to grow faster than anything else we make.
The technium is fundamentally a system that feeds off the accumulation of this explosion of information and knowledge. Similarly, living organisms are also systems that organize the biological information flowing through them. We can read the technium's evolution as the deepening of the structure of information begun by natural evolution.
Nowhere is this increasing structure as visible as in science. Despite its own rhetoric, science is not built to increase either the “truthfulness” or the total volume of information. It is designed to increase the order and organization of knowledge we generate about the world. Science creates “tools”—techniques and methods—that manipulate information such that it can be tested, compared, recorded, recalled in an orderly fashion, and related to other knowledge. “Truth” is really only a measure of how well specific facts can be built upon, extended, and interconnected.
We casually talk about the “discovery of America” in 1492 or the “discovery of gorillas” in 1856 or the “discovery of vaccines” in 1796. Yet vaccines, gorillas, and America were not unknown before their “discovery.” Native peoples had been living in the Americas for 10,000 years before Columbus arrived, and they had explored the continent far better than any European ever could. Certain West African tribes were intimately familiar with the gorilla and many more primate species yet to be “discovered.” Dairy farmers in Europe and cow herders in Africa had long been aware of the protective inoculative effect that related diseases offered, although they did not have a name for it. The same argument can be made about whole libraries' worth of knowledge—herbal wisdom, traditional practices, spiritual insights—that are “discovered” by the educated, but only after having been long known by native and folk peoples. These supposed “discoveries” seem imperialistic and condescending—and often are. Yet there is one legitimate way in which we can claim that Columbus discovered America, and the French-American explorer Paul du Chaillu discovered gorillas, and Edward Jenner discovered vaccines. They “discovered” previously locally known knowledge by adding it to the growing pool of structured global knowledge. Nowadays we would call that accumulating of structured knowledge
science
. Until Du Chaillu's adventures in Gabon any knowledge about gorillas was extremely parochial; the local tribes' vast natural knowledge about these primates was not integrated into all that science knew about all other animals. Information about “gorillas” remained outside the structured known. In fact, until zoologists got their hands on Paul du Chaillu's specimens, gorillas were scientifically considered to be a mythical creature similar to Bigfoot, seen only by uneducated, gullible natives. Du Chaillu's “discovery” was actually science's discovery. The meager anatomical information contained in the killed animals was fitted into the vetted system of zoology. Once their existence was “known,” essential information about gorillas' behavior and natural history could be annexed. In the same way, local farmers' knowledge about how cowpox could inoculate against smallpox remained local knowledge and was not connected to the rest of what was known about medicine. The remedy therefore remained isolated. When Jenner “discovered” the effect, he took what was known locally and linked its effect to medical theory and all the little science knew of infection and germs. He did not so much “discover” vaccines as “link in” vaccines. Likewise America. Columbus's encounter put America on the map of the globe, linking it to the rest of the known world, integrating its own inherent body of knowledge into the slowly accumulating, unified body of verified knowledge. Columbus joined two large continents of knowledge into a growing consilient structure.
The reason science absorbs local knowledge and not the other way around is because science is a machine we have invented to connect information. It is built to integrate new knowledge with the web of the old. If a new insight is presented with too many “facts” that don't fit into what is already known, then the new knowledge is rejected until those facts can be explained. (This is an oversimplification of Thomas Kuhn's theory of the overthrow of scientific paradigms.) A new theory does not need to have every unexpected detail explained (and rarely does) but it must be woven to some satisfaction into the established order. Every strand of conjecture, assumption, observation is subject to scrutiny, testing, skepticism, and verification.
Unified knowledge is constructed by the technical mechanics of duplication, printing, postal networks, libraries, indexing, catalogs, citations, tagging, cross-referencing, bibliographies, keyword search, annotation, peer review, and hyperlinking. Each epistemic invention expands the web of verifiable facts and links one bit of knowledge to another. Knowledge is thus a network phenomenon, with each fact a node. We say knowledge increases not only when the number of facts increases, but also, and more so, when the number and strength of relationships between facts increases. It is that relatedness that gives knowledge its power. Our understanding of gorillas deepens and becomes more useful as their behavior is compared to, indexed with, aligned with, and related to the behavior of other primates. The structure of knowledge is expanded as gorillas' anatomy is related to other animals', as their evolution is integrated into the tree of life, as their ecology is connected to the other animals coevolving with them, as their existence is noted by many kinds of observers, until the facts of gorillahood are woven into the encyclopedia of knowledge in thousands of crisscrossing and self-checking directions. Each strand of enlightenment enhances not only the facts of gorillas, but also the strength of the whole cloth of human knowledge. The strength of those connections is what we call truth.
Today there remain many unconnected pools of knowledge. The unique wealth of traditional wisdom won by indigenous tribes in their long, intimate embrace of their natural environment is very difficult (if not impossible) to move out of their native context. Within their system, their sharp knowledge is tightly woven, but it is disconnected from the rest of what we collectively know. A lot of shamanic knowledge is similar. Currently science has no way to accept these strands of spiritual information and weave them into the current consilience, and so their truth remains “undiscovered.” Certain fringe sciences, such as ESP, are kept on the fringe because their findings, coherent in their own framework, don't fit into the larger pattern of the known. But in time, more facts are brought into this structure of information. More important, the methods whereby knowledge is structured are themselves evolving and being restructured.
The evolution of knowledge began with relatively simple arrangements of information. The most simple organization was the invention of the fact. Facts, in fact, were invented. Not by science but by the European legal system, in the 1500s. In court lawyers had to establish agreed-upon observations as evidence that could not shift later. Science adopted this useful innovation. Over time, the novel ways in which knowledge could be ordered increased. This complex apparatus for relating new information to old knowledge is what we call science.
The scientific method is not one uniform “method.” It is a collection of scores of techniques and processes that has evolved over centuries (and continues to evolve). Each method is one small step that incrementally increases the unity of knowledge in society. A few of the more seminal inventions in the scientific method include:
280 B.C.E.
Cataloged library with index
(at Alexandria), a way to search recorded information
1403
Collaborative encyclopedia,
a pooling of knowledge from more than one person
1590
Controlled experiment,
used by Francis Bacon, wherein one changes a single variable in a test
1665
Necessary repeatability,
Robert Boyle's idea that results of an experiment must be repeatable to be valid
1752
Peer-review-refereed journal,
adding a layer of confirmation and validation over shared knowledge
1885
Blinded, randomized design,
a way to reduce human bias; randomness as a new kind of information
1934
Falsifiable testability,
Karl Popper's notion that any valid experiment must have some testable way it can fail
1937
Controlled placebo,
a refinement in experiments to remove the effect of biased knowledge of the participant
1946
Computer simulations,
a new way of making a theory and generating data
1952
Double-blind experiment,
a further refinement to remove the effect of knowledge of the experimenter
1974
Meta-analysis,
a second-level analysis of all previous analysis in a given field
Together these landmark innovations create the modern practice of science. (I am ignoring various alternative claims of priority because for my purposes the exact dates don't matter.) A typical scientific discovery today will rely on facts and a falsifiable hypothesis; be tested in repeatable, controlled experiments, perhaps with placebos and double-blind controls; and be reported in a peer-reviewed journal and indexed in a library of related reports.
The scientific method, like science itself, is accumulated structure. New scientific instruments and tools add new ways to organize information. Recent methods build upon earlier techniques. The technium keeps adding connections among facts and more complex relations among ideas. As this short timeline makes clear, many of the key innovations of what we now think of as “the” scientific method are relatively recent. The classic double-blind experiment, for instance, in which neither the subject nor the tester is aware of what treatment is being given, was not invented until the 1950s. The placebo was not used in practice until the 1930s. It is hard to imagine science today without these methods.
This recency makes one wonder what other “essential” method in science will be invented next year. The nature of science is still in flux; the technium is rapidly discovering new ways to know. Given the acceleration of knowledge, the explosion of information, and the rate of progress, the nature of the scientific process is on a course to change more in the next 50 years than it has in the last 400 years. (A few probable additions: inclusion of negative results, computer proofs, triple-blind experiments, wiki journals.)
At the core of science's self-modification is technology. New tools enable new ways of discovery, different ways of structuring information. We call that organization knowledge. With technological innovations the structure of our knowledge evolves. The achievement of science is to discover new things; the evolution of science is to organize the discoveries in new ways. Even the organization of our tools themselves is a type of knowledge. Right now, with the advance of communication technology and computers, we have entered a new way of knowing. The thrust of the technium's trajectory is to further organize the avalanche of information and tools we are generating and to increase the structure of the made world.
EVOLVABILITY
Natural evolution is a way for an adaptive system—in this case, life—to search for new ways to survive. Life tries this or that size cell, round or long torso, slow or fast metabolism, without legs or with wings. Most forms it encounters live only a short time. But over aeons, the system of life settles on very stable forms—say, a spherical cell or DNA chromosome—that become stable platforms to experiment upon for more innovations. Evolution searches for designs that will keep the game of searching going. In this way, evolution wants to evolve.
The evolution of evolution? That sounds like a bad case of doubletalk. At first glance, this idea may seem oxymoronic (self-contradictory) or tautological (needlessly repetitive). But on close inspection, the “evolution of evolution” is no more tautological than, say, a “network of networks,” which is what the internet is.
Life kept evolving for four billion years because it discovered ways to increase its own evolvability. At the start, the space of possible life was very small. Room to change was limited. For instance, early bacteria could mutate their genes, change the length of their genome, and swap genes with one another. Several billion years of evolution later, cells could still mutate and swap genes, but they could also repeat entire modules (like repeating segments in an insect), and they could manage their own genome, turning select genes off or on. When evolution discovered sexual reproduction, entire genetic “words” in a cell's genome could be recombined in a mix-and-match method that achieved far faster improvement than merely altering genetic “letters” one at a time.

Other books

Linked by Barbara Huffert
Revenge by David Pilling
Nobody's Angel by Patricia Rice
Crazy Maybe by Justice, A. D.
Old-Fashioned Values by Emily Tilton
Red Light by T Jefferson Parker
Homeland by Barbara Hambly