Data produced on a daily basis is growing both in volume and complexity, whilst the ability to analyse it is growing in power. Meanwhile, uses of data-enabled technologies promise benefits, from improving healthcare and treatment discovery, to better managing critical infrastructure such as transport and energy.
Through these benefits new applications can make a great contribution to human flourishing. But they also present significant choices and dilemmas. The Royal Society’s digital disruption programme explores the ways individuals, communities, and societies can best negotiate the transformations brought about by data and digital technologies.
Governance and practice
The Royal Society and the British Academy conducted a review on the needs of a data governance system adapted to the evolving data landscape, setting out principles and mechanisms in the report Data management and use: Governance in the 21st century.
We are now considering questions such as:
- How do traditional concepts such as ownership evolve in a data-enabled society?
- How do governance principles apply in practice internationally and across sectors?
The Royal Society is contributing to public and policy debates around these questions.
The Royal Society is working with a number of partners to explore concepts related to digital disruption, including techUK, the British Academy, the Alan Turing Institute and the Leverhulme Centre for Future of Intelligence.
On 20 September 2018, the Royal Society convened a workshop, in partnership with The Alan Turing Institute, the Leverhulme Centre for the Future of Intelligence and the Royal Academy of Engineering, to explore how principles for governance of data use might apply in practice for the automobile insurance sector. The automobile insurance sector sits at the intersection of the automobile sector and the insurance sector, which both stand to be transformed by advanced data capture and analysis. Additionally, these are consumer-facing sectors which involve granular, individual-level data. As a result, automobile insurance faces a broad set of challenges and opportunities, and how the sector responds could in turn influence how the automobile sector and the insurance sector more widely adapt to data’s potential. The workshop report, AI and data governance from principles to practice: auto insurance is available here.
On 3 October 2018 the Royal Society, the British Academy, and techUK convened a seminar which provided an opportunity to explore and understand the concept, value and limitations of the idea of ‘data ownership’. It considered the sound bases from which to consider and probe the concept of data ownership and discussed issues relating to the ability to exert rights and control over data use. The seminar report summarises the rich and diverse discussion at the meeting, and includes a set of papers which provide further explorations of data ownership, rights and controls. The seminar report, Data ownership rights and controls: reaching a common understanding, is available here.
The Society has also partnered with the federation of All European Academies (ALLEA), to foster pan-European debate on Flourishing in a data-enabled society (PDF).
Our report Progress and research in cybersecurity: supporting a resilient and trustworthy system for the UK (PDF) outlines how trust, resilience, research and translation of research into practical solutions are essential for creating robust, digitally-enabled society.
As data and digital technologies become ubiquitous, they pose questions for the future, such as:
- What roles could technologies themselves have in governance?
- How can technologies help manage some of the social and ethical tensions identified in our Data management and use report, such as creating value from data whilst preserving personal or sensitive information?
Our project on privacy enhancing technologies examines the social, ethical and legal context in which these technologies may operate, and the art of the possible in their application.
Our report Machine learning: the power and promise of computers that learn by example (PDF) showed that there is a high demand for people with advanced skills as well as a need for broader digital literacy.
To make the most of data and digital technologies, we are exploring further questions:
- How can we ensure that the UK has the skills it needs?
- How does the mobility of skilled workers play out in the emerging field of data science?
Our project Dynamics of Data Science is looking at the movement of talent and skills between universities, academia and industry to find out what is unique about data science as a discipline and how the flow of talent can be supported.