Data analytics provides huge opportunities to improve private and public life, especially in the health sector (medical data analytics, henceforth MDA). Such a potentially highly positive impact is coupled to significant ethical challenges. The extensive use of increasingly more data (Big Data), the growing reliance on algorithms to analyse them and to reach decisions (machine learning), as well as the gradual reduction of human oversight over many automatic processes pose pressing issues of fairness, responsibility, and respect of human rights. These issues can be addressed successfully. However, if they are overlooked, underestimated or left unresolved, they risk hindering the innovation and the progress that MDA can bring to society at large and to future generations. Furthermore, as recent events involving the NHS care.data programme show, MDA projects may face a double bottleneck: ethical mistakes or misunderstandings may lead to social rejection and/or distorted legislation and policies, which in turn may cripple the acceptance and advancement of data science. Clearly, ethical analysis should be incorporated at all stages of any MDA project and since the beginning, in order to understand impact, anticipate risks of unethical consequences, suggest early interventions to avoid or mitigate them, foster resilience, reinforce ethical goals and outcomes, and ensure that ethical best practices are developed, implemented, and appreciated.
In order to pursue these goals, the project organised two internal meetings and two international research workshops. They (a) mapped the range of ethical issues that may challenge MDA projects; (b) outlined the agenda for the development of the conceptual framework needed to address them successfully; (c) identified potential MDA projects that may benchmark such a framework as pilot studies; and (d) delivered a landscape document in the form of a special issue of Philosophy & Technology.
The key question addressed was: what ethics is needed for MDA? The workshops addressed it question by exploring, within the MDA context, (1) the ethics of data, (2) the ethics of algorithms, and (3) the ethics of relevant practices (professional ethics and responsible innovation). These three lines of research constitute the space within which MDA projects need to be contextualised.
The workshops are hosted by the Oxford Internet institute, University of Oxford, Oxford, UK.
Image credits: Stuart Caie (cc By 2.o)
Oxford Internet Institute, University of Oxford