My thoughts on responsive science begin with questioning what we mean by ‘science’? Do we mean STEM – science, technology, engineering, mathematics? Do we limit the call for responsiveness to the natural- , life-, biosciences? Do these include the medical sciences or medicine?
How about the ‘arts’ and the ‘humanities’? While we have only just started the endeavor, the thought experiment of applying Responsive Science to other fields like geography, languages, economy or law – randomly chosen – may aid in developing the concept.
At this moment, instead of a hairsplitting exercise of precise categorization, I would like to argue that ‘science’ should cover here all academic disciplines. It is a matter of language, also. In some languages, other than English, there is a general term that does cover all knowledge-acquiring activities: wetenschap in Dutch, Wissenschaft in German, vetenskap in Swedish – I’m curious to hear more examples.
In our project, we have made a start in the realm of bioscience: our group focuses on the biosciences, and more in particular biological engineering, as the object of inquiry.
Technologies that alter ecosystems by definition impact upon an environment that is shared by many people, and scale of the intervention does not matter: whether at a small local scale, in a larger region or ultimately over vast areas and global ecosystems, the intervention cannot be beneficial and sustainable without mutual – meaning two-way - interaction between communities and researchers. Ideally and ultimately, communities must decide about the appropriateness and acceptability of an intervention in their environment.
However, the structure of the mutual interactions is highly determined by the governance and decision making framework of a given community. Sam, in his perspective, raises the point of democratic governance of science as knowledge production. That includes science policy and research agenda-setting. While a strong case can be made for democratic principles, the realization of truly democratic decision making at the implementation level remains challenging.
Zooming in on concrete technologies for ecosystems intervention, the clearest model may be that of an intervention that is and remains local, is self-limiting over time, and is reversible.
The Daisy Drive concept as currently being developed by our group is such a model, as it permits local and time limited application of a gene drive technology.
With that, it is not only the biological and ecological safer and more secure model, but it also facilitates community decision making, reciprocity and mutual interaction between individuals, community and researchers. Daisy Drives are the litmus test for Responsive Science.