HMI held a workshop in December 2023 to celebrate our achievements since our formation in 2019, as well as looking into the future of the research initiative.
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This paper provides the first formalisation and empirical demonstration of a particular safety concern in reinforcement learning (RL)-based news and social media recommendation algorithms. This safety concern is what we call "user tampering" -- a phenomenon whereby an RL-based recommender system may manipulate a media user's opinions, preferences and beliefs via its recommendations as part of a policy to increase long-term user engagement.
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Pamela Robinson presented ‘Moral Uncertainty and Artificial Intelligence’ to Effective Altruism UQ (University of Queensland). Click through for more information.
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Pamela Robinson presented ‘Moral Disagreement and Artificial Intelligence’ at AIES'21. Click through for more information.
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Atoosa Kasirzadeh presented ‘Reasons, Values, Stakeholders: A Philosophical Framework for Explainable Artificial Intelligence’ at the ACM Conference Proceedings on Fairness, Accountability, Transparency (FAccT) 2021. Click through for more information.
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Rogier Creemers, Angela Zhang and John Lee presented ‘Chinese Tech and the Part State: Privacy, Profit and Power’ on May 26th 2021. Click through for more information.
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Emotional AI, Feminism and Human rights.
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On November 11 2020, the Women in AI Ethics™ Collective - Australia held their first Asia Pacific summit. The summit brought together women and allies from around the world to discuss the current state of diversity + ethics in AI and build meaningful action plans for progress through inspiring panel discussions, workshops, and lightning talks. Click through for more information.
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On December 12 2020, Atoosa Kasirzadeh and Andrew Smart will present their paper ‘A critique of the use of counterfactuals in ethical machine learning’ at the Virtual NeurIPS 2020 Workshop on Algorithmic Fairness through the Lens of Causality and Interpretability.
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This paper is about why we find it problematic to appeal to certain kinds of statistical or profiling evidence when making decisions about individuals. I argue for a novel solution: the problem has to do with the causal information carried by the evidence. We object to evidence that is merely accidental in that it does not carry appropriate causal information pertinent to the decision.
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In this In Conversation event, Dr Claire Benn joined Dr Jason Ketter to explore the sampling of ethical issues with which AI is infused. Dr Benn explains what is AI, whether we should be worried about, the importance of ethical design, and how this might call for us to alter how we understand our own morality. Watch here or click through for more information.
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