Data-Driven Medicine

We live amid a stream of data about us generated by devices from sequencing machines to smartphones. Data are collected, sorted and used by individuals, companies, public services and governments. This data-saturated environment provides the basis for the development of what the Nuffield Trust describes as ‘ADA’ technologies – those involving Algorithms, Data or Artificial intelligence.

The SPACE (Stakeholder Perspectives on ethical challenges in the use of Artificial intelligence for Cognitive Evaluation) study focusses on social and ethical questions associated with the use of ADA technologies in healthcare and biomedical research. It focusses on the assessment of cognitive change and dementia. This is an area of pressing clinical need where data about behaviour and cognition from different sources might make a valuable contribution to understanding and treating illness, but which presents challenges associated with an older and potentially vulnerable population.

SPACE is an ‘empirical ethics’ study which uses a social scientific approach to identify the actual ethical issues which emerge in the process of developing new technologies, and make sense of the experiences and judgements of the individuals and groups involved. In the first stage, we will be working with researchers and technology developers to see what ethical challenges come up in the course of gathering data and developing AI approaches. The use of different types of data, including those that aren’t obviously health data, raises concerns in several areas. These include the challenges of ensuring valid informed consent in cases where people might have cognitive impairment, but also in terms of justice and working towards the fair distributed of benefits across society.

Alongside this work with scientists, the SPACE study will investigate how older people engage with the potential of digital health. We all generate data differently, and have different awareness, expectations and hopes related to ‘our’ data. For some, such as ‘quantified selfers’, using data from a range of sensors and devices has become a way of knowing themselves better. For many people however, data are invisible and incidental – the digital exhaust from everyday life. In this stage of the project, we will examine whether and how people can engage with the data produced by and about them, explore expectations and concerns about data use in health surveillance, monitoring and screening, and consider the potential of different ways of governing data use.