Emerging biotechnologies: full report - Nuffield Council on Bioethics
Emerging biotechnologies: full report - Nuffield Council on Bioethics
Emerging biotechnologies: full report - Nuffield Council on Bioethics
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E m e r g i n g b i o t e c h n o l o g i e s<br />
Transformative potential<br />
Technical change and disruptive technologies<br />
3.22 The ways in which new technologies come to be adopted and, eventually, supplant previous<br />
technologies has been an important area of theoretical interest to social scientists and, in<br />
particular, ec<strong>on</strong>omists. A number of models have been proposed to explain technology choice<br />
behaviour by societies, entrepreneurs and c<strong>on</strong>sumers. 226 They offer different explanati<strong>on</strong>s of the<br />
phenomena of unevenness in technology change (particularly within industry), which tends to<br />
be characterised by relatively stable phases during which a dominant technology is in<br />
widespread use (and enjoys incremental improvement) and often destabilising transiti<strong>on</strong>s to<br />
new dominant technological forms. What are now c<strong>on</strong>venti<strong>on</strong>ally described as ‘disruptive<br />
technologies’, 227 are novel technologies that are not incrementally linked to existing<br />
technologies but that are capable of bringing novel products to market that are cheaper, simpler<br />
and more c<strong>on</strong>venient to use than the c<strong>on</strong>venti<strong>on</strong>al technologies, or that are capable of<br />
developing new markets that did not exist previously. 228 We are therefore c<strong>on</strong>cerned with two<br />
c<strong>on</strong>sequences of technological change (although this distincti<strong>on</strong> is not always clear-cut): first,<br />
the ability to perform functi<strong>on</strong>s that were already being performed by established technologies<br />
but radically more efficiently; sec<strong>on</strong>d, performing functi<strong>on</strong>s that were not possible at all before<br />
the appearance of the new technology.<br />
3.23 As shown by the fact that it took over a hundred years to introduce and develop steam engine –<br />
perhaps the epitome of a transformative technology – the benefits of transformative<br />
technologies may take some time to become established. Perhaps the clearest example of<br />
revoluti<strong>on</strong>ary technological change (novel technologies becoming pervasive in a short time) is<br />
semic<strong>on</strong>ductor-based technologies. 229 However, it may be a mistake to frame our expectati<strong>on</strong>s<br />
of the pace and linearity of biotechnology innovati<strong>on</strong>s by the experience of semic<strong>on</strong>ductors, and<br />
even less so our expectati<strong>on</strong>s of their measureable impact. 230 The gradient and c<strong>on</strong>tinuity of<br />
innovati<strong>on</strong> is important because it has implicati<strong>on</strong>s for policy and the profile of resource<br />
allocati<strong>on</strong> over time. 231<br />
226 Am<strong>on</strong>g the most well-known is the ‘rati<strong>on</strong>al choice’ model of neoclassical ec<strong>on</strong>omics, the ‘wave model’ associated with<br />
Joseph Schumpeter, evoluti<strong>on</strong>ary and Marxian models. A helpful survey is provided by Elster J (1983) Explaining technical<br />
change (Cambridge: Cambridge University Press and Universitetsforlaget).<br />
227 We c<strong>on</strong>sistently prefer the term ‘transformative’ to ‘disruptive’. This avoids any unhelpful negative c<strong>on</strong>notati<strong>on</strong> of the term<br />
‘disruptive’, but, more importantly, suggests the thoroughgoing way in which novel technologies may rec<strong>on</strong>figure a domain of<br />
dependent possibilities not limited to the ec<strong>on</strong>omic register.<br />
228 Christensen CM (1997) The innovator's dilemma: when new technologies cause great firms to fail (Cambridge,<br />
Massachusetts: Harvard Business School Press).<br />
229 Semic<strong>on</strong>ductor materials are the basis of transistors, diodes and all integrated circuits and – as such – modern computing.<br />
230 The increasing computati<strong>on</strong>al power of semic<strong>on</strong>ductor technologies is often described as c<strong>on</strong>forming to the famous ‘Moore’s<br />
law’, which predicts the exp<strong>on</strong>ential rise in the density of transistors that can be placed <strong>on</strong> an integrated circuit (doubling<br />
every two years). Nevertheless, it is not the performance of the technology that is relevant but its c<strong>on</strong>diti<strong>on</strong>s of innovati<strong>on</strong>.<br />
Paul David makes a related point about the complexity and timescale of ec<strong>on</strong>omic impacts of technology, reflecting <strong>on</strong> the<br />
quip, attributed to Robert Solow, that “We see computers everywhere but in the ec<strong>on</strong>omic statistics.”<br />
231 See: Hopkins MM, Martin PA, Nightingale P, Kraft A and Mahdi S (2007) The myth of the biotech revoluti<strong>on</strong>: an assessment<br />
of technological, clinical and organisati<strong>on</strong>al change Research Policy 36: 566-89. The authors c<strong>on</strong>clude: “It may well be better<br />
to allocate a greater proporti<strong>on</strong> of resources to other activities, which offer more immediate health gains (e.g., the better<br />
adopti<strong>on</strong> of existing ‘low tech’ technologies with a proven track record of safety and efficacy). Our analysis also undermines<br />
the idea that the biotech sector will play a key role in ec<strong>on</strong>omic growth or regi<strong>on</strong>al development through the rapid creati<strong>on</strong> of<br />
thousands of new, high-technology jobs.”<br />
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