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Overview: Data and AI

Data and digital technologies are transforming the way we live, work and learn. 

The Royal Society’s Data Programme is developing policy and promoting debate that helps the UK safely and rapidly realise the growing benefits of data science and digital technologies. 

Data management and use

The amount of data produced on a daily basis is growing exponentially in volume and 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. Society and communities need to consider how to strike the right balance when it comes to the distribution of benefits and risks. They need to consider who reaps the most benefit from capturing, analysing and acting on different types of data, and who bears the most risk.

The Royal Society and the British Academy have conducted a review on the needs of a 21st century data governance system, setting out principles and mechanisms for good governance of data in the report Data management and use: Governance in the 21st century. We are following up with explorations of data governance in different sectors, and the status and role of Privacy Enhancing Technologies.

Machine learning and artificial intelligence

Machine learning is a form of artificial intelligence that allows computer systems to learn from examples, data, and experience. Through enabling computers to perform specific tasks intelligently, machine learning systems can carry out complex processes by learning from data, rather than following pre-programmed rules.
Recent years have seen exciting advances in machine learning, which have raised its capabilities across a range of applications. Many people now interact with systems based on machine learning every day, for example in image recognition systems, such as those used on social media; voice recognition systems, used by virtual personal assistants; and recommender systems, such as those used by online retailers. As the field develops further, machine learning promises to support potentially transformative advances in a range of areas, and the social and economic opportunities which follow are significant.

The Royal Society’s programme of work on machine learning has been investigating the potential of this technology over the next 5-10 years, and the barriers to realising that potential. The Society published a report with findings and recommendations on this subject, Machine learning: the power and promise of computers that learn by example. We are following up with investigations on AI and work, and the applications of AI for social good.

Trust in digital systems

Robust cybersecurity and protection of sensitive data is necessary to realise the benefits that data and digital technologies promise. Cybersecurity at most organisations is lagging behind the state of the art, and is not delivering the reliable protection we need. Attacks are increasing, and breaches cause substantial harm to individuals and organisations. This erodes trust, and along with it, the potential benefits digital systems are able to deliver.

The Royal Society’s 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. Our recent report Protecting privacy in practice: the current use, development and limits of Privacy Enhancing Technologies (PETs) in data analysis addresses in particular questions of trust in digital systems and demonstrates how PETs can help share and use data safely.

Open science and data science

Open data is data that is freely available to anyone to access, use and share. Open data affects the way data science and research in general is conducted and communicated, with huge potential to make science itself more open and efficient. Greater openness can help society address global challenges. It provides scientists and citizen scientists with greater opportunities to move science forward by creating further understanding and knowledge from the data as well as identifying errors.

The Royal Society’s report Science as an Open Enterprise explores how open data could lead to a new revolution in the way science is done, as wide-reaching and impactful as the revolution triggered by the first scientific journals. We are now carrying out work to look at the landscape and dynamics of data science research, and in particular the movement of researchers in industry, academia and the public sector.

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