When a technology first appears in the world, it is not understood: no one knows what to do with it.
In a review of the Biomark 96.96 Dynamic Array, a microfluidic chip made by Fluidigm, a startup in South San Francisco (see “Shoveling Water”), David Rotman, Technology Review’s editor, asks why such chips are not more widely used. The Fluidigm chip, which (considered purely as an artifact) is a very beautiful thing, “represents a decade of successive inventions,” Rotman writes, and such chips, in general, are “a fundamental breakthrough in how researchers can interact with the biological world.” Microfluidic chips “allow biologists and chemists to manipulate tiny amounts of fluid in a precise and highly automated way.” And yet these chips, which bear some resemblance to an electronic microprocessor, “with valves replacing transistors and channels replacing wires,” will not live up to the comparison to microelectronics until they have made the transition “from promising laboratory tool to widely used commercial technology.” Possible applications include a variety of diagnostic uses, but the technology still lacks what the software industry calls the “killer app.”
Rotman reviews the chip and Brian Arthur’s book The Nature of Technology: What It Is and How It Evolves, and like many contributors to our Reviews section, he uses the occasion to make a broader point about technology. Arthur, a former professor of economics and population studies at Stanford, wishes to propose a grand theory of technology, akin to the one for science that Thomas Kuhn set out in The Structure of Scientific Revolutions. What interests Rotman is Arthur’s explanation of why truly new technologies, like microfluidic chips, are so slow to be adopted.
Arthur makes a distinction between bodies of technology, or “domains,” such as electronics, photonics, and microfluidics, and their individual technologies. Domains emerge “piece by piece.” Technologies within domains may be adopted quickly, but only after those domains have been encountered first by users who are bewildered. What are these technologies? How are they used? What do they allow people to do that could not be done before, or at least not as efficiently? Always, new domains betray “missing pieces” that technologists must develop before useful applications can be successfully commercialized. All this, says Arthur, “normally takes decades. It is a very, very slow process.”
Arthur’s observation is consistent with a general principle sometimes called “Cringely’s Law,” after the pundit Robert X. Cringely, who proposed it. Cringely’s Law states that short-term adoption of new technologies never occurs as quickly as we expect, but their long-term impact is far greater than we realize.
One market-oriented way of thinking about the protracted adoption of new technologies is to understand that among the “missing pieces” of new domains are the modes of business that will sustain the constituent technologies. That is to say: the real economic value of new technologies is almost always imperfectly understood because the technologies’ markets do not yet exist.
At Red Herring, a magazine I edited during the dot-com boom, we were so conscious of this phenomenon we had a name for its effect: “the Rule of the Second-Mover Advantage.” (I last wrote about it in “The Rules of Innovation,” May 2005.) We meant that the first attempt to commercialize a technology almost never succeeds, but another organization will succeed where the original innovator failed. IBM, for example, first commercialized the personal computer, but Microsoft controlled the “platform” for its software and therefore benefited most. The best recent example, however, is in search. There were many search engines before Google–some of them, like AltaVista, possessing technology the equal of PageRank, Google’s algorithm for ranking the popularity of Web pages. But Google was first to see that the monetary value of search was in keyword advertising; that “missing bit” created the link economy and overturned media (see Briefing).
What will be the markets for microfluidics? Rotman offers a few guesses. Drug companies might use microfluidics to show how genes are expressed in cells: “In one experiment, cancer researchers are using one of Fluidigm’s chips to analyze prostate tumor cells, seeking patterns that would help them select the drugs that will most effectively combat the tumor.” Microfluidics could also make possible cheap, portable diagnostic devices for the poor and developing world, where treatable diseases often go undiagnosed (see “TR 10: Paper Diagnostics,” March/April 2009).
The modes of business that sustain a new technology influence its further development. Norbert Wiener, the founder of cybernetics, showed that this influence is self-amplifying and, eventually, destabilizing. To commercialize a technology is to sow the seeds of its dissolution. IBM’s mainframes were succeeded by Microsoft’s software, which has been succeeded by Google’s keywords, which will be succeeded by something else. Nothing lasts forever, or even for very long. But write and tell me what you think at firstname.lastname@example.org.
This new data poisoning tool lets artists fight back against generative AI
The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models.
The Biggest Questions: What is death?
New neuroscience is challenging our understanding of the dying process—bringing opportunities for the living.
Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist
An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work.
How to fix the internet
If we want online discourse to improve, we need to move beyond the big platforms.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.