The ongoing explosion of interest in artificial intelligence is fueled in part by recently developed techniques in machine learning. Those techniques allow automated systems to process huge amounts of data, utilizing mathematical methods that depart from traditional statistical approaches, and resulting in impressive advancements in our ability to make predictions and uncover correlations across a host of interesting domains. But as is now widely discussed, the way that those systems arrive at their outputs is often opaque, even to the experts (...) who design and deploy them. Is it morally problematic to make use of opaque automated methods when making high-stakes decisions, like whether to issue a loan to an applicant, or whether to approve a parole request? Many scholars answer in the affirmative. However, there is no widely accepted explanation for why transparent systems are morally preferable to opaque systems. We argue that the use of automated decision-making systems sometimes violates duties of consideration that are owed by decision-makers to decision-subjects, duties that are both epistemic and practical in character. Violations of that kind generate a weighty consideration against the use of opaque decision systems. In the course of defending our approach, we show that it is able to address three major challenges sometimes leveled against attempts to defend the moral import of transparency in automated decision-making. (shrink)

Morality bears on what we should forget. Some aspects of our identity are meant to be forgotten and there is a distinctive harm that accompanies the permanence of some content about us, content that prompts a duty to forget. To make the case that forgetting is an integral part of our moral duties to others, the paper proceeds as follows. In §1, I make the case that forgetting is morally evaluable and I survey three kinds of forgetting: no-trace forgetting, archival (...) forgetting, and siloing. In §2, I turn to how we practice these forms of forgetting in our everyday lives and the goods these practices facilitate by drawing on examples ranging from the expunging of juvenile arrest records to the right to privacy. In §3, I turn to how my account can help us both recognize and address a heretofore neglected source of harm caused by technology and big data. In §4, I end by addressing the concern that we lack control over forgetting and thus can't be required to forget. I argue this challenge can be answered, but there’s a harder challenge that can’t. Forgetting is under threat. To address this challenge and preserve forgetting, we must change the world. (shrink)

Large Language Models (LLMs) like ChatGPT were trained on human conversation, but in the future they will also train us. As chatbots speak from our smartphones and customer service helplines, they will become a part of everyday life and a growing share of all the conversations we ever have. It’s hard to doubt this will have some effect on us. Here I explore a specific concern about the impact of artificial conversation on our capacity to deliberate and hold ourselves accountable (...) to reason – that is, to be autonomous, in Kant’s sense of the term. I develop ideas from psychologist Jean Piaget to show how chatbots are autonomy traps: their deference to our commands tempts us into venting authoritarian whims, ultimately weakening our own self-control. I argue that the Kantian tradition, including Piaget and sociologist Emile Durkheim, offers powerful conceptual resources for resisting this slide. But it will require us to do something that may seem bizarre: we will need to treat mindless chatbots as if they are autonomous persons too. (shrink)