Can policymakers detoxify social media? Listen to HMI CI Jenny Davis, Dr Jennifer Hunt, and Yun Jiang discuss online hate, anti-social behaviour on digital platforms, and what policymakers can do about it.
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Information sharing has become a central concern for security agencies since 9/11. Drawing on ideas from the sociology of information and trust, this article adapts Ericson’s framework of rule-following to an Australian case study to frame the sharing/withholding of information between agencies as dependent on rules as a system of trust.
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This book analyses counterradicalisation policy in the US and the UK in the context of the concept of political community. Adapting citizenship theory and literature on state formation and drawing on interviews with senior counterterrorism policymakers, it provides a detailed history of these policy measures in both jurisdictions.
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This chapter is an overview of the use of algorithms in government decision-making, and particularly of the legal issues which arise as a result. The chapter moves from a description of the use of automation in government to a discussion of its effect on core rule of law values.
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In this project, we aim to link attention metrics and communication strategies to real world actions. In particular, we start by contrasting popularity and engagement of online social movements. We then link the measurements to real-world metrics of these activities, as measured by participant turnout, election outcome, legislative success, and others. Answers to these questions will empower content producers, consumers, and hosting platforms to channel attention in mutually beneficial, and socially responsible ways.
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This report analyses the literature exploring the meaning of the fairness principle in EU data protection law. Fairness is included in both Article 8(2) of the Charter of Fundamental Rights of the European Union (the Charter) and Article 5(1)(a) of the General Data Protection Regulation (GDPR). Despite these foundations however, the fairness principle has been largely unexplored and remains broadly undefined in the data protection framework, case law and guidance literature.
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One of the open questions in Bayesian epistemology is how to rationally learn from indicative conditionals (Douven, 2016). Eva et al. (2019) propose a strategy to resolve this question. They claim that their strategy provides a "uniquely rational response to any given learning scenario". We show that their updating strategy is neither very general nor always rational. Even worse, we generalize their strategy and show that it still fails. Bad news for the Bayesians.
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Present some of our work in developing practical solvers for the Partially Observable Markov Decision Process (POMDP) with applications in robotics. I enjoy the discussion in the seminar.
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This chapter, by Peggy Valcke, Damian Clifford, and Viltė Kristina Steponėnaitė, will appear in Constitutional Challenges in the Algorithmic Society, Giovanni De Gregorio et al. (eds) (Forthcoming CUP). It discusses legal-ethical challenges posed by the emergence of emotional artificial intelligence (AI) and its manipulative capabilities.
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Tiberio Caetano, Chief Scientist of the Gradient Institute, has been awarded the title of Honorary Professor by the ANU, in recognition of his research contributions to machine learning in general, and ethical machine learning in particular.
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