I’ve been spending the last couple of days at a meeting about synthetic biology – The economic and social life of synthetic biology. This has been a hexalateral meeting involving the national academies of science and engineering of the UK, China and the USA. The last session was a panel discussion, in which I was invited to reflect on the lessons to be learnt for new emerging technologies like synthetic biology from the experience of nanotechnology. This is more or less what I said.
It’s quite clear from the many outstanding talks we’ve heard over the last couple of days that synthetic biology will be an important part of the future of the applied life sciences. I’ve been invited to reflect on the lessons that synbio and other emerging technologies might learn from the experience of my own field, nanotechnology. Putting aside the rueful reflection that, like synbio now, nanotechnology was the future once, I’d like to draw out three lessons.
1. Mind that metaphor
Metaphors in science are powerful and useful things, but they come with two dangers:
a. it’s possible to forget that they are metaphors, and to think they truly reflect reality,
b. and even if this is obvious to the scientists using the metaphors, the wider public may not appreciate the distinction.
Synthetic biology has been associated with some very powerful metaphors. There’s the idea of reducing biology to software; people talk about booting up cells with new operating systems. This metaphor underlies ideas like the cell chassis, interchangeable modules, expression operating systems. But it is only a metaphor; biology isn’t really digital and there is an inescabable physicality to the biological world. The molecules that carry information in biology – RNA and DNA – are physical objects embedded in a Brownian world, and it’s as physical objects that they interact with their environment.
Similar metaphors have surrounded nanotechnology, in slogans like “controlling the world atom by atom” and “software control of matter”. They were powerful tools in forming the field, but outside the field they’ve caused confusion. Some have believed these ideas are literally becoming true, notably the transhumanists and singularitarians who rather like the idea of a digital transcendence.
On the opposite side, people concerned about science and technology find plenty to fear in the idea. We’ll see this in synbio if ideas like biohacking get wider currency. Hackers have a certain glamour in technophile circles, but to the rest of the world they write computer viruses and send spam emails. And while the idea of reducing biotech to software engineering is attractive to techie types, don’t forget that the experience of most people of software is that it is buggy, unreliable, annoyingly difficult to use, and obsolete almost from the moment you buy it.
Finally, investors and venture capitalists believed, on the basis of this metaphor, that they’d get returns from nano start-ups on the same timescales that the lucky ones got from dot-com companies, forgetting that, even though you could design a marvellous nanowidget on a computer, you still had to get a chemical company to make it.
2. Blowing bubbles in the economy of promises
Emerging areas of technology all inhabit an economy of promises, in which funding for the now needs to be justified by extravagant claims for the future. These claims may be about the economic impact – “the trillion dollar market” – or on revolutions in fields such as sustainable energy and medicine. It’s essential to be able to make some argument about why research needs to be funded and it’s healthy that we make the effort to anticipate the impact of what we do, but there’s an inevitable tendency for those claimed benefits to inflate to bubble proportions.
The mechanisms by which this inflation takes place are well known. People do believe the metaphors; scientists need to get grants, the media demand big and unqualified claims to attract their attention. Even the process of considering the societal and ethical aspects of research, and of doing public engagement can have the effect of giving credence to the most speculative possible outcomes.
There’s a very familiar tension emerging about synthetic biology – is it a completely new thing, or an evolution of something that’s been going on for some time – i.e. industrial biotechnology? This exactly mirrors a tension within nanotechnology – the promise is sold on the grand vision and the big metaphors, but the achievements are largely based on the aspects of the technology with the most continuity with the past.
The trouble with all bubbles, of course, is that reality catches up on unfulfilled promises, and in this environment people are less forgiving of the reality of the hard constraints faced by any technology. If you overdo the promise, disillusionment will set in amongst funders, governments, investors and the public. This might discredit even the genuine achievements the technology will make possible. Maybe our constant focus on revolutionary innovation blinds us to the real achievements of incremental innovation – a better drug, a more efficient process for processing a biofuel, a new method of pest control, for example.
3. It’s not about risk, it’s about trust
The regulation of new technologies is focused on controlling risks, and it’s important that we try and identify and control those risks as the technology emerges. But there’s a danger in focusing on risk too much. When people talk about emerging technologies, by default it is to risk that conversation turns. But often, it isn’t really risk that is fundamentally worrying people, but trust. In the face of the inevitable uncertainties with new technologies, this makes complete sense. If you can’t be confident in identifying risks in advance, the question you naturally ask is whether the bodies and institutions that are controlling these technologies can be trusted. It must be a priority, then, that we think hard about how to build trust and trustworthy institutions. General principles like transparency and openness will certainly be helpful, but we have to ask whether it is realistic for these principles alone to be maintained in an environment demanding commercial returns from large scale industrial operations.