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Final dates announced for Royal Society season of AI events

11 June 2018

The Royal Society, the UK’s national academy of sciences, has added five new dates as part of You and AI, a flagship series of events designed to be an open and robust conversation about the potential and pitfalls of advances in artificial intelligence and machine learning. You and AI is supported by artificial intelligence lab DeepMind.


Monday 11 June

The emerging theory of algorithmic fairness

Intelligent systems can overcome the limitations of human decision-making using a vast amount of data that make more accurate predictions and enable new services. However, this raises questions about how we make decisions, the influence of bias in decision-making, and how society can ensure key values – such as fairness – are built into AI systems.

Join leading thinker and Harvard computer scientist Cynthia Dwork as she explores how to make machines play fair. Cynthia is a pioneer of differential privacy, a strong privacy guarantee and a collection of methods that allow researchers to analyse large data sets containing sensitive personal information – such as medical and mortgage application records – while preserving the privacy of individuals’ personal information.

Cynthia Dwork says: “Computer algorithms that touch our lives in increasingly significant ways codify societal values. Machine learning algorithms imbibe problematic values by learning from historically biased training data.  A major challenge in modern AI is to even define, let alone achieve, algorithmic fairness when the ground truth of fair behaviour is so elusive. Private data analysis benefitted from a mathematically rigorous approach; fairness seems to be a harder – and no less urgent –  problem.”


Tuesday 17 July

What biases in machine learning mean for inequality

Whether it’s handing down judicial decisions in court or telling employers who to hire and fire, artificial intelligence is increasingly used in situations where decisions have an important personal or social impact. Computer scientists are increasingly concerned about biases in the data feeding this decision-making process, but what can be done about it?

Kate Crawford, a leading scholar of the social implications of artificial intelligence will be giving a talk on 17 July on what biases in our data sets mean for inequality. Kate’s recent work address data discrimination and AI, predictive analytics and due process, and algorithmic accountability.


Tuesday 11 September

The impact of AI on work

Artificial intelligence is enabling a new wave of automation, with 21st century technology performing tasks that could normally only be carried out by humans. Digital technologies and platforms are also changing the way work is organised and distributed, creating new frameworks that shape our working lives.

What are the implications of AI for employment, and how can society ensure that the benefits of this technology are shared broadly? On 11 September, join American economist and recipient of the Nobel Prize in Economics Joseph Stiglitz to find more about the socioeconomic effects and impact of AI on work.


Sunday 28 October (Manchester) & Tuesday 11 December (London)

Concerns and aspirations for AI

For the culmination of the season, You and AI will travel beyond the confines of the Royal Society for large-scale events at the Barbican in London and the Royal Exchange in Manchester. Hosted by Jim al-Khalili and Brian Cox, this will be a chance to put your questions on the concerns and aspirations about AI to the leading thinkers in the field. Further details about the events will be revealed later this year.


You and AI follows the Royal Society’s in-depth assessment of public views of machine learning (PDF) which found that just one in ten members of the UK public recognised the term machine learning, even though the technology – a form of artificial intelligence – is already part of our everyday lives.

The report highlighted a range of public opinions on machine learning, depending on how, where, and why the technology was being used. Given the potential of this technology to both transform and disrupt our lives, the Royal Society and other industry experts believe engagement between AI researchers and the broader public is critically important.

The series is a collaborative effort to help people understand what machine learning and AI are, how these technologies work and the ways they may affect our lives. You and AI is supported by artificial intelligence lab DeepMind.

The series launched on 30 April with a talk from British neuroscientist, artificial intelligence researcher and CEO of DeepMind, Demis Hassabis, who discussed the history, capabilities and frontiers of AI.

It was followed by a panel discussion on the applications of AI on 3 May, where leading experts from Microsoft, Apple and academia showcased the potential of the technology to revolutionise healthcare, science and robotics.

Professor Angela McLean FRS, chair of the Royal Society’s AI lectures steering group said: “The Royal Society’s research makes it clear that the UK public view artificial intelligence and machine learning with both optimism and caution. Many of us see the benefits of relieving pressures on health and social care, and we feel favourably about its potential in education and policing. At the same time, some are concerned about the impact of AI on employment and its ability to cause harm, for example by accidents caused by self-driving cars.

“Machine learning and artificial intelligence aren’t decades away – they are revolutionising our lives right here and right now. To ensure that the promise and potential of these rapidly evolving technologies are felt across society, we must inspire ongoing public debate.

“We can only harness the vast untapped potential of artificial intelligence and machine learning if we have the buy-in of the people it is meant to serve. The Royal Society encourages people from all walks in life to attend our series of lectures, where you will have the opportunity to enter an informed public debate on what we want machine learning to do, and how we can ensure it benefits all.”