[From the Everyday AI Conference] Lloyds: Practical Application of Fairness

Principles for the development of fair machine learning systems are now widespread, however, what a development team actually has to do to get things moving is often still unclear. This session will dive into some of the practical considerations surrounding the application of fairness, to give attendees more understanding of what their companies might do to move the needle on this topic. The practical application of fairness is a key component in moving the conversation forward around how we can use trustworthy AI to reduce reputational & compliance risk. Key takeaways: - What is ML fairness and where does unfair bias enter into ML driven systems? - What are the headwinds that a development team faces in the application of fairness? - What approaches are available for structuring a fairness solution?