Date & time: Tuesday, 26 April 2016, 12:00 – 17:00
Venue: Silverstone room, Department of Media and Communications, 7th Floor, LSE Tower 2, Clements Inn, Strand, London WC2A 2AZ
During this invitation-only workshop researchers, civil society representatives, industry and policymakers considered questions of fairness in predictive analytics and ‘big data’ systems in a changing networked media environment. The goal of the workshop was to consider emerging trends and new research on ‘digital inequalities’, to explore the significance of media and communications data (e.g., network usage data, call data, social media data) in particular contexts of automation and prediction (e.g., alternative credit, security/public safety, retail), and to identify particular harms arising from discrimination and bias in ‘big data’ systems.
The invitation-only workshop was the third of a series of workshops being organised by the Media Policy Project as part of a grant for knowledge exchange as part of the Higher Education Innovation Funding (HEIF) project at LSE.
The workshop was held under the Chatham House rule. A summary is available here.
The following blogs linked to the event were published by the Media Policy Project:
Automation, correlation and causation: launching a policy discussion – by Tal Zarsky
Digital exclusion and the robot revolution – by Seeta Peña Gangadharan
Predictive policing and the automated suppression of dissent – by Lina Dencik
The economics of privacy – by Alessandro Acquisti
Digital inequalities in the aisles: the quantified individual – by Joseph Turow Algorithmic fairness: from social good to a mathematical framework – by Suresh Venkatasubramanian