NOTE: Registration for the event is compulsory; please book to ensure a space
Be prepared to show your working! What can statistical science contribute to transparent, validated and explainable algorithms?
Increasingly, algorithms are shaping the way we see the world. They are being deployed to make decisions about sensitive parts of our lives, from our eligibility for a loan to the length of our sentence if we commit a serious crime. But how does algorithmic decision-making work and how do we know how decisions are made and if they are fair?
In this talk, Professor Spiegelhalter will argue that we should ideally be able to check (a) the basis for the algorithm, (b) its past performance, (c) the reasoning behind its current claim, (d) its uncertainty around its current claim and e) that these explanations should be open to different levels of expertise. These ideas will be illustrated by the Predict system for women choosing follow-up treatment after surgery for breast cancer, which has four levels of explanation of its conclusions.
The talk will be followed by a Q&A session and a complimentary drinks reception. For more information, including the agenda, please head to the Turing website.