Many recent privacy proposals end up being wolves in sheep’s clothing. Sometimes this is because these proposals, on inspection, actually end up being privacy harming data collections systems dressed up as complex privacy enhancing systems; sometimes it’s because systems achieve their privacy aims in ways that box out competitors, and create a false privacy-vs-competition dynamic. This panel discussion will focus on traits common to these false-privacy systems, and features to look out for when evaluating privacy proposals. We’ll focus on reoccurring false trade-offs in this space, including: data vs privacy (systems that claim to improve privacy through additional data collection) and competition vs privacy (e.g., monopolist proposed systems that would harm smaller competitors). Presenters will aim to discuss systems past, current and proposed. Finally, panellists will discuss true privacy preserving alternatives, and how online privacy can be improved without harming users or competition:
• What are traits common to false-privacy systems and what features should be looked out for when evaluating proposals?
• What are the recurring false trade-offs in the space?
• Which systems – past, present and future – might be discussed as relevant?
• What are the true privacy preserving alternatives?
