Big Data, Small Talk: Lessons from the Ethical Practices of Interpersonal Communication for the Management of Biomedical Big Data. In: Mittelstadt BD, Floridi L, editors. The Ethics of Biomedical Big Data. Cham: Springer International Publishing; 2016. pp. 277-305. [DOI: 10.1007/978-3-319-33525-4_13]

Thinking about the idea of consent in data science genomics: How 'informed' is it?

In this paper we argue that 'informed' consent in Big Data genomic biobanking is frequently less than optimally informative. This is due to the particular features of genomic biobanking research which render it ethically problematic. We discuss these features together with details of consent models aimed to address them. Using insights from consent theory, we provide a detailed analysis of the essential components of informed consent which includes recommendations to improve consent performance. In addition, and using insights from philosophy of mind and language and psycholinguistics we support our analyses by identifying the nature and function of concepts (ideas) operational in human cognition and language together with an implicit coding/decoding model of human communication. We identify this model as the source of patients/participants poor understanding. We suggest an alternative, explicit model of human communication, namely, that of relevance-theoretic inference which obviates the limitations of the code model. We suggest practical strategies to assist health service professionals to ensure that the specific information they provide concerning the proposed treatment or research is used to inform participants' decision to consent. We do not prescribe a standard, formal approach to decision-making where boxes are ticked; rather, we aim to focus attention towards the sorts of considerations and questions that might usefully be borne in mind in any consent situation. We hope that our theorising will be of real practical benefit to nurses and midwives working on the clinical and research front-line of genomic science.