Tuesday 13 May 2021
Are robots reasonable? Should the law discriminate between AI and human behaviour or is a radical rethink required?
Featuring the internationally renowned Professor Ryan Abbott, Professor of Law and Health Sciences at the University of Surrey School of Law, Adjunct Assistant Professor of Medicine at the David Geffen School of Medicine at UCLA and author of The Reasonable Robot: Artificial Intelligence and the Law.
Ryan is interviewed by Professor Jeannie Marie Paterson, co-director of CAIDE and through leader in the field of AI, Law and fairness.
Does our antiquated legal framework constrain inventive AI. Should AI be allowed to invent? Ryan argues that the law should not discriminate between AI and human behaviour and proposes a new legal principle aims to improve human well-being.
Presented by Centre for Artificial Intelligence and Digital Ethics (CAIDE) and the Australian Society for Computers and Law (AUSCL)
Australian Cyber Law Map Launch
Thursday 25 March 2021
One major challenge facing lawyers trying to engage with cyberlaw is a lack of understanding about what law already exists in Australia. An example of this ignorance is the map created by Bundesverband der Deutschen Industrie (BDI) and Deloitte showing that Australia has “no dedicated cyber security law”. The misunderstanding arises because, while Australia has no piece of legislation dedicated solely to cyber security, it has a range of laws with similar effect that operate in areas such as critical infrastructure protection, criminal law, telecommunications regulation, privacy, and consumer law.
This event was co-hosted by UNSW, the Allens Hub for Technology, Law & Innovation and The University of Melbourne through the Centre for AI and Digital Ethics. With kind support from: Cyber Security Cooperative Research Centre, IEEE SSIT Society on Social Implications of Technology, Sec Edu, Australian Society for Computers and the Law
Data science and the need for collective law and ethics
Thursday 3 December 2020
Dr Jake Goldenfein (MLS) and Dr Sebastian Benthall (NYU) present their research on ‘Data science and the need for collective law and ethics’ in this event, co-hosted by The Centre for AI and Digital Ethics and the HMI project from the Australian National University.
Efforts to regulate businesses doing large-scale data processing typically have their basis in liberalism. Privacy and data protection, property rights in data, and consumer protection models work to protect or scaffold the autonomous decision-making capacities of the individual. We argue that these forms of regulation, and the ethics behind them, are largely incompatible with the techno-political and techno-economic dimensions of data science. Over the course of the 20th century, computer science, cognitive psychology, operations research, statistics and other fields, have converged on an understanding of utility-maximizing agency that, combined with a neoliberal legal configuration, guarantees the supremacy of private corporations over individuals that would know and defend their own individual interests. In particular, platforms, as data-processing businesses within the digital economy, have inverted the relationship between individuals and the market, making the former public and the latter private.
On Fairness and Explainability in AI: Interactions between computer science and social science
4 September 2020
While topics such as fairness and explainability have become key talking points in artificial intelligence, these problems cannot be solved by computer scientists working in a vacuum. This talk will look at the link between computer science and areas of philosophy and social science for solving these problems.
Suresh Venkatasubramanian is a professor at the University of Utah. His background is in algorithms and computational geometry, as well as data mining and machine learning. His current research interests lie in algorithmic fairness, and more generally the impact of automated decision-making systems in society. Suresh was the John and Marva Warnock Assistant Professor at the U, and has received a CAREER award from the NSF for his work in the geometry of probability, as well as a test-of-time award at ICDE 2017 for his work in privacy. His research on algorithmic fairness has received press coverage across North America and Europe, including NPR’s Science Friday, NBC, and CNN, as well as in other media outlets. He is a member of the Computing Community Consortium Council of the CRA, a member of the board of the ACLU in Utah, and a member of New York City’s Failure to Appear Tool (FTA) Research Advisory Council, as well as the Research Advisory Council for the First Judicial District of Pennsylvania.