We live in the age of the algorithm. Increasingly, the decisions that affect our lives - whether we get a job or a loan, how much we pay for insurance - are being made by mathematical models. In theory, this should lead to greater fairness: everyone is judged according to the same rules, and bias is eliminated. But as Cathy O'Neil reveals in her new book, which she will talk about in this lecture, the opposite is true. The models being used today are opaque, unregulated, and incontestable, even when they're wrong. Most troubling, they reinforce discrimination, creating a toxic cocktail for democracy.
Tracing the arc of a person's life, Cathy O'Neil exposes the black box models that shape our future as individuals and as a society. These "weapons of math destruction" score teachers and students, sort CVs, grant or deny loans, evaluate workers, target voters and monitor our health. O'Neil calls on modellers to take more responsibility for their algorithms and on policy makers to regulate their use. But in the end, it's up to us to become more savvy about the models that govern our lives.
Cathy O'Neil (@mathbabedotorg) is a data scientist and author of the blog mathbabe.org. She earned a Ph.D. in mathematics from Harvard and taught at Barnard College before moving to the private sector, where she worked for the hedge fund D. E. Shaw. She then worked as a data scientist at various start-ups, building models that predict people's purchases and clicks. O'Neil started the Lede Program in Data Journalism at Columbia and is the author of Doing Data Science. She appears weekly on the Slate Money podcast. Her latest book is Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy.
Martin Anthony (@MartinHGAnthony) is Professor of Mathematics and Head of Department of Mathematics at LSE.
The Department of Mathematics (@LSEMaths) is internationally recognised for its teaching and research in the fields of discrete mathematics, game theory, financial mathematics and operations research.
SEDS is an interdisciplinary research unit established to foster the study of data science and new forms of data with a focus on its social, economic, and political aspects. SEDS aims to host, facilitate, and promote research in social and economic data science. SEDS is a collaboration between the Departments of Statistics, Methodology and Mathematics.
Twitter Hashtag for this event: #LSEmaths