Series of public Data Debates delivered in collaboration with the Alan Turing Institute
Data has become part of our everyday lives and we are increasingly getting used to dealing with consequences of our personal data being accessible to a myriad of different services, from banking to social media. Some uses of data, however, remain more complex and more difficult to understand for the majority of us, possibly nowhere more so than when it comes to our health. Will more data about us improve our healthcare in the future? Or does it compromise our privacy in a new way that we hardly understand?
As a part of the British Libraryâ€™s collaboration with the Alan Turing Institute we are organising a series of Data Debates over the coming months. In our next event on 12 June 2017, we are discussing the complex issue of data in healthcare.
Introducing this event, Angelo Napolano from the Alan Turing Institute writes:
Can we safeguard our privacy while using health data for better medical care?
It is clear that data-driven technology is transforming medical knowledge and practice.
Innovation is taking place on many levels, for example devices such as fitbits are helping to monitor heart rates, blood sugar levels and sleep cycles, and IBMâ€™s A.I. system, Watson, is giving scientists insight into how genes affect our health.
Data is also being analysed to generate new medical findings, for example scientists at The Alan Turing Institute, are collaborating with the Cystic Fibrosis Trust, to investigate how to apply machine learning techniques to their data to help improve healthcare for people living with the life-limiting condition.
However, despite the benefits for medical research, incidents like the care data breach and subsequent fears around protecting personal information mean there is legitimate public concern around how to share health data safely.
In a special Data Debate event, we will ask a panel of experts:
- How can we balance the potential benefits of using personal data for healthcare research, with the ethical dilemmas they provoke?
- Should we allow companies to use medical data for technological developments and interventions that may improve our lifestyles, or does this contravene our privacy rights?
- How can we ensure a future in which health care data is used in a way which ensures the public trust?
- Can we safeguard our privacy and regulate the use of health data while making medical practice and discovery more effective through technology developments?
Luciano Floridi, Turing Faculty Fellow and Professor of Philosophy and Ethics of Information at the Oxford Internet Institute. His research areas are the philosophy of Information, information and computer ethics, and the philosophy of technology.
Sabina Leonelli, Co-Director of the Exeter Centre for the Study of the Life Sciences (Egenis), where she leads the Data Studies research strand. Currently, Sabina focuses on the philosophy, history and sociology of data-intensive science, especially the research processes, scientific outputs and social embedding of Open Science, Open Data and Big Data.
Natalie Banner, Policy Adviser at the Wellcome Trust. Her focus is on how to get the best use and value from health and genetic data while ensuring it is well protected, responsibly managed and ethically used, both in the UK and internationally.
The panel will be chaired by writer and broadcaster Timandra Harkness. Timandra presents BBC Radio 4 series, FutureProofing and has presented the documentaries, Data, Data Everywhere, Personality Politics & The Singularity. Her recent book Big Data: Does Size Matter? has been published by Bloomsbury Sigma in June 2016. She is Visiting Fellow in Big Data, Information Rights and Public Engagement within the Centre for Information Rights at the University of Winchester.
Data Debates are a collaboration between The Alan Turing Institute and The British Library, aiming to stimulate discussion on issues surrounding big data, its potential uses, and its implications for society.
You can book your place from: https://www.bl.uk/events/health-data-fit-or-failing