Paul Formosa’s research while affiliated with Macquarie University and other places

The proliferation of Artificial Intelligence (AI) systems exhibiting complex and seemingly agentive behaviours necessitates a critical philosophical examination of their agency, autonomy, and moral status. In this paper we undertake a systematic analysis of the differences between basic, autonomous, and moral agency in artificial systems. We argue that while current AI systems are highly sophisticated, they lack genuine agency and autonomy because: they operate within rigid boundaries of pre-programmed objectives rather than exhibiting true goal-directed behaviour within their environment; they cannot authentically shape their engagement with the world; and they lack the critical self-reflection and autonomy competencies required for full autonomy. Nonetheless, we do not rule out the possibility of future systems that could achieve a limited form of artificial moral agency without consciousness through hybrid approaches to ethical decision-making. This leads us to suggest, by appealing to the necessity of consciousness for moral patiency, that such non-conscious AMAs might represent a case that challenges traditional assumptions about the necessary connection between moral agency and moral patiency.

The rapid adoption of commercial Generative Artificial Intelligence (Gen AI) products raises important questions around the impact this technology will have on our communicative interactions. This paper provides an analysis of some of the potential implications that Artificial Intelligence-Mediated Communication (AI-MC) may have on epistemic trust in online communications, specifically on social media. We argue that AI-MC poses a risk to epistemic trust being diminished in online communications on both normative and descriptive grounds. Descriptively, AI-MC seems to (roughly) lower levels of epistemic trust. Normatively, we argue that this brings about the following dilemma. On the one hand, there are at least some instances where we should epistemically trust AI-MC less, and therefore the reduction in epistemic trust is justified in these instances. On the other hand, there are also instances where we epistemically trust AI-MC less, but this reduction in epistemic trust is not justified, resulting in discrimination and epistemic injustice in these instances. The difficulty in knowing which of these two groups any instance of AI-MC belongs to brings about the AI-MC dilemma: We must choose between maintaining normal levels of epistemic trust and risking epistemic gullibility when reduced trust is justified, or adopting generally reduced epistemic trust and risking epistemic injustice when such reduced trust is unjustified. Navigating this choice between problematic alternatives creates a significant challenge for social media as an epistemic environment.

Much of the philosophical discussion of video game ethics is dominated by the literature on the Gamer's Dilemma, which forces us to focus on the ethics of certain forms of extreme virtual content in video games, such as virtual murder or molestation. While a focus on the ethics of video game content is important, we argue that scrutinizing the ethics of video game systems is needed to properly capture the full range of ethical concerns raised by video games. Drawing on a distinction between intravirtual and extravirtual effects, we identify ethical issues with video game content and, by linking to the dark patterns literature, video game systems. To illustrate our view, we give examples of how a game can appear to have morally objectionable content without the game being, at least clearly, morally objectionable, and how a game can appear to be morally unobjectionable despite having morally objectionable systems.

This paper provides a philosophically informed and robust account of the global justice implications of Artificial Intelligence (AI). We first discuss some of the key theories of global justice, before justifying our focus on the Capabilities Approach as a useful framework for understanding the context-specific impacts of AI on low- to middle-income countries. We then highlight some of the harms and burdens facing low- to middle-income countries within the context of both AI use and the AI supply chain, by analyzing the extraction of materials, which includes mineral extraction and the environmental harms associated with it, and the extraction of labor, which includes unethical labor practices, low wages, and the trauma experienced by some AI workers. We then outline some of the potential harms and benefits that AI poses, how these are distributed, and what global justice implications this has for low- to middle-income countries. Finally, we articulate the global justice significance of AI by utilizing the Capabilities Approach. We argue that AI must be considered from a global justice perspective given that, globally, AI puts significant downward pressure on several elements of well-being thereby making it harder for people to achieve threshold levels of the central human capabilities needed for a life of dignity.

The increasing use of Generative AI raises many ethical, philosophical, and legal issues. A key issue here is uncertainties about how different degrees of Generative AI assistance in the production of text impacts assessments of the human authorship of that text. To explore this issue, we developed an experimental mixed methods survey study (N = 602) asking participants to reflect on a scenario of a human author receiving assistance to write a short novel as part of a 3 (high, medium, or low degrees of assistance) X 2 (human or AI assistant) factorial design. We found that, for a human author, the degree of assistance they receive matters for our assessments of their level of authorship, creatorship, and responsibility, but not what or who rendered that assistance, although it was more important to disclose human rather than AI assistance. However, in our assessments of the assisting agent, human assistants were viewed as warranting higher rates of authorship, creatorship, and responsibility, compared to AI assistants rendering the same level of support. These results help us to better understand emerging norms around collaborative human-AI generated text, with implications for other types of collaborative content creation.

Generative AI technologies have the potential to be socially and politically transformative. In this paper, we focus on exploring the potential impacts that Generative AI could have on the functioning of our democracies and the nature of citizenship. We do so by drawing on accounts of deliberative democracy and the deliberative virtues associated with it, as well as the reciprocal impacts that social media and Generative AI will have on each other and the broader information landscape. Drawing on this background theory, we outline some of the key positive and negative impacts that Generative AI is likely to have on democratic citizenship. The political significance of these impacts suggests the need for further regulation.