Artificial Intelligence

Teaching machines to play fair

Machine learning is increasingly used to make decisions about people’s lives, such as whether to give someone a loan or whether to interview someone for a job. This brings with it the risk of discrimination, particularly if the data used for training the machines contains bias.

One strategy for ensuring such systems are fair is to modify the training data they learn from. Such approaches have been successful empirically, but typically lack strong theoretical fairness guarantees.

Driving straight toward a cliff?: preliminary thoughts on artificial intelligence, AI risks and related regulatory issues

Artificial Intelligence (AI) is once again bubbling up through public consciousness. After the false dawns of the Fifties and the Eighties, the very real possibility of Artificial General Intelligence (AGI) at the level of human capabilities being delivered means we are now confronted with the question of whether AI will be Prometheus’ Fire or Pandora’s Box.

Updated:  10 August 2017/Responsible Officer:  Director, RegNet/Page Contact:  Director, RegNet