Promoting and sustaining accountability in artificial intelligence applications
Please note this event is only open to staff and students of LSE.
Technology has been the catalyst for major revolutions societies have gone through, and each new revolution brings social challenges that governments must address. In turn, regulation acts as a form of feedback that directs how the breakthrough technology of the time will have to be adapted.
We are delighted that Leonardo has kindly reschulded this event following its cancellation last month.
Currently, the most pressing technology revolution is being powered by social media, big data, and artificial intelligence (AI). Though this revolution has been taking place for over a decade now, recent years have seen an astounding increase in the pace with which these applications are being developed and deployed. Not surprisingly, regulatory agencies around the world have been unable to cope with this speed and have just recently started to move from a data-centred to an AI-centred concern. More importantly, governments are still beginning to mature their understanding of AI applications in general, let alone discuss AI ethics and how to promote and sustain accountability in AI applications.
In turn, companies that use AI in their applications have also begun to display some public level of awareness, even if often vague and not substantiated by concrete actions.
In this talk, Dr Leonardo Bezerra will briefly overview efforts and challenges regarding AI accountability and how major AI players are addressing it. The goal of the talk is to stir future project collaborations from a multidisciplinary perspective.
Please note this event is only open to staff and students of LSE.
About the speaker:
Dr Leonardo Bezerra joined the University of Stirling as a Lecturer in Artificial Intelligence (AI)/Data Science in 2023, after having been a Lecturer in Brazil for the past 7 years. He received his Ph.D. degree from Université Libre de Bruxelles (Belgium) in 2016, having defended a thesis on the automated design of multi-objective evolutionary algorithms. His research experience spans from applied data science projects with public and private institutions to supervising theses on automated and deep machine learning. Recently, his research has concentrated on the social impact of AI applications, such as disinformation through social media recommendation algorithms and the disruptive potential of generative AI.