Fairness, trust and transparency are qualities we usually associate with organisations or individuals. Today, these attributes might also apply to algorithms. As machine learning systems become more complex and pervasive, Cambridge researchers believe it’s time for new thinking about new technology.
Many of us see our privacy as a basic right. But in the digital world of app-addiction, geolocation tracking and social oversharing, some may have cause to wonder if that right is steadily and sometimes willingly being eroded away.
The digital revolution is one of the great social transformations of our time. How can we make the most of it, and also minimise and manage its risks? Jon Crowcroft and John Thompson discuss the challenges as we commence a month-long focus on ‘digital society’.
David Vincent (CRASSH) discusses the nineteenth century theatrical sensation that inspired public debate about privacy.
What power can individuals have over their data when their every move online is being tracked? Researchers at the Cambridge Computer Laboratory are building new systems that shift the power back to individual users, and could make personal data faster to access and at much lower cost.
We live in an age of near-total surveillance. In a talk given earlier this week, Professor Jon Crowcroft argued that total surveillance of society is toxic, and that those who claim that ‘if you’ve got nothing to hide, you’ve got nothing to fear’ are helping perpetuate a massive power imbalance which is doing harm to society.
Private information would be much more secure if individuals moved away from cloud-based storage towards peer-to-peer systems, where data is stored in a variety of ways and across a variety of sites, argues a University of Cambridge researcher.
David Erdos discusses C-131/12 Google Spain, Google v Agencia Espanola de Protection de Datos (2014), the Court of Justice of the European Union’s long awaited “right to be forgotten” case which examined the rights of individuals mentioned in public domain material indexed on Google search.
Research shows that intimate personal attributes can be predicted with high levels of accuracy from ‘traces’ left by seemingly innocuous digital behaviour, in this case Facebook Likes. The study raises important questions about personalised marketing and online privacy.