Deep Forgetting: Designing for Privacy in a World of Machine Learning
As the technology industry strives to build intelligence through data, what does it mean for a "smart" system to be not just technically reliable or theoretically accurate, but trustworthy in practice?
At a time where being first-to-market seems to outweigh ethical considerations, how can designers, researchers, and technologists incorporate goals such as privacy, security, and transparency into their work? What barriers do they face in designing such massively complex systems, what successful strategies are they employing today, and what work do we need for the future?
Underexposed brings together design and technology practitioners to have hard conversations at the intersection of human-centered thinking, ethics, and computing. This year the event will once again feature an invitation-only workshop, as well as an open evening session for members of the public to join in the conversation.