Machine learning and AI aren’t just about technology – it’s people that make the difference in developing AI systems that are cutting-edge, but also responsible and sustainable. Emma Beauxis (Senior Track Associate, Data-Driven Transformation track at Digital Society School) will be speaking at this conference.
AI & ETHICS TRACK – Making Classification Bias Transparent and Understandable
To develop fair and ethical AI, the errors must be scrutinized by all stakeholders: developers, managers, users, and the general public. At the moment, only technical experts are able to really investigate the AI errors and biases, because tools and methods are lacking for people with limited AI expertise. I want to present visualizations (and simple statistics) that enable the general public to better understand classification errors and biases.