Benjamin Lange

Sedlakova et al. (2025) argue that conversational AI (CAI) cannot satisfy the conditions of epistemic trust in therapeutic contexts. I accept their diagnosis but press a further question: given that patients will de facto treat CAI outputs as reasons, how should patients, clinicians, and designers calibrate their epistemic responses? I argue that even where epistemic trust is inappropriate, calibrated epistemic deference remains rational. On a total evidence view, CAI outputs function as defeasible contributory reasons whose weight is proportional to demonstrated reliability and context-sensitive. Against preemptionism, I show that preemptive CAI deference is distinctively objectionable in therapeutic contexts: it undermines precisely the epistemic capacities—self-knowledge, critical reflection, and reason-integration—that psychotherapy aims to develop. An open question is whether calibrated deference is dynamically stable given users' documented tendency to anthropomorphize CAI over extended interaction, which may cause deference to drift toward the quasi-trust that therapeutic contexts warrant resisting.

Mensch-KI Beziehungen nehmen in unserem Alltag eine immer zentralere Rolle ein: etwa in der Interaktion mit Chatbots, KI-Companions, digitalen Assistenten oder virtuellen Avataren. Dieses Kapitel untersucht, ob und inwiefern sich zwischen Menschen und KI-Systemen Beziehungen entwickeln können und welche ethische Relevanz solchen Beziehungen zukommt. Ziel ist es, Orientierungswissen für die ethische Bewertung zukünftiger Mensch-KI-Interaktionen bereitzustellen. Ausgehend von einer Systematisierung momentaner Mensch-KI-Interaktionen wird der Beziehungsbegriff konzeptuell geschärft und auf seine philosophisch normative Bedeutung hin analysiert. Es wird untersucht, ob KI-Systeme als genuine Beziehungspartner gelten können oder ob die dabei entstehenden Bindungen notwendigerweise asymmetrisch und einseitig bleiben. Ein zentrales Argument ist, dass die normative Debatte nach der Plausibilität von genuinen Mensch-KI Beziehungen im Gesamtkontext von unseren normativen Handlungsgründen betrachtet werden sollte. Anschließend werden drei Ansätze zur ethischen Gestaltung von Mensch-KI Beziehungen vorgestellt und auf ihre Anwendbarkeit hin erläutert.

When should we defer to AI outputs over human expert judgment? Drawing on recent work in social epistemology, I motivate the idea that some AI systems qualify as Artificial Epistemic Authorities (AEAs) due to their demonstrated reliability and epistemic superiority. I then introduce AI Preemptionism, the view that AEA outputs should replace rather than supplement a user’s independent epistemic reasons. I show that classic objections to preemptionism – such as uncritical deference, epistemic entrenchment, and unhinging epistemic bases – apply in amplified form to AEAs, given their opacity, self-reinforcing authority, and lack of epistemic failure markers. Against this, I develop a more promising alternative: a total evidence view of AI deference. According to this view, AEA outputs should function as contributory reasons rather than outright replacements for a user’s independent epistemic considerations. This approach has three key advantages: (i) it mitigates expertise atrophy by keeping human users engaged, (ii) it provides an epistemic case for meaningful human oversight and control, and (iii) it explains the justified mistrust of AI when reliability conditions are unmet. While demanding in practice, this account offers a principled way to determine when AI deference is justified, particularly in high-stakes contexts requiring rigorous reliability.

“AI Ethics”, “Digital Ethics” or “Corporate Digital Responsibility”—ethics in business, especially with the rise of Artificial Intelligence (AI), is now in vogue. But how, if at all, can ethicists meaningfully contribute to practical business challenges? I examine the value that resources from moral philosophy can bring to ethical issues in business, particularly the technology sector. I show that there is a specific need for sharpened ethical acumen in so-called “grey areas”, in which laws and regulation do not provide definite answers to the ethical challenges businesses face. I argue that ethicists can distinctively help businesses navigate grey areas by strengthening their ethical capabilities and functions, which concern an organization’s ethical awareness, deliberation, decision-making, and commitment. I conclude by discussing some practical examples of how ethicists can strengthen these capabilities.

I am grateful to James Cordeiro, Timothy Murphy, Heloise Robinson and Teresa Baron for their perceptive and stimulating comments on my article in this journal. 1 In what follows, I seek to respond to some of the main points raised in each commentary. Cordeiro examines the implications of various forms of ectogestation for the gestational versus moral parenthood debate by contrasting it with in vivo (natural) gestation. 2 His analysis considers the gestating mother’s and biological father’s parenthood claims in light of various outcomes and the burdens and harms ectogestation may impose on them and on the fetus and newborn. I think his analysis helps to illustrate that—even if gestation does not necessarily give rise to a non-instrumentally valuable good in the form of an intimate relationship—corresponding pro tanto claims to moral parenthood might be settled by appeal to harms of ectogestation itself or voluntaristic considerations. Murphy...

“Moral imagination” is the capacity to register that one’s perspective on a decision-making situation is limited, and to imagine alternative perspectives that reveal new considerations or approaches. We have developed a Moral Imagination approach that aims to drive a culture of responsible innovation, ethical awareness, deliberation, decision-making, and commitment in organizations developing new technologies. We here present a case study that illustrates one key aspect of our approach – the technomoral scenario – as we have applied it in our work with product and engineering teams. Technomoral scenarios are fictional narratives that raise ethical issues surrounding the interaction between emerging technologies and society. Through facilitated role-playing and discussion, participants are prompted to examine their own intentions, articulate justifications for actions, and consider the impact of decisions on various stakeholders. This process helps developers to re-envision their choices and responsibilities, ultimately contributing to a culture of responsible innovation.

With the rise and public accessibility of AI-enabled decision-support systems, individuals outsource increasingly more of their decisions, even those that carry ethical dimensions. Considering this trend, scholars have highlighted that uncritical deference to these systems would be problematic and consequently called for investigations of the impact of pertinent technology on humans’ ethical decision-making. To this end, this article conducts a systematic review of existing scholarship and derives an integrated framework that demonstrates how intelligent decision-support systems (IDSSs) shape humans’ ethical decision-making. In particular, we identify resulting consequences on an individual level (i.e., deliberation enhancement, motivation enhancement, autonomy enhancement and action enhancement) and on a societal level (i.e., moral deskilling, restricted moral progress and moral responsibility gaps). We carve out two distinct methods/operation types (i.e., processoriented and outcome-oriented navigation) that decision-support systems can deploy and postulate that these determine to what extent the previously stated consequences materialize. Overall, this study holds important theoretical and practical implications by establishing clarity in the conceptions, underlying mechanisms and (directions of) influences that can be expected when using particular IDSSs for ethical decisions.

An increasing number of regulations propose the notion of ‘AI audits’ as an enforcement mechanism for achieving transparency and accountability for artificial intelligence (AI) systems. Despite some converging norms around various forms of AI auditing, auditing for the purpose of compliance and assurance currently have little to no agreed upon practices, procedures, taxonomies, and standards. We propose the ‘criterion audit’ as an operationalizable compliance and assurance external audit framework. We model elements of this approach after financial auditing practices, and argue that AI audits should similarly provide assurance to their stakeholders about AI organizations’ ability to govern their algorithms in ways that mitigate harms and uphold human values. We discuss the necessary conditions for the criterion audit, and provide a procedural blueprint for performing an audit engagement in practice. We illustrate how this framework can be adapted to current regulations by deriving the criteria on which ‘bias audits’ for hiring algorithms can be performed, as required by the recently effective New York City Local Law 144 of 2021. We conclude by offering critical discussion on the benefits, inherent limitations, and implementation challenges of applying practices of the more mature financial auditing industry to AI auditing where robust guardrails against quality assurance issues are only starting to emerge. Our discussion as informed by experiences in performing these audits in practice highlights the critical role that an audit ecosystem plays in ensuring the effectiveness of such methodology.

Why do relationships of friendship and love support partiality, but not relationships of hatred or commitments of racism? Where does partiality end and why? I take the intuitive starting point that important cases of partiality are meaningful. I develop a view whereby meaning is understood in terms of transcending self-limitations in order to connect with things of external value. I then show how this view can be used to distinguish central cases of legitimate partiality from cases of illegitimate partiality and how it puts pressure on the traditional way of thinking about partiality.

Existing discussions of partiality have primarily examined special personal relationships between family, friends, or co-nationals. The negative analogue of such relationships – for example, the relationship of enmity – has, by contrast, been largely neglected. This chapter explores this adverse relation in more detail and considers the special reasons generated by it. We suggest that enmity can involve justified negative partiality, allowing members to give less consideration to each other’s interests. We then consider whether the negative partiality of enmity can be justified through projects or the value inherent in the relationship, following two influential views about the justification of positive partiality. We argue that both accounts of partiality can be conceptually extended to the negative analogue, but doing so brings into focus the problems with such accounts of the grounds of partiality.

We propose a ‘Moral Imagination’ methodology to facilitate a culture of responsible innovation for engineering and product teams in technology companies. Our approach has been operationalized over the past two years at Google, where we have conducted over 50 workshops with teams from across the organization. We argue that our approach is a crucial complement to existing formal and informal initiatives for fostering a culture of ethical awareness, deliberation, and decision-making in technology design such as company principles, ethics and privacy review procedures, and compliance controls. We characterize some distinctive benefits of our methodology for the technology sector in particular.

We argue for asymmetries between positive and negative partiality. Specifically, we defend four claims: i) there are forms of negative partiality that do not have positive counterparts; ii) the directionality of personal relationships has distinct effects on positive and negative partiality; iii) the extent of the interactions within a relationship affects positive and negative partiality differently; and iv) positive and negative partiality have different scope restrictions. We argue that these asymmetries point to a more fundamental moral principle, which we call Morality’s Harmonious Propensity. According to this principle, morality has a propensity toward preserving positive relationships and dissolving negative ones.

The institution of the family and its importance have recently received considerable attention from political theorists. Leading views maintain that the institution’s justification is grounded, at least in part, in the non-instrumental value of the parent-child relationship itself. Such views face the challenge of identifying a specific good in the parent-child relationship that can account for how adults acquire parental rights over a particular child—as opposed to general parental rights, which need not warrant a claim to parent one’s biological progeny. I develop a view that meets this challenge. This Project View identifies the pursuit of a parental project as a distinctive non-instrumentally valuable good that provides a justification for the family and whose pursuit is necessary and sufficient for the acquisition of parental rights. This view grounds moral parenthood in a normative relation as opposed to a biological one, supports polyadic forms of parenting, and provides plausible guidance in cases of assisted reproduction.

In this paper, we distinguish between different sorts of assessments of algorithmic systems, describe our process of assessing such systems for ethical risk, and share some key challenges and lessons for future algorithm assessments and audits. Given the distinctive nature and function of a third-party audit, and the uncertain and shifting regulatory landscape, we suggest that second-party assessments are currently the primary mechanisms for analyzing the social impacts of systems that incorporate artificial intelligence. We then discuss two kinds of as-sessments: an ethical risk assessment and a narrower, technical algo-rithmic bias assessment. We explain how the two assessments depend on each other, highlight the importance of situating the algorithm within its particular socio-technical context, and discuss a number of lessons and challenges for algorithm assessments and, potentially, for algorithm audits. The discussion builds on our team’s experience of advising and conducting ethical risk assessments for clients across dif-ferent industries in the last four years. Our main goal is to reflect on the key factors that are potentially ethically relevant in the use of algo-rithms, and draw lessons for the nascent algorithm assessment and audit industry, in the hope of helping all parties minimize the risk of harm from their use.

AI-supported methods for identifying and combating disinformation are progressing in their development and application. However, these methods face a litany of epistemic and ethical challenges. These include (1) robustly defining disinformation, (2) reliably classifying data according to this definition, and (3) navigating ethical risks in the deployment of countermeasures, which involve a mixture of harms and benefits. This paper seeks to expose and offer preliminary analysis of these challenges.

Partiality is the special concern that we display for ourselves and other people with whom we stand in some special personal relationship. It is a central theme in moral philosophy, both ancient and modern. Questions about the justification of partiality arise in the context of enquiry into several moral topics, including the good life and the role in it of our personal commitments; the demands of impartial morality, equality, and other moral ideals; and commonsense ideas about supererogation. This paper provides an overview of the debate on the ethics of partiality through the lens of the domains of permissible and required partiality. After outlining the conceptual space, I first discuss agent-centred moral options that concern permissions not to do what would be impartially optimal. I then focus on required partiality, which concerns associative duties that go beyond our general duties to others and require us to give special priority to people who are close to us. I discuss some notable features of associative duties and the two main objections that have been raised against them: the Voluntarist and the Distributive objections. I then turn to the justification of partiality, focusing on underivative approaches and reasons-based frameworks. I discuss the reductionism and non-reductionism debate: the question whether partiality is derivative or fundamental. I survey arguments for ‘the big three’, according to which partiality is justified by appeal to the special value of either projects, personal relationships, or individuals. I conclude by discussing four newly emerging areas in the debate: normative transitions of various personal relationships, relationships with AI, epistemic partiality, and negative partiality, which concerns the negative analogue of our positive personal relationships.

I argue that you can be permitted to discount the interests of your adversaries even though doing so would be impartially suboptimal. This means that, in addition to the kinds of moral options that the literature traditionally recognises, there exist what I call other-sacrificing options. I explore the idea that you cannot discount the interests of your adversaries as much as you can favour the interests of your intimates; if this is correct, then there is an asymmetry between negative partiality toward your adversaries and positive partiality toward your intimates.

I here settle a recent dispute between two rival theories in distributive ethics: Restricted Prioritarianism and the Competing Claims View. Both views mandate that the distribution of benefits and burdens between individuals should be justifiable to each affected party in a way that depends on the strength of each individual’s separately assessed claim to receive a benefit. However, they disagree about what elements constitute the strength of those individuals’ claims. According to restricted prioritarianism, the strength of a claim is determined in ‘prioritarian’ fashion by both what she stands to gain and her absolute level of well-being, while, according to the competing claims view, the strength of a claim is also partly determined by her level of well-being relative to others with conflicting interests. I argue that, suitably modified, the competing claims view is more plausible than restricted prioritarianism.