'Of Water Drops and Atomic Nuclei: Analogies and Pursuit Worthiness in Science'

This paper highlights a use of analogies in science that so far has received relatively little systematic discussion: providing reasons for pursuing a model or theory. Using the development of the liquid drop model as a test case, I critically assess two extant pursuit worthiness accounts: (i) that analogies justify pursuit by supporting plausibility arguments and (ii) that analogies can serve as a guide to potential theoretical unification. Neither of these fit the liquid drop model case. Instead, I develop an alternative account, based on the idea that analogies facilitate the transfer of a well-understood modelling strategy to a new domain.Leverhulme Trust Research Centre Grant (awarded to the Leverhulme Centre for the Future of Intelligence

Motivations and Risks of Machine Ethics

This paper surveys reasons for and against pursuing the field of machine ethics, understood as research aiming to build 'ethical machines.' We clarify the nature of this goal, why it is worth pursuing, and the risks involved in its pursuit. First, we survey and clarify some of the philosophical issues surrounding the concept of an 'ethical machine' and the aims of machine ethics. Second, we argue that while there are good prima facie reasons for pursuing machine ethics, including the potential to improve the ethical alignment of both humans and machines, there are also potential risks that must be considered. Third, we survey these potential risks and point to where research should be devoted to clarifying and managing potential risks. We conclude by making some recommendations about the questions that future work could address

Ethical considerations in the early detection of Alzheimer's disease using speech and AI

While recent studies indicate that AI could play an important role in detecting early signs of Alzheimer's disease in speech, this use of data from individuals with cognitive decline raises numerous ethical concerns. In this paper, we identify and explain concerns related to autonomy (including consent, depersonalization and disclosure), privacy and data protection (including the handling of personal content and medical information), welfare (including distress, discrimination and reliability), transparency (including the interpretability of language features and AI-based decision-making for developers and clinicians), and fairness (including bias and the distribution of benefits). Our aim is to not only raise awareness of the ethical concerns posed by the use of AI in speech-based Alzheimer's detection, but also identify ways in which these concerns might be addressed. To this end, we conclude with a list of suggestions that could be incorporated into ethical guidelines for researchers and clinicians working in this area

What is a subliminal technique? An ethical perspective for artificial intelligence systems

Concerns about threats to human autonomy feature prominently in the field of AI ethics. One aspect of this concerns relates to the use of AI systems for problematically manipulative influence. In response to this, the European Union’s draft AI Act (AIA) includes a prohibition on AI systems that use subliminal techniques that alter people’s behavior in ways that are reasonably likely to cause harm (Article 5(1)(a)). Critics have argued that the term ‘subliminal techniques’ is too narrow to capture the target cases of AI-based manipulation. We propose a definition of ‘subliminal techniques’ that (a) is grounded on a plausible interpretation of the legal text; (b) addresses all or most of the underlying ethical concerns motivating the prohibition; (c) is defensible from a scientific and philosophical perspective; and (d) does not over-reach in ways that impose excessive administrative and regulatory burdens. The definition is meant to provide guidance for design teams seeking to pursue responsible and ethically aligned AI innovation

Examining the technology-mediated cycles of injustice that contribute to digital ageism: Advancing the conceptualization of digital ageism: evidence and implications

Our work draws attention to digital ageism referring to the nexus of ageism (discrimination or bias related to age) that is mediated and perpetuated by artificial intelligent (AI) systems and technologies. Building on the World Health Organization's recently published policy brief entitled "Ageism in AI for Health"and our previous work about digital ageism, this paper aims to advance our current understanding and conceptualization of digital ageism in technology and AI systems broadly and beyond health alone. To do this, we will 1) elaborate on our conceptual model and the ageist technology-mediated cycles of injustice that can produce and reinforce digital ageism; 2) present empirical evidence of our descriptive analysis of seven commonly used facial image datasets to highlight data disparities for older adults which will provide real-world evidence that substantiates one of the elements in our ageist cycles of injustice; and 3) summarize results from our grey literature search of various grey literature databases including the AI ethics guidelines Global Inventory to identify guidance documents that address ageism in AI in research or technology development. This paper uniquely contributes conceptual and empirical evidence of digital ageism which will advance knowledge in the field and deepen our understanding of how ageism in AI is fostered by broader ageist cycles of injustice. Lastly, we will briefly provide future considerations to address digital ageism