Arianna Manzini

This article investigates the prospect of aligning AI agents with human autonomy. We show that doing so is a challenge: while there is general agreement on the concept’s broad contours, its components can be specified in a number of conflicting ways, making it difficult to decide how an autonomy-enhancing agent should act. In response, we introduce three strategies for dealing with disagreements about interpretations of autonomy. Each offers a coherent approach that captures a different set of considerations, with its own strength and trade-offs. The liberal approach is committed to user integrity and promotes human autonomy by acting strictly on what a person says they want, without trying to change their mind. The capability-boosting approach is built around the idea of flourishing and promotes human autonomy by empowering the user to act on their goals. The meta-autonomy approach prioritizes choice by giving the user the kind of autonomy they want in relation to their interactions with an AI agent. By highlighting the multifaceted nature of human autonomy, this article contributes to recent efforts seeking to identify and operationalize targets of AI value alignment. It also illustrates the challenges and trade-offs that can arise not just between—but even within—the values selected as targets for alignment and offers strategies to navigate them.

As AI assistants become increasingly sophisticated and deeply integrated into our lives, questions of trust rise to the forefront. In this paper, we build on philosophical studies of trust to investigate when user trust in AI assistants is justified. By moving beyond a focus on the technical artefact in isolation, we consider the broader societal system in which AI assistants are developed and deployed. We conceptualise user trust in AI assistants as encompassing two main targets, namely AI assistants and their developers. We argue that – as AI assistants become more human like and exhibit increased agency – discerning when user trust is justified requires consideration not only of competence, on the part of AI assistants and their developers, but also alignment between the competing interests, values or incentives of AI assistants, developers and users. To help users understand if and when their trust in the competence and alignment of AI assistants and developers is justified, we propose a sociotechnical approach that requires evidence to be collected at three levels: AI assistant design, organisational practices and third-party governance. Taken together, these measures can help harness the transformative potential of AI assistants while also ensuring their operation is ethical and value aligned.

Much has been written about the need for trustworthy artificial intelligence (AI), but the underlying meaning of trust and trustworthiness can vary or be used in confusing ways. It is not always clear whether individuals are speaking of a technology’s trustworthiness, a developer’s trustworthiness, or simply of gaining the trust of users by any means. In sociotechnical circles, trustworthiness is often used as a proxy for ‘the good’, illustrating the moral heights to which technologies and developers ought to aspire, at times with a multitude of diverse requirements; or at other times, no specification at all. In philosophical circles, there is doubt that the concept of trust should be applied at all to technologies rather than their human creators. Nevertheless, people continue to intuitively reason about trust in technologies in their everyday language. This qualitative study employed an empirical ethics methodology to address how developers and users define and construct requirements for trust throughout development and use, through a series of interviews. We found that different accounts of trust (rational, affective, credentialist, norms based, relational) served as the basis for individual granting of trust in technologies and operators. Ultimately, the most significant requirement for user trust and assessment of trustworthiness was the accountability of AI developers for the outputs of AI systems, hinging on the identification of accountable moral agents and perceived value alignment between the user and developer’s interests.

Background: Since the 1990s, increasing research has been devoted to the identification of biomarkers for autism to help attain more objective diagnosis; enable early prediction of prognosis; and guide individualized intervention options. Early studies focused on the identification of genetic variants associated with autism, but more recently, research has expanded to investigate neurodevelopmental markers. While ethicists have extensively discussed issues around advances in autism genomics, much less ethical scrutiny has focused on research on early neurodevelopment and on the interventions being developed as a result. Objectives: We summarize the current state of the science on the identification of early markers for autism and its potential clinical applications, before providing an overview of the ethical issues arising from increasing understanding of children's neurodevelopment in very early life. Results: Advances in the understanding of brain and behavioral trajectories preceding later autism diagnosis raise ethical concerns around three themes: (a) New models for understanding autism; (b) Risks and benefits of early identification and intervention; and (c) Communication of early concerns to families. These ethical issues should be further investigated in research conducted in partnership with autistic people and their families. Conclusions: This paper highlights the need for ethical scrutiny of early neurodevelopmental research in autism. Scrutiny requires expertise and methods from the basic sciences and bioethics, as well as constructive collaborations among autistic people, their parents, and autism researchers to anticipate early interventions that serve the community's interests and accommodate the varied experiences and preferences of people on the spectrum and their families.

Context: The 1989 UN Convention on the Rights of the Child states that children have the right to be heard in all matters affecting them. The Convention inspired a surge in research that investigates young people's perspectives on health and wellness‐related concerns and that involves children as ‘co‐researchers'. Young people's advisory groups (YPAGs) are a widely used method to enable young people's involvement in all research stages, but there is a lack of academic literature to guide researchers on how to set up, run and evaluate the impact of such groups.Objective: In this paper, we provide a step‐by‐step model, grounded in our own experience of setting up and coordinating the Oxford Neuroscience, Ethics and Society Young People's Advisory Group (NeurOx YPAG). This group supports studies at the intersection of ethics, mental health and novel technologies. Our model covers the following stages: deciding on the fit for co‐production, recruiting participants, developing collective principles of work, running a meeting and evaluating impact.Results: We emphasize that throughout this process, researchers should take a critical stance by reflecting on whether a co‐production model fits their research scope and aims; ensuring (or aspiring to) representativeness within the group; valuing different kinds of expertise; and undertaking on‐going evaluations on the impact of the group on both the young people and the research.Conclusion: Adopting a critical and reflective attitude can increase researchers' capacity to engage youth in democratic and inclusive ways, and to produce research outputs that are aligned with the target audience's needs and priorities.