The following is from the second issue of BioCoder, the quarterly newsletter for synthetic biologists, DIY biologists, neurobiologists, and more. Download your free copy today.
Within DIYbio, one cannot escape the hacking metaphor. The metaphor is ubiquitous and, to a point, useful. The term connotes both productive play with an existing technology aimed at improvement and, at the same time, play with sinister undertones. In this sense, hacking captures the promise and pitfalls of the dual uses any mature technology might be put to, whether that technology is as dramatic as nuclear power/weapons or as mundane as a free/premium software license. But every metaphor has its limits. Pushed too far, metaphors break down, and instead of illuminating, they obscure. Which brings me to ask: how far can the hacking metaphor be pushed within DIYbio—at least the part of DIYbio falling in line with synthetic biology?
Nowhere has the hacking metaphor been taken as literally as Andrew Hessel, Marc Goodman, and Steven Kotler took it in the 2012 Atlantic article, “Hacking the President’s DNA.” Hessel, Goodman, and Kotler imagine a world in which biology is a mature technology and maps one-to-one with computer programming. A world where novices can create human viruses and infect individuals with them in just the same way the unskilled can infect computers with malware. They craft a dramatic narrative around this metaphor by imagining the president of the United States as the target of sinister biohackers. The authors justify the premise of their article by arguing that the technology to make the scenario plausible is accelerating at an exponential rate and that it will only be a few short years before it is mature and ubiquitous. Therefore, better to prepare now than suffer tomorrow.
But is this the case? Is biology a few years away from the scenario outlined in The Atlantic? Two years ago, I attended a symposium on the current state and future of synthetic biology. It was the usual mix of technical talks and hallway conversations, but a question asked in the plenary roundtable stood out. During the Q&A, a young undergraduate asked a synthetic biologist the following question:
Undergrad: At Google, an entry-level job requires a BA, but in synthetic biology, an entry-level job requires a postdoc. Should this be rethought?
Biologist: Have you looked into DIYbio?
The undergrad brushed off the biologist’s response as beside the point, and the testy exchange ended shortly thereafter with the biologist pointing out that there was much basic research to be done in creating tools for the commons. But the undergrad’s question remains hanging. What kind of training counts here? There is an established discourse holding that synthetic biology—and, by extension, much of DIYbio—is analogous to computer science, but the implication of the student’s question and the biologist’s deflection argue for a different answer. The question posed to the biologist has two parts, both of which shed light on the scenario envisioned by Hessel, Goodman, and Kotler: a) why must so much synthetic biology be done in vivo or in vitro, not in silico, thus making necessary a long and arduous course of laboratory training? and b) why doesn’t the work translate directly to the in-vivo world outside the laboratory and thus bring about an industry comparable to the software industry?
In answering an earlier question posed during the roundtable, the biologist picked up on the tool comment when he said there was basic work in metrology to be done in synthetic biology before the academic work could be readily translated into the commercial realm. This has been true in almost all theoretical fields that have been translated into commercial ventures. The fact that synthetic biology is still coming to terms with metrology means that it has many years of difficult laboratory work ahead and that the scenario envisioned by Hessel, Goodman, and Kotler is more fear mongering than an accurate assessment of the near-future possibilities.
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