Data–driven Responses to COVID–19: opportunities and limitations
With many activities moving online, there is growing pressure to implement a range of data–driven responses as “obvious” solutions to various COVID–19 concerns. These range from contact tracing to address the spread of the disease, through the use of AI in the dashboards that allocate health resources to identifying and supporting vulnerable individuals. This panel will review the opportunities and limitations of data–driven responses to COVID–19 from a legal, societal and technical perspective, highlighting the risks of exclusion and discrimination that can arise.
Seeta Peña Gangadharan is Assistant Professor in the Department of Media and Communications at LSE. She researches data and discrimination and will discuss what data–driven responses all too often leave out including institutional capacity issues and precariously positioned members of society.
Orla Lynskey (@lynskeyo) is an Associate Professor and joined LSE Law in September 2012. Orla conducts research in the fields of technology regulation and digital rights, with her primary focus being on EU data protection and privacy law. She will focus on the safeguards offered by data protection and human rights law for the use of data in pandemics and assess the potential and possible limitations of these safeguards.
Alison Powell is Assistant Professor in the Department of Media and Communications at LSE. She leads the JUST AI initiative in conjunction with the Ada Lovelace Institute and the AHRC. She will reflect on how AI that is ethical, works for the common good and is effectively governed and regulated can operate to address Covid–19 responses, and how issues of vulnerability, solidarity and risk have been reshaped through this crisis.
Edgar Whitley is Associate Professor (Reader) of Information Systems at LSE and is a data governance expert and will speak to the challenges of identifying and supporting vulnerable individuals through data sharing in government.
Susan Scott is Associate Professor (Reader) of Information Systems in the Department of Management.