Responsible Innovation in Data-Driven Biotechnology

Innovations in biotechnology increasingly shape our societies and our planet. The stream of innovations that could be witnessed in the past few decades opens up new ways to do agriculture, to provide healthcare and to produce compounds and materials, amongst many other things. Many of these innovations rely on biological data. The ability to extract a plethora of biodata vastly increased over the past few decades. These biodata provide deeper insights into the workings of biological systems, thus constituting a fertile ground for bio-inspired innovations. For example, population genomics data provides the basis for a personalized health care. Biodiversity data derived from ecosystems provides the basis for the identification of novel drugs, high value chemicals and materials. Biodata is increasingly crucial when aiming for a flourishing bio-economy and biomedicine. Biodata-based innovations thereby raise very substantial ethical questions. Pronounced cases like human genome editing, or the engineering of entire species via gene drive technologies, make clear that innovations need to go hand in hand with societal deliberation and an ethical accompaniment of technology development. The question though is how such responsible innovation can be organized. Extraction of biodata is done at a speed that surpasses Moore’s law. And the resulting biodata-based innovations are fast-paced. It is therefore highly needed to consider how a responsible guidance of innovation in biotechnology can be accomplished, in view of the biodata-avalanche. This question provides the entry point for this dissertation. Central to this analysis is the special ontological and epistemological position of biodata. Biodata resides at the interface between the biophysical world and the realm of human language and meaning. This makes biodata a central locus when pursuing a value-driven accompaniment of innovation in the field of biotechnology.