When making substituted judgments for incapacitated patients, surrogates often struggle to guess what the patient would want if they had capacity. Surrogates may also agonize over having the (sole) responsibility of making such a determination. To address such concerns, a Patient Preference Predictor (PPP) has been proposed that would use an algorithm to infer the treatment preferences of individual patients from population-level data about the known preferences of people with similar demographic characteristics. However, critics have suggested that even if such (...) a PPP were more accurate, on average, than human surrogates in identifying patient preferences, the proposed algorithm would nevertheless fail to respect the patient’s (former) autonomy since it draws on the ‘wrong’ kind of data: namely, data that are not specific to the individual patient and which therefore may not reflect their actual values, or their reasons for having the preferences they do. Taking such criticisms on board, we here propose a new approach: the Personalized Patient Preference Predictor (P4). The P4 is based on recent advances in machine learning, which allow technologies including large language models to be more cheaply and efficiently ‘fine-tuned’ on person-specific data. The P4, unlike the PPP, would be able to infer an individual patient’s preferences from material (e.g., prior treatment decisions) that is in fact specific to them. Thus, we argue, in addition to being potentially more accurate at the individual level than the previously proposed PPP, the predictions of a P4 would also more directly reflect each patient’s own reasons and values. In this article, we review recent discoveries in artificial intelligence research that suggest a P4 is technically feasible, and argue that, if it is developed and appropriately deployed, it should assuage some of the main autonomy-based concerns of critics of the original PPP. We then consider various objections to our proposal and offer some tentative replies. (shrink)

While organizations today make extensive use of complex algorithms, the notion of algorithmic accountability remains an elusive ideal due to the opacity and fluidity of algorithms. In this article, we develop a framework for managing algorithmic accountability that highlights three interrelated dimensions: reputational concerns, engagement strategies, and discourse principles. The framework clarifies that accountability processes for algorithms are driven by reputational concerns about the epistemic setup, opacity, and outcomes of algorithms; that the way in which organizations practically engage with emergent (...) expectations about algorithms may be manipulative, adaptive, or moral; and that when accountability relationships are heavily burdened by the opacity and fluidity of complex algorithmic systems, the emphasis of engagement should shift to a rational communication process through which a continuous and tentative assessment of the development, workings, and consequences of algorithms can be achieved over time. The degree to which such engagement is, in fact, rational can be assessed based on four discourse-ethical principles of participation, comprehension, multivocality, and responsiveness. We conclude that the framework may help organizations and their environments to jointly work toward greater accountability for complex algorithms. It may further help organizations in reputational positioning surrounding accountability issues. The discourse-ethical principles introduced in this article are meant to elevate these positioning contests to extend beyond mere adaption or compliance and help guide organizations to find moral and forward-looking solutions to accountability issues. (shrink)

The potential for biases being built into algorithms has been known for some time, yet literature has only recently demonstrated the ways algorithmic profiling can result in social sorting and harm marginalised groups. We contend that with increased algorithmic complexity, biases will become more sophisticated and difficult to identify, control for, or contest. Our argument has four steps: first, we show how harnessing algorithms means that data gathered at a particular place and time relating to specific persons, can be used (...) to build group models applied in different contexts to different persons. Thus, privacy and data protection rights, with their focus on individuals, do not protect from the discriminatory potential of algorithmic profiling. Second, we explore the idea that anti-discrimination regulation may be more promising, but acknowledge limitations. Third, we argue that in order to harness anti-discrimination regulation, it needs to confront emergent forms of discrimination or risk creating new invisibilities, including invisibility from existing safeguards. Finally, we outline suggestions to address emergent forms of discrimination and exclusionary invisibilities via intersectional and post-colonial analysis. (shrink)

Since their public launch, a little over a year ago, large language models (LLMs) have inspired a flurry of analysis about what their implications might be for medical ethics, and for society more broadly. 1 Much of the recent debate has moved beyond categorical evaluations of the permissibility or impermissibility of LLM use in different general contexts (eg, at work or school), to more fine-grained discussions of the criteria that should govern their appropriate use in specific domains or towards certain (...) ends. 2 With each passing week, it seems more and more inevitable that LLMs will be a pervasive feature of many, if not most, of our lives. It would not be possible—and would not be desirable—to prohibit them across the board. We need to learn how to live with LLMs; to identify and mitigate the risks they pose to us, to our fellow creatures, and the... (shrink)

In this paper, we suggest that personalized LLMs trained on information written by or otherwise pertaining to an individual could serve as artificial moral advisors (AMAs) that account for the dynamic nature of personal morality. These LLM-based AMAs would harness users’ past and present data to infer and make explicit their sometimes-shifting values and preferences, thereby fostering self-knowledge. Further, these systems may also assist in processes of self-creation, by helping users reflect on the kind of person they want to be (...) and the actions and goals necessary for so becoming. The feasibility of LLMs providing such personalized moral insights remains uncertain pending further technical development. Nevertheless, we argue that this approach addresses limitations in existing AMA proposals reliant on either predetermined values or introspective self-knowledge. (shrink)

Danaher and Nyholm ( 2024a ) have recently proposed that digital duplicates—such as fine-tuned, “personalized” large language models that closely mimic a particular individual—might reduce that individual’s _scarcity_ and thus increase the amount of instrumental value they can bring to the world. In this commentary, we introduce the notion of _relational scarcity_ and explore how digital duplicates would affect the value of interpersonal relationships.

Moving away from the strong body of critique of pervasive ‘bad data’ practices by both governments and private actors in the globalized digital economy, this book aims to paint an alternative, more optimistic but still pragmatic picture of the datafied future. The authors examine and propose ‘good data’ practices, values and principles from an interdisciplinary, international perspective. From ideas of data sovereignty and justice, to manifestos for change and calls for activism, this collection opens a multifaceted conversation on the kinds (...) of futures we want to see, and presents concrete steps on how we can start realizing good data in practice. (shrink)

Participation in research is supposed to be voluntary and informed. Yet it is difficult to ensure people are adequately informed about the potential uses of their biological materials when they donate samples for future research. We propose a novel consent framework which we call “demonstrated consent” that leverages blockchain technology and generative AI to address this problem. In a demonstrated consent model, each donated sample is associated with a unique non-fungible token (NFT) on a blockchain, which records in its metadata (...) information about the planned and past uses of the sample in research, and is updated with each use of the sample. This information is accessible to a large language model (LLM) customized to present this information in an understandable and interactive manner. Thus, our model uses blockchain and generative AI technologies to track, make available, and explain information regarding planned and past uses of donated samples. (shrink)

We propose a pluralist account of content for predictive processing systems. Our pluralism combines Millikan's teleosemantics with existing structural resemblance accounts. The paper has two goals. First, we outline how a teleosemantic treatment of signal passing in predictive processing systems would work, and how it integrates with structural resemblance accounts. We show that the core explanatory motivations and conceptual machinery of teleosemantics and predictive processing mesh together well. Second, we argue this pluralist approach expands the range of empirical cases to (...) which the predictive processing framework might be successfully applied. This is because our pluralism is practice-oriented. A range of different notions of content are used in the cognitive sciences to explain behaviour, and some of these cases look to employ teleosemantic notions. As a result, our pluralism gives predictive processing the scope to cover these cases. (shrink)

A key argument of Dixon et al. in the target article is that prejudice reduction through intergroup contact and collective action work in opposite ways. We argue for a complementary approach focusing on extreme emotions to understand why people turn to non-normative collective action and to understand when and under what conditions extreme emotions may influence positive effects of contact on reconciliation.

A central goal of research in explainable artificial intelligence (XAI) is to facilitate human understanding. However, understanding is an elusive concept that is difficult to target. In this paper, we argue that a useful way to conceptualize understanding within the realm of XAI is via certain human abilities. We present four criteria for a useful conceptualization of understanding in XAI and show that these are fulfilled by an abilities-based approach: First, thinking about understanding in terms of specific abilities is motivated (...) by research from numerous disciplines involved in XAI. Second, an abilities-based approach is highly versatile and can capture different forms of understanding important in XAI application contexts. Third, abilities can be operationalized for empirical studies. Fourth, abilities can be used to clarify the link between explainability, understanding, and societal desiderata concerning AI, like fairness and trustworthiness. Conceptualizing understanding as abilities can therefore support interdisciplinary collaboration among XAI researchers, provide practical benefit across diverse XAI application contexts, facilitate the development and evaluation of explainability approaches, and contribute to satisfying the societal desiderata of different stakeholders concerning AI systems. (shrink)

We present a compositional semantics for first-order logic with imperfect information that is equivalent to Sevenster and Sandu’s equilibrium semantics (under which the truth value of a sentence in a finite model is equal to the minimax value of its semantic game). Our semantics is a generalization of an earlier semantics developed by the first author that was based on behavioral strategies, rather than mixed strategies.

Contrary to Vaesen's argument that humans are unique with respect to nine cognitive capacities essential for tool use, we suggest that although such cognitive processes contribute to variation in tool use, it does not follow that these capacities arenecessaryfor tool use, nor that tool use shaped cognition per se, given the available data in cognitive neuroscience and behavioral biology.

It is not uncommon to hear that poor school performance, welfare dependancy, youth unemployment, and criminal activity result more from shortcomings in the personal makeup of individuals than from societal forces beyond their control. Are American values declining as so many suggest? And are those values at the root of many social problems today?Shaped by experience and public policies, people's values and social norms do change. What role can or should a democratic government play in shaping values? And how do (...) these values conditon the efficacy of public policy?In this book, six distinguished social scientists identify trends in America's values and their consequences, and consider public policy tools with which some of those values might be changed.Daniel Yankelovich begins with a discussion of how American values have shifted in the last half-century, and argues that affluence is the driving force behind these changes in values. James Q. Wilson argues that destructive habits which can lead to social pathologies, like crime and drug use, are set early in life; he examines how public policy might intervene when children are young to promote better values. David Popenoe maintains that America has veered too far towards industrialist values, and explores the resulting decline of families and many attendant social ills. Nathan Glazer describes the history and present status of the dispute over multicultural education. Jane Mansbridge examines the process of building cooperation, consensus, and public spirit. And George Akerlof and Janet L. Yellen discuss the problem of gang criminality.Inthe past, social scientists have often sidestepped questions about values as undefinable, unquantifiable, and somehow unscientific. The essays in this volume address these questions at last.Henry J. Aaron, director of the Economic Studies program at Brookings, is the authorof numerous books, including most recently Serious and Unstable Condition: Financing America's Health Care (1991), and coeditor of Setting Domestic Priorities (1992). Thomas E. Mann is director of the Brookings Governmental Studies program, coeditor of Media Polls in American Politics (1992), and coauthor of the Renewing Congress series (1993). Timothy Taylor is managing editor of the Journal of Economic Perspectives at Stanford University. (shrink)

Objective Hermeneutics is a qualitative method that focuses on few sequences of texts, which helps understand single cases. It is used to explore how consumers cope with the contradiction between their enjoyment for meat and their empathy for animals without using frameworks drafted by social scientists. Five cases are analysed, which range from strong references towards the societal norm of meat eating to a feeling of uncertainty in the face of the animals’ death. None of the cases, however, sees the (...) necessity to find a rationale for their own meat consumption. The study concludes by raising the question about the persistence of a societal consensus for meat consumption. (shrink)

Although the authors' ingenuity in identifying criteria for innovation for field studies is appealing, most field studies will lack adequate data. Additionally, their definition does not clearly distinguish innovation from individual learning and is vague about cognitive mechanisms involved. We suggest that developmental data are essential to identifying the causes and consequences of learning new behaviors.

Entangled states whose Wigner functions are non-negative may be viewed as being accounted for by local hidden variables (LHV). Recently, there were studies of Bell’s inequality violation (BIQV) for such states in conjunction with the well known theorem of Bell that precludes BIQV for theories that have LHV underpinning. We extend these studies to teleportation which is also based on entanglement. We investigate if, to what extent, and under what conditions may teleportation be accounted for via LHV theory. Our study (...) allows us to expose the role of various quantum requirements. These are, e.g., the uncertainty relation among non-commuting operators, and the no-cloning theorem which forces the complete elimination of the teleported state at its initial port. (shrink)

Background: Collaboration between physicians and nurses is key to improving patient care. We know very little about collaboration and interdisciplinary practice in African healthcare settings. Research question/aim: The purpose of this study was to explore the ethical challenges of interdisciplinary collaboration in clinical practice and education in Botswana Participants and research context: This qualitative descriptive study was conducted with 39 participants (20 physicians and 19 nurses) who participated in semi-structured interviews at public hospitals purposely selected to represent the three levels (...) of hospitals in Botswana (referral, district, and primary). Ethical considerations: Following Institutional Review Board Approval at the University of Pennsylvania and the Ministry of Health in Botswana, participants’ written informed consent was obtained. Findings: Respondents’ ages ranged from 23 to 60 years, and their duration of work experience ranged from 0.5 to 32 years. Major qualitative themes that emerged from the data centered on the nature of the work environment, values regarding nurse–doctor collaboration, the nature of such collaboration, resources available for supporting collaboration and the smooth flow of work, and participants’ views about how their work experiences could be improved. Discussion: Participants expressed concerns that their work environment compromised their ability to provide high-quality and safe care to their patients. The physician staffing structure was described as consisting of a few specialists at the top, a vacuum in the middle that should be occupied by senior doctors, and junior doctors at the bottom—and not a sufficient number of nursing staff. Conclusion: Collaboration between physicians and nurses is critical to optimizing patients’ health outcomes. This is true not only in the United States but also in developing countries, such as Botswana, where health care professionals reported that their ethical challenges arose from resource shortages, differing professional attitudes, and a stressful work environment. (shrink)

_Purpose:_ In order to develop an evidence-based, sport-specific minimum impairment criteria (MIC) for the sport of vision-impaired (VI) shooting, this study aimed to determine the relative influence of losses in visual acuity (VA) and contrast sensitivity (CS) on shooting performance. Presently, VA but not CS is used to determine eligibility to compete in VI shooting. _Methods:_ Elite able-sighted athletes ( n = 27) shot under standard conditions with their habitual vision, and with their vision impaired by the use of simulation (...) spectacles (filters which reduce both VA and CS) and refractive blur (lenses which reduce VA with less effect on CS). Habitual shooting scores were used to establish a cut-off in order to determine when shooting performance was ‘below expected’ in the presence of vision impairment. Logistic regression and decision tree analyses were then used to assess the relationship between visual function and shooting performance. _Results:_ Mild reductions in VA and/or CS did not alter shooting performance, with greater reductions required for shooting performance to fall below habitual levels (below 87% of normalized performance). Stepwise logistic regression selected CS as the most significant predictor of shooting performance, with VA subsequently improving the validity of the model. In an unconstrained decision tree analysis, CS was selected as the sole criterion (80%) for predicting ‘below expected’ shooting score. _Conclusion:_ Shooting performance is better predicted by losses in CS than by VA. Given that it is not presently tested during classification, the results suggest that CS is an important measure to include in testing for the classification of vision impairment for athletes competing in VI shooting. (shrink)

We describe a new class of experiments designed to probe the foundations of quantum mechanics. Using quantum controlling devices, we show how to attain a freedom in temporal ordering of the control and detection of various phenomena. We consider wave–particle duality in the context of quantum-controlled and the entanglement-assisted delayed-choice experiments. Then we discuss a quantum-controlled CHSH experiment and measurement of photon’s transversal position and momentum in a single set-up.

BackgroundDecision-making in out-of-hospital cardiac arrest should ideally include clinical and ethical factors. Little is known about the extent of ethical considerations and their influence on prehospital resuscitation. We aimed to determine the transparency in medical records regarding decision-making in prehospital resuscitation with a specific focus on ethically relevant information and consideration in resuscitation providers’ documentation.MethodsThis was a Danish nationwide retrospective observational study of out-of-hospital cardiac arrests from 2016 through 2018. After an initial screening using broadly defined inclusion criteria, two experienced (...) philosophers performed a qualitative content analysis of the included medical records according to a preliminary codebook. We identified ethically relevant content in free-text fields and categorised the information according to Beauchamp and Childress’ four basic bioethical principles: autonomy, non-maleficence, beneficence, and justice. ResultsOf 16,495 medical records, we identified 759 (4.6%) with potentially relevant information; 710 records (4.3%) contained ethically relevant information, whereas 49 did not. In general, the documentation was vague and unclear. We identified four kinds of ethically relevant information: patients’ wishes and perspectives on life; relatives’ wishes and perspectives on patients’ life; healthcare professionals’ opinions and perspectives on resuscitation; and do-not-resuscitate orders. We identified some “best practice” examples that included all perspectives of decision-making. ConclusionsThere is sparse and unclear evidence on ethically relevant information in the medical records documenting resuscitation after out-of-hospital cardiac arrests. However, the “best practice” examples show that providing sufficient documentation of decision-making is, in fact, feasible. To ensure transparency surrounding prehospital decisions in cardiac arrests, we believe that it is necessary to ensure more systematic documentation of decision-making in prehospital resuscitation. (shrink)

BackgroundNonverbal social perception is the ability to interpret the intentions and dispositions of others by evaluating cues such as facial expressions, body movements, and emotional prosody. Nonverbal social perception plays a key role in social cognition and is fundamental for successful social interactions. Patients with schizophrenia have severe impairments in nonverbal social perception leading to social isolation and withdrawal. Collectively, these aforementioned deficits affect patients’ quality of life. Here, we compare nonverbal social perception in patients with schizophrenia and controls and (...) examine how nonverbal social perception relates to daily functioning.MethodsWe compared nonverbal social perception in 41 stable outpatients with schizophrenia and 30 healthy controls using the Mini Profile of Nonverbal Sensitivity. The participants evaluated 64 video clips showing a female actor demonstrating various nonverbal social cues. Participants were asked to choose one of two options that best described the observed scenario. We correlated clinical ratings, Self-report of Negative Symptoms, and functional assessments with Mini-PONS scores.ResultsPatients performed significantly poorer in the Mini-PONS compared to controls, suggesting deficits in nonverbal social perception. These deficits were not associated with either positive symptoms or negative symptoms. However, impaired nonverbal social perception correlated with distinctive domains of BNSS, as well as functional capacity and functional outcome in patients.ConclusionWe demonstrate that nonverbal social perception is impaired in stable outpatients with schizophrenia. Nonverbal social perception is directly related to specific negative symptom domains, functional capacity and functional outcome. These findings underline the importance of nonverbal social perception for patients’ everyday life and call for novel therapeutic approaches to alleviate nonverbal social perception deficits. (shrink)