Teleological accounts of sensory normativity treat normal functioning for a species as a standard: sensory error involves departure from normal functioning for the species, i.e. sensory malfunction. Straightforward reflection on sensory trade-offs reveals that normal functioning for a species can exhibit failures of accuracy. Acknowledging these failures of accuracy is central to understanding the adaptations of a species. To make room for these errors we have to go beyond the teleological framework and invoke the notion (...) of an ideal observer from vision science. The notion of an ideal observer also sheds light on the important distinction between sensory malfunction and sensory limitation. (shrink)

Autism spectrum disorder is characterised by differences in unimodal and multimodal sensory and proprioceptive processing, with complex biases towards local over global processing. Many of these elements are implicated in versions of the rubber hand illusion, which were therefore studied in high-functioning individuals with ASD and a typically developing control group. Both groups experienced the illusion. A number of differences were found, related to proprioception and sensorimotor processes. The ASD group showed reduced sensitivity to visuotactile-proprioceptive discrepancy but more accurate (...) proprioception. This group also differed on acceleration in subsequent reach trials. Results are discussed in terms of weak top-down integration and precision-accuracy trade-offs. The RHI appears to be a useful tool for investigating multisensory processing in ASD. (shrink)

We argue that deliberative decision-making that is inclusive, transparent and accountable can contribute to more trustworthy and legitimate decisions on difficult ethical questions and political trade-offs during the pandemic and beyond.

This paper presents two challenges faced by many initiatives that try to diversify undergraduate philosophy curricula, both intellectually and demographically. Trade-offs involve making difficult decisions to prioritise some values over others (like gender diversity over cultural diversity). Backfires involve unintended consequences contrary to the aims and values of diversity initiatives, including ones that compromise more general philosophical values. I discuss two specific backfire risks, involving the critical and political dimensions of teaching philosophy. Some general practical advice is offered along (...) the way. (shrink)

There is growing concern that decision-making informed by machine learning (ML) algorithms may unfairly discriminate based on personal demographic attributes, such as race and gender. Scholars have responded by introducing numerous mathematical definitions of fairness to test the algorithm, many of which are in conflict with one another. However, these reductionist representations of fairness often bear little resemblance to real-life fairness considerations, which in practice are highly contextual. Moreover, fairness metrics tend to be implemented in narrow and targeted toolkits that (...) are difficult to integrate into an algorithm’s broader ethical assessment. In this paper, we derive lessons from ethical philosophy and welfare economics as they relate to the contextual factors relevant for fairness. In particular we highlight the debate around acceptability of particular inequalities and the inextricable links between fairness, welfare and autonomy. We propose Key Ethics Indicators (KEIs) as a way towards providing a more holistic understanding of whether or not an algorithm is aligned to the decision-maker’s ethical values. (shrink)

This article offers a characterization of what I call multiple-models juxtaposition, a strategy for managing trade-offs among modeling desiderata. MMJ displays models of distinct phenomena to...

This research is concerned with understanding the factors behind the trade-off between child labor and child schooling, given the well-documented links between the two. It examines parents' behavior in their decision-making on their children's schooling or practicing child labor. Depending on qualitative research methods including 28 semi-structured interviews and two focus group discussions conducted in the rural areas of Bangladesh in 2020, this study reveals the following: subsistence needs compel households, particularly the ultra-poor and the female-headed, to trade (...) off child labor with schooling; due to higher demand of labor, parents engage their children into work instead of schooling; parents of labor-intensive occupations tend to trade off child labor with schooling; sexual division of labor remains obvious; finally, credit constraints and cultural beliefs have negative impacts on parental decision-making on child schooling. Interventions aiming to reduce child labor and increase schooling in these rural areas must remain mindful of the socio-economic and cultural needs. (shrink)

Ian James Kidd ABSTRACT: This paper presents two challenges faced by many initiatives that try to diversify undergraduate philosophy curricula, both intellectually and demographically. Trade-offs involve making difficult decisions to prioritise some values over others. Backfires involve unintended consequences contrary to the aims and values of diversity initiatives, including ….

In the context of a global pandemic, there is good health-based reason for governments to impose various social distancing measures. However, such measures also cause economic and other harms to people at low risk from the virus. In this paper, I examine how to make such trade-offs in a way that is respectfully justifiable to their losers. I argue that existing proposals like using standard QALY (quality-adjusted life-year) valuations or WELLBYs (wellbeing-adjusted life-years) as the currency for trade-offs do (...) not allow such justification, because they give weight to utilities that are irrelevant in a life-and-death context. Drawing on work on restricted aggregation in ethics, I articulate an alternative framework for balancing claims arising from prospects of different kinds of harm and benefit, and show how it can be applied to reasoning about trade-offs in a pandemic context. (shrink)

In the debate on how we ought to define political freedom, some definitions are criticized for implying that no one can ever be free to perform any action. In this paper, I show how the possibility of freedom depends on a definition that finds an appropriate balance between absence of interference and protection against interference. To assess the possibility of different conceptions of freedom, I consider the trade-offs they make between these two dimensions. I find that pure negative freedom (...) is clearly possible. Republican freedom might also be possible, though its protection requirement is too vague for a definitive verdict. Finally, the recently proposed ‘freedom as independence’ is impossible since it is an attempt to avoid the unavoidable trade-off. (shrink)

Abstract: Recently, the experimental philosopher Joshua Knobe has shown that the folk are more inclined to describe side effects as intentional actions when they bring about bad results. Edouard Machery has offered an intriguing new explanation of Knobe's work—the 'trade-off hypothesis'—which denies that moral considerations explain folk applications of the concept of intentional action. We critique Machery's hypothesis and offer empirical evidence against it. We also evaluate the current state of the debate concerning the concept of intentionality, and argue (...) that, given the number of variables at play, any parsimonious account of the relevant data is implausible. (shrink)

This chapter argues that rather than viewing transparency as a right, we should regard it as a finite resource whose allocation involves tradeoffs. It then argues that those tradeoffs should be resolved by using a multi-principle approach to distributive justice. The relevant principles include maximizing welfare, maximizing autonomy, and giving priority to the worst off. Finally, it examines some of the implications for law of recognizing the tradeoffs presented by transparency proposals.

This paper focuses on two highly publicized formal trade-offs in the field of responsible artificial intelligence (AI) -- between predictive accuracy and fairness and between predictive accuracy and interpretability. These formal trade-offs are often taken by researchers, practitioners, and policy-makers to directly imply corresponding tensions between underlying values. Thus interpreted, the trade-offs have formed a core focus of normative engagement in AI governance, accompanied by a particular division of labor along disciplinary lines. This paper argues against this (...) prevalent interpretation by drawing attention to three sets of considerations that are critical for bridging the gap between these formal trade-offs and their practical impacts on relevant values. I show how neglecting these considerations can distort our normative deliberations, and result in costly and misaligned interventions and justifications. Taken together, these considerations form a sociotechnical framework that could guide those involved in AI governance to assess how, in many cases, we can and should have higher aspirations than the prevalent interpretation of the trade-offs would suggest. I end by drawing out the normative opportunities and challenges that emerge out of these considerations, and highlighting the imperative of interdisciplinary collaboration in fostering responsible AI. (shrink)

Lane et al. propose an integrative model for the reconsolidation of traces in their timely and impressive article. This commentary draws attention to tradeoffs between accuracy and self-narrative integrity in the model. The tradeoffs concern the sense of agency in memory and its role in both implicit and explicit memory reconsolidation, rather than balances concerning degrees of emotional arousal.

Autonomy is often considered a core value of Western society that is deeply entrenched in moral, legal, and political practices. The development and deployment of artificial intelligence (AI) systems to perform a wide variety of tasks has raised new questions about how AI may affect human autonomy. Numerous guidelines on the responsible development of AI now emphasise the need for human autonomy to be protected. In some cases, this need is linked to the emergence of increasingly ‘autonomous’ AI systems that (...) can perform tasks without human control or supervision. Do such ‘autonomous’ systems pose a risk to our own human autonomy? In this article, I address the question of a trade-off between human autonomy and system ‘autonomy’. (shrink)

Tailoring the design of robot bodies for control purposes is implicitly performed by engineers, however, a methodology or set of tools is largely absent and optimization of morphology (shape, material properties of robot bodies, etc.) is lag- ging behind the development of controllers. This has become even more prominent with the advent of compliant, deformable or "soft" bodies. These carry substantial potential regarding their exploitation for control – sometimes referred to as "mor- phological computation" in the sense of offloading computation (...) needed for control to the body. Here, we will argue in favor of a dynamical systems rather than com- putational perspective on the problem. Then, we will look at the pros and cons of simple vs. complex bodies, critically reviewing the attractive notion of “soft” bodies automatically taking over control tasks. We will address another key dimension of the design space – whether model-based control should be used and to what extent it is feasible to develop faithful models for different morphologies. ----- This paper was also published in the 2014 AISB proceedings http://aisb50.org/representation-of-reality-humans-animals-and-machines/ - http://doc.gold.ac.uk/aisb50/. (shrink)

Non-technical summary: -/- When developing and deploying negative emissions technologies (NETs), little attention has been paid to where. On the one hand, one might develop NETs where they are likely to contribute most to global mitigation targets, contributing to a global climate solution. On the other hand, one might develop NETs where they can help support development on a regional basis, justified by regional demands. I defend these arguments and suggest that they reflect the values of efficiency and responding to (...) need, respectively. To the extent that these values conflict, they introduce what I call the Need-Efficiency Trade-off Effect (‘NET Effect’). -/- Technical summary: -/- Unlike other geoengineering methods, the effectiveness of negative emissions technologies (NETs) tends to be sensitive to regional siting. This paper argues that this point raises morally and legally important implications by identifying a trade-off between ‘efficiency’ and ‘need’. First, it introduces two arguments justifying NETs: one focused on contributions to global mitigation and the other focused on contributions to regional development. Second, reflecting the two arguments, the paper discusses the moral values of efficiency and need, respectively. For instance, if the strategy is to try to use NETs to maximize expected mitigation contributions to reflect efficiency, then deployment should occur in regions with the best prospects for success (e.g. Western countries). However, if the strategy is to try to use NETs to improve the chances of simultaneous development and mitigation to respond to need, then deployment should occur in regions with limited development and expected growth of demand for NETs (e.g. Asian countries). When these values conflict, I call that a Need-Efficiency Trade-off Effect (‘NET Effect’). The paper concludes by considering the NET Effect in the context of bioenergy with carbon capture and storage as well as direct air carbon capture and storage. [Open access]. (shrink)

To address the rising concern that algorithmic decision-making may reinforce discriminatory biases, researchers have proposed many notions of fairness and corresponding mathematical formalizations. Each of these notions is often presented as a one-size-fits-all, absolute condition; however, in reality, the practical and ethical trade-offs are unavoidable and more complex. We introduce a new approach that considers fairness—not as a binary, absolute mathematical condition—but rather, as a relational notion in comparison to alternative decisionmaking processes. Using US mortgage lending as an example (...) use case, we discuss the ethical foundations of each definition of fairness and demonstrate that our proposed methodology more closely captures the ethical trade-offs of the decision-maker, as well as forcing a more explicit representation of which values and objectives are prioritised. (shrink)

Explanation is a foundational goal in the exact sciences. Besides the contemporary considerations on ‘description’, ‘classification’, and ‘prediction’, we often see these terms in thriving applications of artificial intelligence (AI) in chemistry hypothesis generation. Going beyond describing ‘things in the world’, these applications can make accurate numerical property calculations from theoretical or topological descriptors. This association makes an interesting case for a logic of discovery in chemistry: are these induction-led ventures showing a shift in how chemists can problematize research questions? (...) In this article, I present a fresh perspective on the current context of discovery in chemistry. I argue how data-driven statistical predictions in chemistry can be explained as a quasi-logical process for generating chemical theories, beyond the classic examples of organic and theoretical chemistry. Through my position on formal models of scientific explanation, I demonstrate how the dawn of AI can provide novel insights into the explanatory power of scientific endeavors. (shrink)

Engineers fine-tune the design of robot bodies for control purposes, however, a methodology or set of tools is largely absent, and optimization of morphology (shape, material properties of robot bodies, etc.) is lagging behind the development of controllers. This has become even more prominent with the advent of compliant, deformable or ”soft” bodies. These carry substantial potential regarding their exploitation for control—sometimes referred to as ”morphological computation”. In this article, we briefly review different notions of computation by physical systems and (...) propose the dynamical systems framework as the most useful in the context of describing and eventually designing the interactions of controllers and bodies. Then, we look at the pros and cons of simple vs. complex bodies, critically reviewing the attractive notion of ”soft” bodies automatically taking over control tasks. We address another key dimension of the design space—whether model-based control should be used and to what extent it is feasible to develop faithful models for different morphologies. (shrink)

The Market Failures Approach (MFA) is one of the leading theories in contemporary business ethics. It generates a list of ethical obligations for the managers of private firms that states that they should not create or exploit market failures because doing so reduces the efficiency of the economy. Recently the MFA has been criticised by Abraham Singer on the basis that it unjustifiably does not assign private managers obligations based on egalitarian values. Singer proposes an extension to the MFA, the (...) Justice Failures Approach (JFA), in which managers have duties to alleviate political, social, and distributive inequalities in addition to having obligations to not exploit market failures. In this paper I describe the MFA and JFA and situate them relative to each other. I then highlight a threefold distinction between different types of obligations that can be given to private managers in order to argue that a hybrid theory of business ethics, which I call the MFA +, can be generated by arguing that managers have obligations based on efficiency and duties based on equality to the extent that these latter obligations do not lead to efficiency losses. This argument suggests a novel theoretical option in business ethics, elucidates the issues that are at stake between the MFA and the JFA, and clarifies the costs and benefits of each theory. (shrink)

Minimum wages are usually assumed to be inefficient as they prevent the full exploitation of mutual gains from trade. Yet advocates of wage regulation policies have repeatedly claimed that this loss in market efficiency can be justified by the pursuit of ethical goals. Policy makers, it is argued, should not focus on efficiency alone. Rather, they should try to find an adequate balance between efficiency and equity targets. This idea is based on a two-worlds-paradigm that sees ethics and economics (...) as two inherently conflicting ways of thinking. We, however, believe that this view of the relationship between ethics and economics is fundamentally flawed and blurs our understanding of how an ethically responsible regulation of the labour market should be conducted. In drawing on an economic-ethical approach that resolves the antinomy between efficiency and equity, we show that ethics and economics are, in fact, two sides of the same coin and that minimum wage legislation can only be ethically responsible, if it is at the same time economically efficient. In other words, we can have our cake and eat it too. On the basis of our approach, we develop two simple game theoretical models for different types of labour markets and derive policy implications from an economic-ethical viewpoint. We suggest that under the assumption of perfectly competitive labour markets a tax-funded wage subsidy is preferable over minimum wages, as it makes everyone better off. If, however, employers have monopsony power in the wage setting process, the minimum wage is justifiable under certain conditions. (shrink)

This paper disputes the notion, endorsed by much of narrative theory, that the reading of literary narrative is functionally analogous to an act of communication, where communication stands for the transfer of thought and conceptual information. The paper offers a basic typology of the sensorimotor effects of reading, which fall outside such a narrowly communication-based model of literary narrative. A main typological distinction is drawn between those sensorimotor effects pertaining to the narrative qua verbal utterance (verbal presence) and those sensorimotor (...) effects pertaining to the imaginary physical world(s) of the story (direct presence). While verbal presence refers to the reader's vicarious perception of the voices of narrators and characters, direct presence refers to the emulated sensorimotor experience of the imaginary worlds that the narrators' and characters' utterances refer to. The paper further elaborates on how, by which kinds of narrative content and structure, direct presence may be prompted. The final section addresses some of the observational and historical caveats that must be attached to any theoretical inquiry made into the sensorimotor effects of reading. As a preliminary for further research, a few ideas about the model's potential for empirical validation are put forward. A brief, tentative history of the sensorimotor benefits of literary narrative reading is then outlined. (shrink)

This article argues that capital flight of real investment presents governments with a quadrilemma. First, governments can tailor their policies to attract investors – but this is incompatible with a whole range of alternative policy choices. Second, they can simply accept capital flight – but this is incompatible with a robust capital stock and tax base. Third, they can harmonize its taxes and regulations with other states – but this is incompatible with international independence. Fourth, they can impose capital controls (...) – but this is incompatible with international capital mobility. These incompatibilities make up four different goals, the value of which are described. Strategies may be mixed, but the pursuit of any three goals must always come at the expense of the fourth. (shrink)

The overall aim of this article is to reorient the contemporary debate about epistemic consequentialism. Thus far the debate has to a large extent focused on whether standard theories of epistemic justification are consequentialist in nature and therefore vulnerable to certain trade-off cases where accepting a false or unjustified belief leads to good epistemic outcomes. We claim that these trade-offs raise an important—yet somewhat neglected—issue about the epistemic demands on inquiry. We first distinguish between two different kinds of (...) epistemic evaluation, viz., backing evaluation and outcome evaluation, and then go on to outline and discuss a consequentialist metatheory about the right combinations of decision procedures to adopt in inquiry. Note that the piece is exploratory in the following sense: we try to explore epistemic evaluation in consequentialist terms, which involves stating a form of epistemic consequentialism, but also pointing to what non-consequentialist alternatives might be. Rather than trying to argue decisively for a particular conclusion, we aim to outline various intricate issues in an underexplored area of theorizing. In the course of doing this, we’ll transpose some well-known themes from discussions of consequentialism in ethics to the current debate about consequentialism in epistemology, e.g., agent-neutrality, options, and side-constraints. (shrink)

Critics have recently argued that reliabilists face trade-off problems, forcing them to condone intuitively unjustified beliefs when they generate lots of true belief further downstream. What these critics overlook is that reliabilism entails that there areside-constraintson belief-formation, on account of which there are some things you should not believe, even if doing so would have very good epistemic consequences. However, we argue that by embracing side-constraints the reliabilist faces a dilemma: she can either hold on to reliabilism, and with (...) it aforementioned side-constraints, but then needs to explain why we should allow the pursuit of justification to get in the way of the acquisition of true belief; or she can deny that there are side-constraints – and in effect give up on reliabilism. We'll suggest that anyone moved by the considerations that likely attract people to reliabilism in the first place – the idea the true belief is good, and as such should be promoted – should go for the second horn, and instead pursue a form ofepistemic utilitarianism. (shrink)

There is a general presumption against arming outlaw states. But can that presumption sometimes be overturned? The argument considered here maintains that outlaw states can have legitimate security interests and that transferring weapons to these states can be an appropriate way of promoting those interests. Weapons enable governments to engage in wrongful oppression and aggression, but they also enable them to fend off predators in a manner that can be beneficial to their citizens. It clearly does not follow from the (...) fact that a state is oppressive or aggressive that it will never be a victim of wrongful aggression itself, and while an outlaw state’s primary aim in repelling such aggression will often be the preservation of its own power, its defensive manoeuvres will sometimes also serve its citizens’ interests. In short, supplying weapons to outlaw states may sometimes contribute to the protection of innocents. (shrink)

There is a trade-off between specificity and accuracy in existing models of belief. Descriptions of agents in the tripartite model, which recognizes only three doxastic attitudes—belief, disbelief, and suspension of judgment—are typically accurate, but not sufficiently specific. The orthodox Bayesian model, which requires real-valued credences, is perfectly specific, but often inaccurate: we often lack precise credences. I argue, first, that a popular attempt to fix the Bayesian model by using sets of functions is also inaccurate, since it requires us (...) to have interval-valued credences with perfectly precise endpoints. We can see this problem as analogous to the problem of higher order vagueness. Ultimately, I argue, the only way to avoid these problems is to endorse Insurmountable Unclassifiability. This principle has some surprising and radical consequences. For example, it entails that the trade-off between accuracy and specificity is in-principle unavoidable: sometimes it is simply impossible to characterize an agent’s doxastic state in a way that is both fully accurate and maximally specific. What we can do, however, is improve on both the tripartite and existing Bayesian models. I construct a new model of belief—the minimal model—that allows us to characterize agents with much greater specificity than the tripartite model, and yet which remains, unlike existing Bayesian models, perfectly accurate. (shrink)

This article introduces and defends the “pathological complexity thesis” as a hypothesis about the evolutionary origins of minimal consciousness, or sentience, that connects the study of animal consciousness closely with work in behavioral ecology and evolutionary biology. I argue that consciousness is an adaptive solution to a design problem that led to the extinction of complex multicellular animal life following the Avalon explosion and that was subsequently solved during the Cambrian explosion. This is the economic trade-off problem of having (...) to deal with a complex body with high degrees of freedom, what I call “pathological complexity.” By modeling the explosion of this computational complexity using the resources of state-based behavioral and life history theory we will be able to provide an evolutionary bottom-up framework to make sense of subjective experience and its function in nature by paying close attention to the ecological lifestyles of different animals. (shrink)

All too often, the requirements for actionability and accountability of data infrastructures are conceptualised as incompatible and leading to a trade-off situation where increasing one will unavoidably decrease the other. Through a comparative analysis of two data infrastructures used to share genomic data about the SARS-COV-2 virus, we argue that making data actionable for knowledge development involves a commitment to ensuring that the data in question are representative of the phenomena being studied and accountable to data subjects and users. (...) This in turn presupposes that: (1) enough data are contributed by a wide and diverse set of relevant sources; (2) mechanisms of feedback and inclusion are set up to ensure that data contributors can participate data governance and interpretation, thereby helping to adequately contextualise data; and (3) accountability extends to the ways in which data infrastructures are run, financed and positioned vis-à-vis the communities they are meant to serve. Such a model of data sharing can only work on the understanding that data do not need to be easily accessible to be actionable; rather, actionability depends on the responsiveness and accountability of data infrastructures, and the efforts invested in ensuring open communication among contributors. (shrink)

Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions. These models are a useful pedagogical device for teaching trained professionals how to predict what decisions will be made by the complex system, and most importantly how the system might break. However, when considering any such model it’s important to remember Box’s maxim that "All models are wrong but some are useful." We focus on (...) the distinction between these models and explanations in philosophy and sociology. These models can be understood as a "do it yourself kit" for explanations, allowing a practitioner to directly answer "what if questions" or generate contrastive explanations without external assistance. Although a valuable ability, giving these models as explanations appears more difficult than necessary, and other forms of explanation may not have the same trade-offs. We contrast the different schools of thought on what makes an explanation, and suggest that machine learning might benefit from viewing the problem more broadly. (shrink)

Which is better: a guarantee of a modest amount of moral value, or a tiny probability of arbitrarily large value? To prefer the latter seems fanatical. But, as I argue, avoiding such fanaticism brings severe problems. To do so, we must decline intuitively attractive trade-offs; rank structurally identical pairs of lotteries inconsistently, or else admit absurd sensitivity to tiny probability differences; have rankings depend on remote, unaffected events ; and often neglect to rank lotteries as we already know we (...) would if we learned more. Compared to these implications, fanaticism is highly plausible. (shrink)

Davis called for “extreme caution” in the use of non-invasive brain stimulation to treat neurological disorders in children, due to gaps in scientific knowledge. We are sympathetic to his position. However, we must also address the ethical implications of applying this technology to minors. Compensatory trade-offs associated with NIBS present a challenge to its use in children, insofar as these trade-offs have the effect of limiting the child’s future options. The distinction between treatment and enhancement has some normative (...) force here. As the intervention moves away from being a treatment toward being an enhancement—and thus toward a more uncertain weighing of the benefits, risks, and costs—considerations of the child’s best interests diminish, and the need to protect the child’s autonomy looms larger. NIBS for enhancement involving trade-offs should therefore be delayed, if possible, until the child reaches a state of maturity and can make an informed, personal decision. NIBS for treatment, by contrast, is permissible insofar as it can be shown to be at least as safe and effective as currently approved treatments, which are themselves justified on a best interests standard. (shrink)

Objectives: Machine learning (ML) has the potential to facilitate “continual learning” in medicine, in which an ML system continues to evolve in response to exposure to new data over time, even after being deployed in a clinical setting. In this article, we provide a tutorial on the range of ethical issues raised by the use of such “adaptive” ML systems in medicine that have, thus far, been neglected in the literature. -/- Target audience: The target audiences for this tutorial are (...) the developers of ML AI systems, healthcare regulators, the broader medical informatics community, and practicing clinicians. -/- Scope: Discussions of adaptive ML systems to date have overlooked the distinction between 2 sorts of variance that such systems may exhibit—diachronic evolution (change over time) and synchronic variation (difference between cotemporaneous instantiations of the algorithm at different sites)—and underestimated the significance of the latter. We highlight the challenges that diachronic evolution and synchronic variation present for the quality of patient care, informed consent, and equity, and discuss the complex ethical trade-offs involved in the design of such systems. (shrink)

This paper outlines an account of political realism as a form of ideology critique. Our focus is a defence of the normative edge of this critical-theoretic project against the common charge that there is a problematic trade-off between a theory’s groundedness in facts about the political status quo and its ability to consistently envisage radical departures from the status quo. To overcome that problem we combine insights from three distant corners of the philosophical landscape: theories of legitimacy by Bernard (...) Williams and other realists, Frankfurt School-inspired Critical Theory, and recent analytic epistemological and metaphysical theories of cognitive bias, ideology, and social construction. The upshot is a novel account of realism as empirically-informed diagnosis- critique of social and political phenomena. This view rejects a sharp divide between descriptive and normative theory, and so is an alternative to the anti- empiricism of some approaches to Critical Theory as well as to the complacency towards existing power structures found within liberal realism, let alone mainstream normative political philosophy, liberal or otherwise. (shrink)

When it comes to epistemic normativity, should we take the good to be prior to the right? That is, should we ground facts about what we ought and ought not believe on a given occasion in facts about the value of being in certain cognitive states (such as, for example, the value of having true beliefs)? The overwhelming answer among contemporary epistemologists is “Yes, we should.” This essay argues to the contrary. Just as taking the good to be prior to (...) the right in ethics often leads one to sanction implausible trade-offs when determining what an agent should do, so too, this essay argues, taking the good to be prior to the right in epistemology leads one to sanction implausible trade-offs when determining what a subject should believe. Epistemic value—and, by extension, epistemic goals—are not the explanatory foundation upon which all other normative notions in epistemology rest. (shrink)

Where does the impetus towards ethical theory come from? What drives humans to make values explicit, consistent, and discursively justifiable? This paper situates the demand for ethical theory in human life by identifying the practical needs that give rise to it. Such a practical derivation puts the demand in its place: while finding a home for it in the public decision-making of modern societies, it also imposes limitations on the demand by presenting it as scalable and context-sensitive. This differentiates strong (...) forms of the demand calling for theory from weaker forms calling for less, and contexts where it has a place from contexts where it is out of place. In light of this, subjecting personal deliberation to the demand turns out to involve a trade-off. (shrink)

Many people believe that the research-based pharmaceutical industry has a ‘special’ moral obligation to provide lifesaving medications to the needy, either free-ofcharge or at a reduced rate relative to the cost of manufacture. In this essay, I argue that we can explain the ubiquitous notion of a special moral obligation as an expression of emotionally charged intuitions involving sacred or protected values and an aversive response to betrayal in an asymmetric trust relationship. I then review the most common arguments used (...) to justify the claim that the pharmaceutical industry has a special moral obligation and show why these justifications fail. Taken together, these conclusions call into question the conventional ideologies that have traditionally animated the debate on whether the pharmaceutical industry has special duties of beneficence and distributive justice with respect to the impoverished in dire need of their products. (shrink)

The concepts of placebos and placebo effects refer to extremely diverse phenomena. I recommend dissolving the concepts of placebos and placebo effects into loosely related groups of specific mechanisms, including (potentially among others) expectation-fulfillment, classical conditioning, and attentional-somatic feedback loops. If this approach is on the right track, it has three main implications for the ethics of informed consent. First, because of the expectation-fulfillment mechanism, the process of informing cannot be considered independently from the potential effects of treatment. Obtaining informed (...) consent influences the effects of treatment. This provides support for the authorized concealment and authorized deception paradigms, and perhaps even for outright deceptive placebo use. Second, doctors may easily fail to consider the potential benefits of conditioning, leading them to misjudge the trade-off between beneficence and autonomy. Third, how attentional-somatic feedback loops play out depends not only on the content of the informing process but also on its framing. This suggests a role for libertarian paternalism in clinical practice. (shrink)

Political theorists have offered many accounts of collective decision-making under pluralism. I discuss a key dimension on which such accounts differ: the importance assigned not only to the choices made but also to the reasons underlying those choices. On that dimension, different accounts lie in between two extremes. The ‘minimal liberal account’ holds that collective decisions should be made only on practical actions or policies and that underlying reasons should be kept private. The ‘comprehensive deliberative account’ stresses the importance of (...) giving reasons for collective decisions, where such reasons should also be collectively decided. I compare these two accounts on the basis of a formal model developed in the growing literature on the ‘discursive dilemma’ and ‘judgment aggregation’ and address several questions: What is the trade-off between the (minimal liberal) demand for reaching agreement on outcomes and the (comprehensive deliberative) demand for reason-giving? How large should the ‘sphere of public reason’ be? When do the decision procedures suggested by the two accounts agree and when not? How good are these procedures at truthtracking on factual matters? What strategic incentives do they generate for decision-makers? My discussion identifies what is at stake in the choice between minimal liberal and comprehensive deliberative accounts of collective decisionmaking, and sheds light not only on these two ideal-typical accounts themselves, but also on many characteristics that intermediate accounts share with them. (shrink)

The birth of a new science is long, drawn out, and often fairly messy. Comparative psychology has its roots in Darwin’s Descent of Man, was fertilized in academic psychology departments, and has branched across the universities into departments of biology, anthropology, primatology, zoology, and philosophy. Both the insights and the failings of comparative psychology are making their way into contemporary discussions of artificial intelligence and machine learning (Chollett 2019; Lapuschkin et al. 2019; Watson 2019). It is the right time to (...) turn a philosophical lens onto the methodologies of comparative psychology. That is the aim of this Element. -/- Comparative psychology is the umbrella covering the different ways scientists study animal mind and behavior. Comparative psychologists study animal behavior and mentality, including the mechanisms and inner states that allow crows to form hooks, vervet monkeys to give warnings, crabs to make trade-off decisions, and humans to use language. While focus is on the similarities and differences between different species, capacities are often studied in terms of their evolutionary history, development, and current ecological or cultural context. What this entails is that comparative psychologists have a range of different kinds of training, different areas of expertise, and different research questions. One comparative cognition researcher compares children and dogs on causal reasoning abilities (Daphna Buchsbaum), another looks at memory in corvids (Nicola Clayton). An animal behaviorist examines raccoon territories in a city (Suzanne MacDonald). One anthropologist looks at war in wild chimpanzees (John Mitani), another looks at how innovations are adopted in capu- chin monkeys (Susan Perry). One ethologist looks at play in wolves (Marc Bekoff), and another looks at deception in birds (Carolyn Ristau). One biologist looks at male alliances in dolphins (Richard Connor), and another examines economic game performance in apes and monkeys (Sarah Brosnan). An animal welfare scientist studies the effect of enrichment on mink (Georgia Mason). A learning theorist looks at gambling in pigeons (Thomas Zentall). A zoologist studies social learning in bees (Lars Chittka). It is not easy to guess in which department you’ll find a comparative psychologist. -/- This Element aims to examine the methods of comparative psychology, which remains especially concerned about how to study animal minds and behavior without falling prey to fuzzy thinking. Animals can be cute, so humans are often intrinsically drawn to them; and this love of animals is sometimes taken to be at odds with being a careful scientist. The methods of comparative psychology reflect this worry with their special emphases on avoiding bias and on avoiding developing warm relationships with animal subjects. The first two sections analyze three textbooks to examine what young scientists are taught. Section 1 investigates three methodological principles students are taught to follow: Anti-anthropomorphism, Morgan’s Canon, and Anti-anthropocentrism. I argue that the first two principles should be discarded, and that developing relationships with animals should no longer be discouraged, as relationships promote understanding. Building on this critique, in Section 2 I challenge the common prohibition against including animal consciousness in comparative psychology by arguing that it does not harm the science, but promotes it. Setting aside the special prohibitions for comparative psychology, in Section 3 I examine how the quest for objectivity in comparative psychology introduces its own bias and argue that the different disciplines of comparative psychology will introduce different biases; the best scientists can do is identify the sources of bias. The quest to eliminate all bias is a misguided one. Section 4 applies these issues to recent debates in ape cognition research between scientists who work in the field and those who work in the lab, and suggests best practices for integrating knowledge from both sources. -/- I have had the opportunity to work with a number of comparative psychologists in a variety of contexts, including a stint at Lou Herman’s dolphin communication lab in the 1990s, collaborative studies with Peter Verbeek on the child’s theory of mind at the University of Minnesota’s Institute for Child Development, conducting research on orangutan pantomime communication with Anne Russon at her field sites in Borneo, research on rat social learning with Noam Miller at Wilfrid Laurier University, and co-teaching a field course in dolphin communication with Kathleen Dudzinski. As a philosopher of science who has been in the field and in the lab, I have a perspective from which to compare the comparative psychologists. This Element is my attempt to synthesize almost thirty years of experience and thinking about how to study animal minds. (shrink)

Nearly everyone prefers pain to be in the past rather than the future. This seems like a rationally permissible preference. But I argue that appearances are misleading, and that future-biased preferences are in fact irrational. My argument appeals to trade-offs between hedonic experiences and other goods. I argue that we are rationally required to adopt an exchange rate between a hedonic experience and another type of good that stays fixed, regardless of whether the hedonic experience is in the past (...) or future. (shrink)

Many of the moral and political disputes that loom large today involve claims (1) in the register of respect and offense that are (2) linked to membership in a subordinated social group and (3) occasioned by symbolic or expressive items or acts. This essay seeks to clarify the nature, stakes, and characteristic challenges of these recurring, but often disorienting, conflicts. Drawing on a body of philosophical work elaborating the moral function of etiquette, I first argue that the claims at issue (...) implicate a communicative apparatus of the same basic kind—a system that I term the “etiquette of equality.” That regime, I suggest, can serve a kindred function of facilitating the expression of morally appropriate attitudes. I also argue, however, that the etiquette of equality exhibits three problematic features that counsel ambivalence about its mounting significance: (1) the costly overdetermination of relevant signals; (2) a recursive tendency toward inflation in respect’s demands; and (3) a related set of incentives for testing, and then affirming, a group’s status through the assertion and symbolic remediation of dignitary harm. The upshot is a better understanding of the trade-offs and predicaments we face in a vital area of public life. (shrink)

I explain the shutdown problem: the problem of designing artificial agents that (1) shut down when a shutdown button is pressed, (2) don’t try to prevent or cause the pressing of the shutdown button, and (3) otherwise pursue goals competently. I prove three theorems that make the difficulty precise. These theorems show that agents satisfying some innocuous-seeming conditions will often try to prevent or cause the pressing of the shutdown button, even in cases where it’s costly to do so. And (...) patience trades off against shutdownability: the more patient an agent, the greater the costs that agent is willing to incur to manipulate the shutdown button. I end by noting that these theorems can guide our search for solutions. (shrink)

Definition of the problem The umbrella term “explicability” refers to the reduction of opacity of artificial intelligence (AI) systems. These efforts are challenging for medical AI applications because higher accuracy often comes at the cost of increased opacity. This entails ethical tensions because physicians and patients desire to trace how results are produced without compromising the performance of AI systems. The centrality of explicability within the informed consent process for medical AI systems compels an ethical reflection on the trade-offs. (...) Which levels of explicability are needed to obtain informed consent when utilizing medical AI? Arguments We proceed in five steps: First, we map the terms commonly associated with explicability as described in the ethics and computer science literature, i.e., disclosure, intelligibility, interpretability, and explainability. Second, we conduct a conceptual analysis of the ethical requirements for explicability when it comes to informed consent. Third, we distinguish hurdles for explicability in terms of epistemic and explanatory opacity. Fourth, this then allows to conclude the level of explicability physicians must reach and what patients can expect. In a final step, we show how the identified levels of explicability can technically be met from the perspective of computer science. Throughout our work, we take diagnostic AI systems in radiology as an example. Conclusion We determined four levels of explicability that need to be distinguished for ethically defensible informed consent processes and showed how developers of medical AI can technically meet these requirements. (shrink)

Safe-by-Design (SBD) frameworks for the development of emerging technologies have become an ever more popular means by which scholars argue that transformative emerging technologies can safely incorporate human values. One such popular SBD methodology is called Value Sensitive Design (VSD). A central tenet of this design methodology is to investigate stakeholder values and design those values into technologies during early stage research and development (R&D). To accomplish this, the VSD framework mandates that designers consult the philosophical and ethical literature to (...) best determine how to weigh moral trade-offs. However, the VSD framework also concedes the universalism of moral values, particularly the values of freedom, autonomy, equality trust and privacy justice. This paper argues that the VSD methodology, particularly applied to nano-bio-info-cogno (NBIC) technologies, has an insufficient grounding for the determination of moral values. As such, an exploration of the value-investigations of VSD are deconstructed to illustrate both its strengths and weaknesses. This paper also provides possible modalities for the strengthening of the VSD methodology, particularly through the application of moral imagination and how moral imagination exceed the boundaries of moral intuitions in the development of novel technologies. (shrink)

In 2012, the Geological Time Scale, which sets the temporal framework for studying the timing and tempo of all major geological, biological, and climatic events in Earth’s history, had one-quarter of its boundaries moved in a widespread revision of radiometric dates. The philosophy of metrology helps us understand this episode, and it, in turn, elucidates the notions of calibration, coherence, and consilience. I argue that coherence testing is a distinct activity preceding calibration and consilience, and I highlight the value of (...) discordant evidence and trade-offs scientists face in calibration. The iterative nature of calibration, moreover, raises the problem of legacy data. (shrink)

There is a long-standing debate in philosophy about whether it is morally permissible to harm one person in order to prevent a greater harm to others and, if not, what is the moral principle underlying the prohibition. Hypothetical moral dilemmas are used in order to probe moral intuitions. Philosophers use them to achieve a reflective equilibrium between intuitions and principles, psychologists to investigate moral decision-making processes. In the dilemmas, the harms that are traded off are almost always deaths. However, the (...) moral principles and psychological processes are supposed to be broader than this, encompassing harms other than death. Further, if the standard pattern of intuitions is preserved in the domain of economic harm, then that would open up the possibility of studying behaviour in trolley problems using the tools of experimental economics. We report the results of two studies designed to test whether the standard patterns of intuitions are preserved when the domain and severity of harm are varied. Our findings show that the difference in moral intuitions between bystander and footbridge scenarios is replicated across different domains and levels of physical and non-physical harm, including economic harms. (shrink)

In this article we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change and it contribute to combating the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and the (...) contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI’s greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combating climate change, while reducing its impact on the environment. (shrink)