To Err is Machine: Biases Failure and Fairness in AI

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Appleton Tower, LT 5

11 Crichton Street

Edinburgh

EH8 9AB

United Kingdom

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NB: Doors open at 5.30 pm

Fifth in a series of public discussion, the event will cover issues around machine biases, failures and fairness.

About the event

Everybody makes mistakes – and so do machines, sometimes. Despite their perceived capabilities and our trust in them, similarly to us, they are prone to biases. Machine biases result from current machine learning methods and the training data used. They may be brittle and fail in unexpected ways or be black boxes – their decision-making processes will be hard to understand and interpret.

Neither the public or software engineers and data science or the regulators are fully aware of the extent machine biases and failures.

But as these systems are becoming part of our daily lives, machine errors can have critical implication for recruitment, medical diagnosis, the safety of automated systems and political debate.

Come and listen to our panel discussing the consequences of the failures of AI systems and methods of developing, deploying, and utilising them.

In particular, we will be trying to establish how well we understand the decision-making processes of different AI systems? How to ensure public accountability and transparency of decisions made by AI? How to prevent algorithmic bias and other undesirable consequences? We will also wonder whether we should refrain from using AI systems when making certain decisions, like criminal sentencing?

Come and join the discussion.

This event is co-organised by EdIntelligence (Machine Learning Society), School of Informatics, University of Edinburgh and Edinburgh Futures Institute.

Panel

The event will be followed by a drinks reception/social.

NB This event might be streamed live, recorded and/or photographed.

Date and time

Location

Appleton Tower, LT 5

11 Crichton Street

Edinburgh

EH8 9AB

United Kingdom

View Map

Organiser School of Informatics, University of Edinburgh

Organiser of To Err is Machine: Biases Failure and Fairness in AI

Edinburgh’s School of Informatics is the largest academic centre of its kind in Europe and the UK’s most successful informatics research institution. We have consistently been a leader in the field since the 1960s, when our first Professor of Computer Science was appointed and the Department of Artificial Intelligence was founded. The Research Excellence Framework (REF) 2014 ranked us first in the UK for computer science and informatics. We produce more world leading and internationally excellent research in this field than any other UK university. We're also ranked 14th for Computer Science in the THES Rankings by Subject 2018. Our size and strength support unparalleled breadth in our taught courses, which are consistently ranked excellent in external assessments.

Our students rate us highly too. Members of staff are proud to have received EUSA Teaching Awards on the basis of student nominations and votes. We provide outstanding facilities. Computer laboratories are available to all Informatics students 24 hours a day. Our city centre premises include both teaching and research centres.

We lead the way in an exciting discipline that is central to a new enlightenment in scholarship and learning. Informatics is critical to the development of science, technology, culture and society. Our academics include Fellows of the Royal Society, the Royal Society of Edinburgh and the Royal Academy of Engineering. We boast recent winners of the most prestigious awards in the field, including the Herbrand Award, the Blaise Pascal Medal and the Yangtze River Scholar award.

Graduates from our programmes enjoy career success in a wide array of roles that shape our society, from developing the latest mobile technology to creating intelligent infrastructure. Many go on to work as project managers, researchers, software developers and consultants in the commercial sector (at firms such as Google, Amazon, Skyscanner or Adobe) or take up academic posts, often in Russell Group and US research universities such as MIT and Stanford. Some of our graduates have found success through start-up companies.

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