This paper looks at philosophical questions that arise in the context of AI alignment. It defends three propositions. First, normative and technical aspects of the AI alignment problem are interrelated, creating space for productive engagement between people working in both domains. Second, it is important to be clear about the goal of alignment. There are significant differences between AI that aligns with instructions, intentions, revealed preferences, ideal preferences, interests and values. A principle-based approach to AI alignment, which combines these elements (...) in a systematic way, has considerable advantages in this context. Third, the central challenge for theorists is not to identify ‘true’ moral principles for AI; rather, it is to identify fair principles for alignment that receive reflective endorsement despite widespread variation in people’s moral beliefs. The final part of the paper explores three ways in which fair principles for AI alignment could potentially be identified. (shrink)

Effective altruism is a philosophy and a social movement that aims to revolutionise the way we do philanthropy. It encourages individuals to do as much good as possible, typically by contributing money to the best-performing aid and development organisations. Surprisingly, this approach has met with considerable resistance among activists and aid providers who argue that effective altruism is insensitive to justice insofar as it overlooks the value of equality, urgency and rights. They also hold that the movement suffers from methodological (...) bias, reaching mistaken conclusions about how best to act for that reason. Finally, concerns have been raised about the ability of effective altruism to achieve systemic change. This article weighs the force of each objection in turn, and looks at responses to the challenge they pose. (shrink)

This article offers an account of the information condition on morally valid consent in the context of sexual relations. The account is grounded in rights. It holds that a person has a sufficient amount of information to give morally valid consent if, and only if, she has all the information to which she has a claim-right. A person has a claim-right to a piece of information if, and only if, a. it concerns a deal-breaker for her; b. it does not (...) concern something that her partner has a strong interest in protecting from scrutiny, sufficient to generate a privilege-right; c.i. her partner is aware of the information to which her deal-breaker applies; or c.ii. her partner ought to be held responsible for the fact that he is not aware of the information to which her deal-breaker applies; and finally, d. she has not waived or forfeited her claim-right. Although we present this account in the context of sexual relations, we believe a virtue of the account is that it can be easily translated into other contexts. (shrink)

How much personal partiality do agent-centred prerogatives allow? If there are limits on what morality may demand of us, then how much does it permit? For a view Henry Shue has termed ‘yuppie ethics’, the answer to both questions is a great deal. It holds that rich people are morally permitted to spend large amounts of money on themselves, even when this means leaving those living in extreme poverty unaided. Against this view, I demonstrate that personal permissions are limited in (...) certain ways: their strength must be continuous with the reasons put forward to explain their presence inside morality to begin with. Typically, these reasons include non-alienation and the preservation of personal integrity. However, when personal costs do not result in alienation or violate integrity, they are things that morality can routinely demand of us. Yuppie ethics therefore runs afoul of what I call the ‘continuity constraint’. (shrink)

Xenophobia is one of the key drivers of marginalisation, discrimination, and conflict, yet many prominent machine learning fairness frameworks fail to comprehensively measure or mitigate the resulting xenophobic harms. Here we aim to bridge this conceptual gap and help facilitate safe and ethical design of artificial intelligence (AI) solutions. We ground our analysis of the impact of xenophobia by first identifying distinct types of xenophobic harms, and then applying this framework across a number of prominent AI application domains, reviewing the (...) potential interplay between AI and xenophobia on social media and recommendation systems, healthcare, immigration, employment, as well as biases in large pre-trained models. These help inform our recommendations towards an inclusive, xenophilic design of future AI systems. (shrink)