In today’s world we have recently seen a compelling need for human oversight to ensure the responsible use of AI / Data science.
“This scary AI has learned how to pick out criminals by their faces”... In this session, Melanie Zhang will cover some examples of Machine Learning (ML) being used in both traditional actuarial and wider industries, and highlight a few common fallacies that can occur when interpreting the results. Actuaries have a central role to play in ensuring that the use of ML models is robust and any wider implications are well understood, as this webinar will address questions such as:
- Are 'black box' models truly black boxes?
- Why can bias occur even when we do not explicitly use sensitive input features?
- Why can data that we are not shown matter as much as data that we are shown?
- Why is more data not always better?
- When can accurate predictions lead to lower customer satisfaction?
|Melanie Zhang is Head of Property Innovation at AXIS Capital, having previously worked in actuarial pricing, reserving and business planning roles in the London insurance market since 2011. Melanie has recently completed her Master’s degree at UCL in Computational Statistics and Machine Learning. She is a member of the IFoA Data Science Member Interest Group.|
Dame Wendy Hall, DBE, FRS, FREng
Dame Wendy Hall, DBE, FRS, FREng is Regius Professor of Computer Science, Associate Vice President (International Engagement) and is an Executive Director of the Web Science Institute at the University of Southampton. She became a Dame Commander of the British Empire in the 2009 UK New Year's Honours list, and is a Fellow of the Royal Society and the Royal Academy of Engineering. Dame Wendy was co-Chair of the UK government’s AI Review, which was published in October 2017, and is the first Skills Champion for AI in the UK. In May 2020, she was appointed as Chair of the Ada Lovelace Institute.
Contact Events Team for more information.
0207 632 1498
Live webinar to commence at 13.00 BST
Nearest Public Transport