Innovations in biotechnology increasingly shape our societies and our planet. They open up novel avenues in societally important fields like medicine, agriculture, and the production of chemicals and materials. Innovation though is not a straight road towards societally preferred outcomes. It is important to innovate responsibly: towards ethical acceptability and societal desirability. The current avalanche of biological data impacts this ability to innovate responsibly. Biological data are fuel for innovations. And they open up human populations and ecosystems to new ways of relating to them, including new ways of usage and control.
The analyses in this dissertation pivot around biological data as a touchpoint: a place where the biological reality and our world of values and meaning increasingly meet. This makes that biodata can give rise to morally salient categories. Digital Twins are explored as a thought experiment. Such computer models that dynamically represent aspects of a person’s biology can impact seemingly solid categories, like health and disease. The tendency towards moral interpretations of biodata calls for epistemic modesty – the viewpoint that there is always more to know about a person or a biological system than the data can tell. This warrants special considerations concerning privacy in the case of human genomics.
Fair access to biodata is a precondition to innovate. The inherent tendency towards exclusive data thus needs to be taken into account in a responsible innovation approach. The biological realities that underpin the biodata should be taken into account. And societally preferred values should be included in the process. Twin Commons – digitalized biological resources that are managed via collective self-regulation – are proposed as a framework to analyze these aspects.
Resulting dissertation
Volume 20 in the Simon Stevin series