The advent of ChatGPT, and the subsequent rapid improvement in the performance of what has become known as Generative AI, has led to many pundits declaring that AI will revolutionize education, as well as work, in the future. In this paper, we argue that enthusiasm for the use of AI in tertiary education is misplaced. A proper understanding of the nature of the outputs of AI suggests that it would be profoundly misguided to replace human teachers with AI, while the history of automation in other settings suggests that it is naïve to think that AI can be developed to assist human teachers without replacing them. The dream that AI could teach students effectively neglects the importance of ‘learning how’ in order to ‘learn that’, that teachers are also role models, and the social nature of education. To the extent that students need to learn how to use AI, they should do so in specialized study skills units. Rather than creating a market for dodgy educational AI by lowering their ambitions about what they can offer, universities should invest in smaller class sizes and teachers who are passionate about their disciplines. To flourish in the future, just as much as they do today, societies will need people who have learned to think and not—or not just—intelligent machines.
Monday July 6, 2026 11:00am - 11:55am AEST Steele-3143 Staff House Rd, St Lucia QLD 4067, Australia
There has been a recent proliferation of “AI Agents”: systems or programs that can operate in an increasingly autonomous manner. These systems raise an important question: do improvements in the capabilities of autonomous systems change the requirements for how we hold such systems – or their operators or designers – responsible for their outputs? Responsibility can be fruitfully connected to explainability – having the ability to explain an outcome helps in determining who, or what, should be held responsible for that outcome.
My talk will highlight how increasingly agentic systems pose challenges for pre-existing criteria for explainability. Specifically, I will examine how the increasing agentic features of algorithmic systems complicates the explanatory picture, and how different accounts of artificial agency can help to clarify these added complexities. I will conclude by considering how we should better understand the role of explanation in relation to increasingly complex explanatory contexts involving AI agents.
Monday July 6, 2026 12:00pm - 12:55pm AEST Steele-3143 Staff House Rd, St Lucia QLD 4067, Australia
Reason-Responsiveness Theories of Moral Responsibility (RRT) posits that the control necessary for moral responsibility depends on an agent's sensitivity to reasons. However, Situationist experiments present evidence that situational factors, rather than reasons, predominantly shape behavior. This paper contends that RRT cannot adequately address these challenges. After critiquing two common yet failed defenses—namely, the rarity of situational influences and the view that situational factors qualify as reasons—I discuss about RRT's usage of the Aristotelian Ethical Method (AEM), which suffers from selective application and epistemic overconfidence in attributing reason-responsiveness. Moreover, even when reason-responsiveness is capable to be captured by non-ideal cognizer, it remains irrelevant to the causal explanation of actions in situationist scenarios as a modal property. Finally, RRT falls short of meeting the Authority Demand, as it provides no authoritatively normative reason by its failure to justify a moral fact of the grounding relation between reason-responsiveness and moral responsibility.
Monday July 6, 2026 2:00pm - 2:55pm AEST Steele-3143 Staff House Rd, St Lucia QLD 4067, Australia
Agricultural robots and artificial intelligence (AI) are increasingly promoted for their environmental virtues. In Australia, the idea that agriculture needs to be less environmentally destructive and attend to ongoing colonial harms, is increasingly expressed in terms of ‘caring for Country’. Although this concept draws on Indigenous ideas of kinship, it is being adopted by white agriculturalists seeking to be more environmentally attentive and sensitive to Indigenous justice issues. In this paper, we ask whether, and if so how, robots and AI can contribute to caring for Country. We examine issues that those who seek to be more sensitive to relationships with the environment and Indigenous justice must consider in the context of decisions about AI and robots. We argue that while not without promise in some respects, robots and AI seem likely to exacerbate the logics of settler-colonial agriculture in ways that call into question their capacity to contribute to an ethic of caring for Country.
Monday July 6, 2026 3:00pm - 3:55pm AEST Steele-3143 Staff House Rd, St Lucia QLD 4067, Australia
Why wouldn’t you eat a person? One simple answer for many of us is that cannibalism is morally wrong. Another, perhaps more honest answer, is that it would be gross. In this paper, I show how this disgust response can be rationally related to moral judgements and evaluation. Although disgust and moral judgement are clearly correlated, most modern handlings of disgust treat the truth (or some nearby sense of accuracy/applicability) or falsity of ‘it’s disgusting’ (at least in the sense that applies to food) as being conceptually and essentially unrelated to the truth of any moral evaluation. Any moral judgement that springs from our disgust, then, is simply mistaking a non-moral response for something more meaningful. This paper gives an alternative account. By looking at what aspects of food ‘that’s disgusting’ evaluates, I argue that evaluations of tastes and textures can involve moral – and morally relevant – evaluations.
Monday July 6, 2026 4:30pm - 5:25pm AEST Steele-3143 Staff House Rd, St Lucia QLD 4067, Australia
There are multiple vectors along which one can be more or less pessimistic about the prospects for human-AI friendship. I could be optimistic about the purely technological aspects of AI friends, believing that they will soon be able to do some non-trivial percentage of the things the AI companies claim they can already do. I could be optimistic about the affordances of these AI friends for human relationships and experiences. I could be optimistic about the implementation, or the regulation, of such AI. Here, I examine and taxonomize these possibilities.
I was born and raised in Northland, New Zealand, outside of Whangārei. My undergraduate education at the University of Otago resulted in an LLB and a BA(Hons) in Political Science and Philosophy. I then moved to Melbourne, Australia, where I completed... Read More →
Monday July 6, 2026 4:30pm - 5:25pm AEST Steele-206
Should university campuses be politically neutral? In this paper I focus mainly on whether professors can or should express political views in class. Its main contribution is to distinguish between absolutist arguments, often thought by proponents to apply universally to all institutions and contexts, and more nuanced context-dependent considerations. I argue that while there are lessons to be learned from each, the absolutist arguments fail. While this means that things are, and there may not be a one size fit all ideal prescription (Schliesser, 2024), the paper describes a plethora of considerations that should be considered when devising policies. The paper examines three absolutist arguments, one against neutrality and two in favor. The first is that neutrality is impossible, it is a myth that serves those in power, and therefore professors should not be neutral (Dea, n.d.; Giroux, 2020, p. 210) . The second is that when professors use their social status and role in classrooms to express their political opinions, it is an abuse of power. The third is that professors, when talking as professors, should talk only about their areas of expertise and research (Fish, 2008). When they express their political views, they are not doing so.
Monday July 6, 2026 8:30pm - 9:25pm AEST ONLINE ONLY
