Automated decision making for sentencing is the use of a software algorithm to analyse a convicted offender’s case and deliver a sentence. This chapter reviews the moral arguments for and against employing automated decision making for sentencing and finds that its use is in principle morally permissible. Specifically, it argues that well-designed automated decision making for sentencing will better approximate the just sentence than human sentencers. Moreover, it dismisses common concerns about (...) transparency, privacy and bias as unpersuasive or inapplicable. The chapter also notes that moral disagreement about theories of just sentencing are plausibly resolved by applying the principle of maximising expected moral choiceworthiness, and that automated decision making is better suited to the resulting ensemble model. Finally, the chapter considers the challenge posed by penal populism. The dispiriting conclusion is that although it is in theory morally desirable to use automated decision-making for criminal sentencing, it may well be the case that we ought not to try. (shrink)

Important decisions that impact humans lives, livelihoods, and the natural environment are increasingly being automated. Delegating tasks to so-called automated decision-making systems can improve efficiency and enable new solutions. However, these benefits are coupled with ethical challenges. For example, ADMS may produce discriminatory outcomes, violate individual privacy, and undermine human self-determination. New governance mechanisms are thus needed that help organisations design and deploy ADMS in ways that are ethical, while enabling society to reap the full economic (...) and social benefits of automation. In this article, we consider the feasibility and efficacy of ethics-based auditing as a governance mechanism that allows organisations to validate claims made about their ADMS. Building on previous work, we define EBA as a structured process whereby an entity’s present or past behaviour is assessed for consistency with relevant principles or norms. We then offer three contributions to the existing literature. First, we provide a theoretical explanation of how EBA can contribute to good governance by promoting procedural regularity and transparency. Second, we propose seven criteria for how to design and implement EBA procedures successfully. Third, we identify and discuss the conceptual, technical, social, economic, organisational, and institutional constraints associated with EBA. We conclude that EBA should be considered an integral component of multifaced approaches to managing the ethical risks posed by ADMS. (shrink)

Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. (...) In contrast to the right to explanation of specific automated decisions claimed elsewhere, the GDPR only mandates that data subjects receive meaningful, but properly limited, information (Articles 13-15) about the logic involved, as well as the significance and the envisaged consequences of automated decision-making systems, what we term a ‘right to be informed’. Further, the ambiguity and limited scope of the ‘right not to be subject to automated decision-making’ contained in Article 22 (from which the alleged ‘right to explanation’ stems) raises questions over the protection actually afforded to data subjects. These problems show that the GDPR lacks precise language as well as explicit and well-defined rights and safeguards against automated decision-making, and therefore runs the risk of being toothless. We propose a number of legislative and policy steps that, if taken, may improve the transparency and accountability of automated decision-making when the GDPR comes into force in 2018. (shrink)

The ongoing explosion of interest in artificial intelligence is fueled in part by recently developed techniques in machine learning. Those techniques allow automated systems to process huge amounts of data, utilizing mathematical methods that depart from traditional statistical approaches, and resulting in impressive advancements in our ability to make predictions and uncover correlations across a host of interesting domains. But as is now widely discussed, the way that those systems arrive at their outputs is often opaque, even to the (...) experts who design and deploy them. Is it morally problematic to make use of opaque automated methods when making high-stakes decisions, like whether to issue a loan to an applicant, or whether to approve a parole request? Many scholars answer in the affirmative. However, there is no widely accepted explanation for why transparent systems are morally preferable to opaque systems. We argue that the use of automated decision-making systems sometimes violates duties of consideration that are owed by decision-makers to decision-subjects, duties that are both epistemic and practical in character. Violations of that kind generate a weighty consideration against the use of opaque decision systems. In the course of defending our approach, we show that it is able to address three major challenges sometimes leveled against attempts to defend the moral import of transparency in automated decision-making. (shrink)

Computers are used to make decisions in an increasing number of domains. There is widespread agreement that some of these uses are ethically problematic. Far less clear is where ethical problems arise, and what might be done about them. This paper expands and defends the Ethical Gravity Thesis: ethical problems that arise at higher levels of analysis of an automated decision-making system are inherited by lower levels of analysis. Particular instantiations of systems can add new problems, but (...) not ameliorate more general ones. We defend this thesis by adapting Marr’s famous 1982 framework for understanding information-processing systems. We show how this framework allows one to situate ethical problems at the appropriate level of abstraction, which in turn can be used to target appropriate interventions. (shrink)

The era of AI-based decision-making fast approaches, and anxiety is mounting about when, and why, we should keep “humans in the loop” (“HITL”). Thus far, commentary has focused primarily on two questions: whether, and when, keeping humans involved will improve the results of decision-making (making them safer or more accurate), and whether, and when, non-accuracy-related values—legitimacy, dignity, and so forth—are vindicated by the inclusion of humans in decision-making. Here, we take up a related (...) but distinct question, which has eluded the scholarship thus far: does it matter if humans appear to be in the loop of decision-making, independent from whether they actually are? In other words, what is stake in the disjunction between whether humans in fact have ultimate authority over decision-making versus whether humans merely seem, from the outside, to have such authority? Our argument proceeds in four parts. First, we build our formal model, enriching the HITL question to include not only whether humans are actually in the loop of decision-making, but also whether they appear to be so. Second, we describe situations in which the actuality and appearance of HITL align: those that seem to involve human judgment and actually do, and those that seem automated and actually are. Third, we explore instances of misalignment: situations in which systems that seem to involve human judgment actually do not, and situations in which systems that hold themselves out as automated actually rely on humans operating “behind the curtain.” Fourth, we examine the normative issues that result from HITL misalignment, arguing that it challenges individual decision-making about automated systems and complicates collective governance of automation. (shrink)

One recent priority of the U.S. government is developing autonomous robotic systems. The U.S. Army has funded research to design a metric of evil to support military commanders with ethical decision-making and, in the future, allow robotic military systems to make autonomous ethical judgments. We use this particular project as a case study for efforts that seek to frame morality in quantitative terms. We report preliminary results from this research, describing the assumptions and limitations of a program that (...) assesses the relative evil of two courses of action. We compare this program to other attempts to simulate ethical decision-making, assess possibilities for overcoming the trade-off between input simplification and output reliability, and discuss the responsibilities of users and designers in implementing such programs. We conclude by discussing the implications that this project highlights for the successes and challenges of developing automated mechanisms for ethical decision making. (shrink)

Many seem to think that AI-induced responsibility gaps are morally bad and therefore ought to be avoided. We argue, by contrast, that there is at least a pro tanto reason to welcome responsibility gaps. The central reason is that it can be bad for people to be responsible for wrongdoing. This, we argue, gives us one reason to prefer automated decision-making over human decision-making, especially in contexts where the risks of wrongdoing are high. While we (...) are not the first to suggest that responsibility gaps should sometimes be welcomed, our argument is novel. Others have argued that responsibility gaps should sometimes be welcomed because they can reduce or eliminate the psychological burdens caused by tragic moral choice-situations. By contrast, our argument explains why responsibility gaps should sometimes be welcomed even in the absence of tragic moral choice-situations, and even in the absence of psychological burdens. (shrink)

Enterprise resource planning (ERP) has a significant impact on modern businesses by enhancing productivity, automation, and streamlining of business processes, even accounting. Manufacturers can assure proper functioning and timely client demand using ERP software. Coordination, procurement control, inventory control, and dispatch of commodities are all features of supply chain management.

Existing discussions about automated decision-making focus primarily on its inputs and outputs, raising questions about data collection and privacy on one hand and accuracy and fairness on the other. Less attention has been devoted to critically examining the temporality of decision-making processes—the speed at which automated decisions are reached. In this paper, I identify four dimensions of algorithmic speed that merit closer analysis. Duration (how much time it takes to reach a judgment), timing (when (...) automated systems intervene in the activity being evaluated), frequency (how often evaluations are performed), and lived time (the human experience of algorithmic speed) are interrelated, but distinct, features of automated decision-making. Choices about the temporal structure of automated decision-making systems have normative implications, which I describe in terms of "disruption," "displacement," "re-calibration," and "temporal fairness," with values such as accuracy, fairness, accountability, and legitimacy hanging in the balance. As computational tools are increasingly tasked with making judgments about human activities and practices, the designers of decision-making systems will have to reckon, I argue, with when—and how fast—judgments ought to be rendered. Though computers are capable of reaching decisions at incredible speeds, failing to account for the temporality of automated decision-making risks misapprehending the costs and benefits automation promises. (shrink)

While Autonomous Weapons Systems have obvious military advantages, there are prima facie moral objections to using them. By way of general reply to these objections, I point out similarities between the structure of law and morality on the one hand and of automata on the other. I argue that these, plus the fact that automata can be designed to lack the biases and other failings of humans, require us to automate the formulation, administration, and enforcement of law as much as (...) possible, including the elements of law and morality that are operated by combatants in war. I suggest that, ethically speaking, deploying a legally competent robot in some legally regulated realm is not much different from deploying a more or less well-armed, vulnerable, obedient, or morally discerning soldier or general into battle, a police officer onto patrol, or a lawyer or judge into a trial. All feature automaticity in the sense of deputation to an agent we do not then directly control. Such relations are well understood and well-regulated in morality and law; so there is not much challenging philosophically in having robots be some of these agents — excepting the implications of the limits of robot technology at a given time for responsible deputation. I then consider this proposal in light of the differences between two conceptions of law. These are distinguished by whether each conception sees law as unambiguous rules inherently uncontroversial in each application; and I consider the prospects for robotizing law on each. Likewise for the prospects of robotizing moral theorizing and moral decision-making. Finally I identify certain elements of law and morality, noted by the philosopher Immanuel Kant, which robots can participate in only upon being able to set ends and emotionally invest in their attainment. One conclusion is that while affectless autonomous devices might be fit to rule us, they would not be fit to vote with us. For voting is a process for summing felt preferences, and affectless devices would have none to weigh into the sum. Since they don't care which outcomes obtain, they don't get to vote on which ones to bring about. (shrink)

Sparrow argues that military robots capable of making their own decisions would be independent enough to allow us denial for their actions, yet too unlike us to be the targets of meaningful blame or praise—thereby fostering what Matthias has dubbed “the responsibility gap.” We agree with Sparrow that someone must be held responsible for all actions taken in a military conflict. That said, we think Sparrow overlooks the possibility of what we term “blank check” responsibility: A person of sufficiently (...) high standing could accept responsibility for the actions of autonomous robotic devices—even if that person could not be causally linked to those actions besides this prior agreement. The basic intuition behind our proposal is that humans can impute relations even when no other form of contact can be established. The missed alternative we want to highlight, then, would consist in an exchange: Social prestige in the occupation of a given office would come at the price of signing away part of one's freedoms to a contingent and unpredictable future guided by another agency. (shrink)

In recent years there has been an explosion of interest in Artificial Intelligence (AI) both in health care and academic philosophy. This has been due mainly to the rise of effective machine learning and deep learning algorithms, together with increases in data collection and processing power, which have made rapid progress in many areas. However, use of this technology has brought with it philosophical issues and practical problems, in particular, epistemic and ethical. In this paper the authors, with backgrounds in (...) philosophy, maternity care practice and clinical research, draw upon and extend a recent framework for shared decision-making (SDM) that identified a duty of care to the client's knowledge as a necessary condition for SDM. This duty entails the responsibility to acknowledge and overcome epistemic defeaters. This framework is applied to the use of AI in maternity care, in particular, the use of machine learning and deep learning technology to attempt to enhance electronic fetal monitoring (EFM). In doing so, various sub-kinds of epistemic defeater, namely, transparent, opaque, underdetermined, and inherited defeaters are taxonomized and discussed. The authors argue that, although effective current or future AI-enhanced EFM may impose an epistemic obligation on the part of clinicians to rely on such systems' predictions or diagnoses as input to SDM, such obligations may be overridden by inherited defeaters, caused by a form of algorithmic bias. The existence of inherited defeaters implies that the duty of care to the client's knowledge extends to any situation in which a clinician (or anyone else) is involved in producing training data for a system that will be used in SDM. Any future AI must be capable of assessing women individually, taking into account a wide range of factors including women's preferences, to provide a holistic range of evidence for clinical decision-making. (shrink)

It has been argued by disability advocates that supported decision-making must replace surrogate, or substituted, decision-making for people with cognitive disabilities. From a moral perspective surrogate decision-making it is said to be an indefensible form of paternalism. At the heart of this argument against surrogate decision-making is the belief that such paternalistic action expresses something fundamentally disrespectful about those upon whom it is imposed: that they are inferior, deficient or child-like in some (...) way. Contrary to this widespread belief, I will argue that surrogate decision-making sometimes expresses more respect for people with life-long, ‘severe’ or ‘profound’ cognitive disabilities than does the adoption of supported decision-making.. Specifically, I argue that in some cases supported decision-making can arguably express that people with severe or profound cognitive disabilities lack equal moral value. I also argue that supported decision-making for people with profound cognitive disabilities can arguably express that they lack complex and rich inner lives. If our aim is to ensure our behaviour and practices express respect for people with life-long ‘severe’ or ‘profound’ cognitive disabilities, then sometimes surrogate rather than supportive decision-making will be a better option. (shrink)

Decision-making capacity (DMC) plays an important role in clinical practice—determining, on the basis of a patient’s decisional abilities, whether they are entitled to make their own medical decisions or whether a surrogate must be secured to participate in decisions on their behalf. As a result, it’s critical that we get things right—that our conceptual framework be well-suited to the task of helping practitioners systematically sort through the relevant ethical considerations in a way that reliably and transparently delivers correct (...) verdicts about who should and should not have the authority to make their own medical decisions. Unfortunately, however, the standard approach to DMC does not get things right. It is of virtually no help in identifying and clarifying the relevant ethical considerations. And, embedded in the prevailing anti-paternalist paradigm, DMC assessments obfuscate and distort the underlying ethical justification for granting or withholding decisional authority. Here, we describe the core commitments of the standard approach to DMC and then highlight three problems with it. We then argue that these problems are significant enough that they call for more than merely tinkering and fine tuning—variations of the standard approach cannot adequately address them. Instead, we should ditch DMC. (shrink)

Decision-making Capacity matters to whether a patient’s decision should determine her treatment. But why it matters in this way isn’t clear. The standard story is that dmc matters because autonomy matters. And this is thought to justify dmc as a gatekeeper for autonomy – whereby autonomy concerns arise if but only if a patient has dmc. But appeals to autonomy invoke two distinct concerns: concern for authenticity – concern that a choice is consistent with an individual’s commitments; (...) and concern for sovereignty – concern that an individual exercises control over that which is hers to control. Here, I argue, neither concern can alone explain why dmc matters. Instead, dmc matters because it indicates a harmony between the two concerns – the demands of each concern are more likely to agree if a patient has dmc. This vindicates the standard story, but also makes clear that dmc is an inappropriate gatekeeper for autonomy. (shrink)

This article is about the information relevant to decision-making capacity in refusal of life-prolonging medical treatment cases. We examine the degree to which the phenomenology of the options available to the agent—what the relevant states of affairs will feel like for them—forms part of the capacity-relevant information in the law of England and Wales, and how this informational basis varies across adolescent and adult medical treatment cases. We identify an important doctrinal phenomenon. In the leading authorities, the courts (...) appear to count the first-personal phenomenology of the available options among the information that adolescents seeking to refuse life-prolonging treatment must understand and appreciate in order to possess capacity; adults are not held to this (higher) standard. We evaluate this differential treatment in light of philosophical work on transformative choice—decisions involving options whose sensory character, and effect on our values and preferences, are grasped only through experience itself. (shrink)

This book is concerned with helping you improve your approach to decision-making. The author examines judgement in a selection of managerial contexts and provides important understanding that can help you make better leadership decisions. The book also pinpoints the in-house politics of organisational decision-making. Drawing on the very latest research, it introduces practical techniques that show you how to analyse and develop your own decision-making style. It will help you to deliver sharp and insightful (...) analyses of your business and develop effective solutions. In addition, it presents simple checklists that will give you vital insights throughout the decision-making process. Students and practitioners of leadership, management, and allied fields will find this book useful in order to understand and implement useful methods. (shrink)

Recently, bioethicists and the UNCRPD have advocated for supported medical decision-making on behalf of patients with intellectual disabilities. But what does supported decision-making really entail? One compelling framework is Anita Silvers and Leslie Francis’ mental prosthesis account, which envisions supported decision-making as a process in which trustees act as mere appendages for the patient’s will; the trustee provides the cognitive tools the patient requires to realize her conception of her own good. We argue that (...) supported decision-making would be better understood as a collaborative process, giving patients with intellectual disabilities the opportunity to make decisions in a respectful relationship with trusted others. We offer an alternative account of supported decision-making where the primary constraint is to protect the patient from domination by the trustee. This is advantageous in its preservation of the prospects for genuine collaboration, for the mental prosthesis approach ultimately reinforces a problematic ideal of isolated patient self-determination. (shrink)

Over the past decade, scholars, institutions, and activists have voiced strong concerns about the potential of automated decision systems to indirectly discriminate against vulnerable groups. This article analyses the ethics of algorithmic indirect discrimination, and argues that we can explain what is morally bad about such discrimination by reference to the fact that it causes harm. The article first sketches certain elements of the technical and conceptual background, including definitions of direct and indirect algorithmic differential treatment. It next (...) introduces three prominent accounts of fairness as potential explanations if the badness of algorithmic indirect discrimination, but argues that all three are vulnerable to powerful levelling-down-style objections. Instead, the article demonstrates how proper attention to the way differences in decision-scenarios affect the distribution of harms can help us account for intuitions in prominent cases. Finally, the article considers a potential objection based on the fact that certain forms of algorithmic indirect discrimination appear to distribute rather than cause harm, and notes that we can explain how such distributions cause harm by attending to differences in individual and group vulnerability. (shrink)

Sometimes citizens disagree about political matters, but a decision must be made. We have two theoretical frameworks for resolving political disagreement. The first is the framework of social choice. In it, our goal is to treat parties to the dispute fairly, and there is no sense in which some are right and the others wrong. The second framework is that of collective decision-making. Here, we do believe that preferences are truth apt, and our moral consideration is owed (...) not to those who disagree but to the community that stands to benefit or suffer from the decision. In this chapter, I describe and explore these two frameworks. I conclude two things. First, analysis of real-world disagreement suggests that collective decision-making is the right way to model politics. In most, possibly even all, political disagreement, all parties believe (if implicitly) that there is an objective standard of correctness. Second, this matter is connected to the concept of pluralism. If pluralism is true, then collective decision-making cannot be applied to some political disagreements. More surprisingly, pluralism may rule out the applicability of social choice theory as well. (shrink)

Across two studies the hypotheses were tested that stressful situations affect both leadership ethical acting and leaders' recognition of ethical dilemmas. In the studies, decision makers recruited from 3 sites of a Swedish multinational civil engineering company provided personal data on stressful situations, made ethical decisions, and answered to stress-outcome questions. Stressful situations were observed to have a greater impact on ethical acting than on the recognition of ethical dilemmas. This was particularly true for situations involving punishment and lack (...) of rewards. The results are important for the Corporate Social Responsibility (CSR) of an organization, especially with regard to the analysis of the Stressors influencing managerial work and its implications for ethical behavior. (shrink)

Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress’ prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report (...) on the difficult task of operationalizing the principles of beneficence, non-maleficence and patient autonomy, and describe how we selected suitable input parameters that we extracted from a training dataset of clinical cases. The first performance results are promising, but an algorithmic approach to ethics also comes with several weaknesses and limitations. Should one really entrust the sensitive domain of clinical ethics to machine intelligence? (shrink)

Decisions are made under uncertainty when there are distinct outcomes of a given action, and one is uncertain to which the act will lead. Decisions are made under indeterminacy when there are distinct outcomes of a given action, and it is indeterminate to which the act will lead. This paper develops a theory of (synchronic and diachronic) decision-making under indeterminacy that portrays the rational response to such situations as inconstant. Rational agents have to capriciously and randomly choose how (...) to resolve the indeterminacy relevant to a given choice-situation, but such capricious choices once made constrain how they will choose in the future. The account is illustrated by the case of self-interested action in situations where it is indeterminate whether you yourself will survive to benefit or suffer the consequences. The conclusion emphasizes some distinctive anti-hedging predictions of the account. (shrink)

In this study, we propose a new approach based on fuzzy TODIM (Portuguese acronym for interactive and multicriteria decision-making) for decision-making problems in uncertain environments. Our method incorporates group utility and individual regret, which are often ignored in traditional multicriteria decision-making (MCDM) methods. To enhance the analysis and application of fuzzy sets in decision-making processes, we introduce novel entropy and distance measures for q-rung picture fuzzy sets. These measures include an entropy measure (...) based on the sine function and a distance measure derived from the Jensen-Shannon divergence. In our methodology, incorporating the sine function into the entropy measure stands out as a distinctive decision, grounded in a profound understanding of the inherent characteristics of fuzzy sets. Utilizing the sine function proves especially advantageous when handling fuzzy sets that exhibit cyclical variations or fluctuations in their membership degrees. We effectively weight the criteria for an improved evaluation by using this new entropy measure. The introduced distance measure finds application in the TODIM approach, allowing the execution of TODIM method steps within a fuzzy environment until the determination of one alternative’s dominance over another—an advancement beyond traditional approaches. We apply our enhanced fuzzy TODIM method to a real-life construction project management problem from the literature and compare the results with those in the literature and obtained from other MCDM methods. Our proposed measures are robust, as demonstrated by the sensitivity analysis that varied the weights of group utility and individual regret, with the results visualized in a 3D sensitivity plot. The findings demonstrate the superiority of our method in providing a more comprehensive evaluation of alternatives, making it a useful tool for decision-makers facing complex and uncertain decision-making problems. (shrink)

The American justice system, from police departments to the courts, is increasingly turning to information technology for help identifying potential offenders, determining where, geographically, to allocate enforcement resources, assessing flight risk and the potential for recidivism amongst arrestees, and making other judgments about when, where, and how to manage crime. In particular, there is a focus on machine learning and other data analytics tools, which promise to accurately predict where crime will occur and who will perpetrate it. Activists and (...) academics have begun to raise critical questions about the use of these tools in policing contexts. In this chapter, I review the emerging critical literature on predictive policing and contribute to it by raising ethical questions about the use of predictive analytics tools to identify potential offenders. Drawing from work on the ethics of profiling, I argue that the much-lauded move from reactive to preemptive policing can mean wrongfully generalizing about individuals, making harmful assumptions about them, instrumentalizing them, and failing to respect them as full ethical persons. I suggest that these problems stem both from the nature of predictive policing tools and from the sociotechnical contexts in which they are implemented... (shrink)

This volume presents research that integrates decision making and creativity within the social contexts in which these processes occur. The volume is an essential addition to and expansion of recent approaches to decision making. Such approaches attempt to incorporate more of the psychological and socio-cultural context in which human decision making takes place. The authors come from different disciplines and also belong to a broad spectrum of research traditions. They present innovative chapters dealing with (...) both theoretical and empirical aspects of decision making in different personal and organizational contexts. All chapters are written from the perspective that human decision making is inherently social and more or less creative. The volume addresses fundamental questions about the nature of human decision making as it occurs in different social contexts. Thereby, it becomes essential reading for researchers in decision making and for advanced students in psychology, management science, informatics, and related disciplines. (shrink)

Abstract: This paper defends a constraint that any satisfactory decision theory must satisfy. I show how this constraint is violated by all of the decision theories that have been endorsed in the literature that are designed to deal with cases in which opinions or values are represented by a set of functions rather than a single one. Such a decision theory is necessary to account for the existence of what Ruth Chang has called “parity” (as well as (...) for cases in which agents have incomplete preferences or imprecise credences). The problem with the all of the decision theories that have been defended to account for parity is that they are committed to a claim I call unanimity: when all of the functions in the set agree that an agent ought to do A, then an agent ought to do A. A decision theory committed to unanimity violates the constraint I defend in this paper. Thus, if parity exists, a new approach to decision theory is necessary. (shrink)

Using artificial intelligence (AI) to make decisions in human resource management (HRM) raises questions of how fair employees perceive these decisions to be and whether they experience respectful treatment (i.e., interactional justice). In this experimental survey study with open-ended qualitative questions, we examine decision making in six HRM functions and manipulate the decision maker (AI or human) and decision valence (positive or negative) to determine their impact on individuals’ experiences of interactional justice, trust, dehumanization, and perceptions (...) of decision-maker role appropriate- ness. In terms of decision makers, the use of human decision makers over AIs generally resulted in better perceptions of respectful treatment. In terms of decision valence, people experiencing positive over negative decisions generally resulted in better perceptions of respectful treatment. In instances where these cases conflict, on some indicators people preferred positive AI decisions over negative human decisions. Qualitative responses show how people identify justice concerns with both AI and human decision making. We outline implications for theory, practice, and future research. (shrink)

The stakes associated with an algorithmic decision are often said to play a role in determining whether the decision engenders a right to an explanation. More specifically, “high stakes” decisions are often said to engender such a right to explanation whereas “low stakes” or “non-high” stakes decisions do not. While the overall gist of these ideas is clear enough, the details are lacking. In this paper, we aim to provide these details through a detailed investigation of what we (...) will call the “Simple Stakes Thesis”. The Simple Stakes Thesis, as it will turn out, is too simple. For even if the stakes associated with a specific one-off decision are low—and hence does not engender a right to an explanation—such decisions may nevertheless form part of a high stakes pattern or aggregate of decisions. In such cases, we argue, even a low stakes decision may engender a right to explanation. Not only does this show that the right to explanation is more demanding than so far recognized. It also shows that the stakes thesis is significantly harder to apply in practice. (shrink)

Shared decision-making involves health professionals and patients/clients working together to achieve true person-centred health care. However, this goal is infrequently realized, and most barriers are unknown. Discussion between philosophers, clinicians, and researchers can assist in confronting the epistemic and moral basis of health care, with benefits to all. The aim of this paper is to describe what shared decision-making is, discuss its necessary conditions, and develop a definition that can be used in practice to support excellence (...) in maternity care. Discussion between the authors, with backgrounds in philosophy, clinical maternity care, health care management, and maternity care research, assisted the team to confront established norms in maternity care and challenge the epistemic and moral basis of decision-making for caesarean section. The team concluded that shared decision-making must start in pregnancy and continue throughout labour and birth, with equality in discourse facilitated by the clinician. Clinicians have a duty of care for the adequacy of women's knowledge, which can only be fulfilled when relevant knowledge is offered freely and when personal beliefs and biases that may impinge on decision-making (defeaters) are disclosed. Informed consent is not shared decision-making. Key barriers include existing cultural norms of “the doctor knows best” and “patient acquiescence” that prevent defeaters being acknowledged and discussed and can lead to legal challenges, overuse of medical intervention and, in some areas, obstetric violence. Shared decision-making in maternity care can thus be defined as an enquiry by clinician and expectant woman aimed at deciding upon a course of care or none, which takes the form of a dialogue within which the clinician fulfils their duty of care to the client's knowledge by making available their complete knowledge (based on all types of evidence) and expertise, including an exposition of any relevant and recognized potential defeaters. Research to develop measurement tools is required. (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)

Kahneman's theory of two systems assumes that human decision making in Economy is based on two cognitive systems, one that is automatic, intuitive and mostly unconscious, and one that is reflexive, rational and fully conscious. The authors consider Kahneman’s approach incomplete and limited in accounting for the creativity of embodied agents grasping the opportunities afforded by physical and social environments. This limitation leads us to argue for the existence of a third system in decision making in (...) Economy, the creative intuition based on direct perception of affordances, addressing not only the dispositions and goals of agents but also the social and environmental responsibility of corporations and governments. The authors argue that the third decision-making system the authors propose implies a concept of intuition that is different from the type of association process discussed by Morewedge and Kahneman [2] and gives an example of the third system operation, the Bolsa Família in Brazil, and finding new options for the funding of similar programs. (shrink)

The application of artificial intelligence (AI) to judicial decision-making has already begun in many jurisdictions around the world. While AI seems to promise greater fairness, access to justice, and legal certainty, issues of discrimination and transparency have emerged and put liberal democratic principles under pressure, most notably in the context of bail decisions. Despite this, there has been no systematic analysis of the risks to liberal democratic values from implementing AI into judicial decision-making. This article sets (...) out to fill this void by identifying and engaging with challenges arising from artificial judicial decision-making, focusing on three pillars of liberal democracy, namely equal treatment of citizens, transparency, and judicial independence. Methodologically, the work takes a comparative perspective between human and artificial decision-making, using the former as a normative benchmark to evaluate the latter. -/- The chapter first argues that AI that would improve on equal treatment of citizens has already been developed, but not yet adopted. Second, while the lack of transparency in AI decision-making poses severe risks which ought to be addressed, AI can also increase the transparency of options and trade-offs that policy makers face when considering the consequences of artificial judicial decision-making. Such transparency of options offers tremendous benefits from a democratic perspective. Third, the overall shift of power from human intuition to advanced AI may threaten judicial independence, and with it the separation of powers. While improvements regarding discrimination and transparency are available or on the horizon, it remains unclear how judicial independence can be protected, especially with the potential development of advanced artificial judicial intelligence (AAJI). Working out the political and legal infrastructure to reap the fruits of artificial judicial intelligence in a safe and stable manner should become a priority of future research in this area. (shrink)

Albert Jonsen and Stephen Toulmin have argued that the best way to resolve complex “moral” issues in clinical settings is to focus on the details of specific cases. This approach to medical decision-making, labeled ‘casuistry’, has met with much criticism in recent years. In response to this criticism, Carson Strong has attempted to salvage much of Jonsen’s and Toulmin’s version of casuistry. He concludes that much of their analysis, including Jonsen’s further elaboration about the casuistic methodology, is on (...) the mark. In this essay, the details of Jonsen’s and Toulmin’s version of casuistry and the major criticisms against their approach to clinical decision-making are explicated. Furthermore, it is argued that Strong’s salvage efforts fail to deflect these criticisms. The upshot of this analysis, which includes a few additional criticisms, is that Jonsen’s and Toulmin’s version of casuistry is not an appropriate framework from which to resolve complex “moral” issues in clinical settings. (shrink)

This essay investigates, via the concepts of the philosophy of orientation, Annie Duke’s decision-making theory in "Thinking in Bets" and scrutinizes as to what extent one can universalize the 'orientation skill' of decision-making with regard to our everyday and professional life.

In this chapter, it is argued that some animal shelters fulfill the conditions that make triage protocols necessary, namely, the operation with limited financial budgets, space, medical resources, and staff. It is suggested that requirements presented for triage in humans can be fruitfully applied to the context of animal shelters. The focus lies on the criteria of maximizing benefit, justice, medical criteria, life-span considerations, fair decision-making, patient will, re-evaluation of triage decisions and changes in the therapeutic goal, and (...) burden of triage and staff support. The establishment of triage protocols for shelters will make the decision-making process less arbitrary, fairer, and more transparent. Furthermore, it is argued that, in situations where disagreement persist among shelter staff, an external Ethics Board could be called in to help analyze and potentially resolve some of the remaining ethical issues. (shrink)

In this paper, we define correlation coefficient measure between any two rough neutrosophic sets. We also prove some of its basic properties.. We develop a new multiple attribute group decision making method based on the proposed correlation coefficient measure. An illustrative example of medical diagnosis is solved to demonstrate the applicability and effecriveness of the proposed method.

Inspired by recent breakthroughs in predictive modeling, practitioners in both industry and government have turned to machine learning with hopes of operationalizing predictions to drive automated decisions. Unfortunately, many social desiderata concerning consequential decisions, such as justice or fairness, have no natural formulation within a purely predictive framework. In efforts to mitigate these problems, researchers have proposed a variety of metrics for quantifying deviations from various statistical parities that we might expect to observe in a fair world and offered (...) a variety of algorithms in attempts to satisfy subsets of these parities or to trade o the degree to which they are satised against utility. In this paper, we connect this approach to fair machine learning to the literature on ideal and non-ideal methodological approaches in political philosophy. The ideal approach requires positing the principles according to which a just world would operate. In the most straightforward application of ideal theory, one supports a proposed policy by arguing that it closes a discrepancy between the real and the perfectly just world. However, by failing to account for the mechanisms by which our non-ideal world arose, the responsibilities of various decision-makers, and the impacts of proposed policies, naive applications of ideal thinking can lead to misguided interventions. In this paper, we demonstrate a connection between the fair machine learning literature and the ideal approach in political philosophy, and argue that the increasingly apparent shortcomings of proposed fair machine learning algorithms reflect broader troubles faced by the ideal approach. We conclude with a critical discussion of the harms of misguided solutions, a reinterpretation of impossibility results, and directions for future research. (shrink)

Using automated systems to avoid the need for human discretion in government contexts – a scenario we call ‘rule by automation’ – can help us achieve the ideal of a free and equal society. Drawing on relational theories of freedom and equality, we explain how rule by automation is a more complete realization of the rule of law and why thinkers in these traditions have strong reasons to support it. Relational theories are based on the absence of human domination (...) and hierarchy, which automation helps us achieve. Nevertheless, there is another understanding of relational theories where what matters is the presence of valuable relationships with those in power. Exploring this further might help us see when and why we should accept human discretion. (shrink)

Phenomenology gives rise to certain ontological considerations that have far-reaching implications for standard conceptions of patient autonomy in medical ethics, and, as a result, the obligations of and to patients in clinical decision-making contexts. One such consideration is the phenomenological reduction in classical phenomenology, a core feature of which is the characterisation of our primary experiences as immediately and inherently meaningful. This paper builds on and extends the analyses of the phenomenological reduction in the works of Husserl, Heidegger, (...) and Merleau-Ponty in order to identify and explain its implications for our current understanding of the principle of respect for patient autonomy and the norms of clinical decision making. (shrink)

Prima facie, we make successful decisions as we act on and intervene in the world day-to-day. Epistemologists are often concerned with whether rationality is involved in such decision-making practices, and, if so, to what degree. Some, particularly in the post-structuralist tradition, argue that successful decision-making occurs via an existential leap into the unknown rather than via any determinant or criterion such as rationality. I call this view radical voluntarism (RV). Proponents of RV include those who subscribe (...) to a view they call Critical Complexity (CC). In this paper, I argue that CC presents a false dichotomy when it conceives of rationality in Cartesian – i.e. ideal and transcendental – terms, and then concludes that RV is the proper alternative. I then outline a pragmatist rationality informed by recent work in psychology on bounded rationality, ecological rationality, and specifically embodied rationality. Such a pragmatist rationality seems to be compatible with the tenets of post-structuralism, and can therefore replace RV in CC. (shrink)

According to many of its proponents, shared decision making ("SDM") is the right way to interpret the clinician-patient relationship because it respects patient autonomy in decision-making contexts. In particular, medical ethicists have claimed that SDM respects a patient's relational autonomy understood as a capacity that depends upon, and can only be sustained by, interpersonal relationships as well as broader health care and social conditions. This paper challenges that claim. By considering two primary approaches to relational autonomy, (...) this paper argues that standard accounts of SDM actually undermine patient autonomy. It also provides an overview of the obligations generated by the principle of respect for relational autonomy that have not been captured in standard accounts of SDM and which are necessary to ensure consistency between clinical practice and respect for patient autonomy. (shrink)

Psychopathy, which is characterized by a constellation of antisocial behavioral traits, may be subdivided on the basis of etiology: “primary” (low-anxious) psychopathy is viewed as a direct consequence of some core intrinsic deficit, whereas “secondary” (high-anxious) psychopathy is viewed as an indirect consequence of environmental factors or other psychopathology. Theories on the neurobiology of psychopathy have targeted dysfunction within ventromedial prefrontal cortex (vmPFC) as a putative mechanism, yet the relationship between vmPFC function and psychopathy subtype has not been fully explored. (...) In this study, we administered two laboratory decision-making tasks (the Ultimatum Game and the Dictator Game) to a group of prisoners (n=47) to determine whether the different subtypes of psychopathy (primary vs. secondary) are associated with characteristic patterns of economic decision-making, and furthermore, whether either subtype exhibits similar performance to patients with vmPFC lesions. Comparing primary psychopaths (n=6) to secondary psychopaths (n=6) and non-psychopaths (n=22), we found that primary psychopathy was associated with significantly lower acceptance rates of unfair Ultimatum offers and lower offer amounts in the Dictator Game. Moreover, primary psychopaths were quantitatively similar to vmPFC lesion patients in their response patterns. These results support the purported connection between psychopathy and vmPFC dysfunction, bolster the distinction between primary and secondary psychopathy, and demonstrate the utility of laboratory economic decision-making tests in differentiating clinical subgroups. (shrink)

This paper explores the defects in fuzzy (hyper) graphs (as complex (hyper) networks) and extends the fuzzy (hyper) graphs to fuzzy (quasi) superhypergraphs as a new concept.We have modeled the fuzzy superhypergraphs as complex superhypernetworks in order to make a relation between labeled objects in the form of details and generalities. Indeed, the structure of fuzzy (quasi) superhypergraphs collects groups of labeled objects and analyzes them in the form of the part to part of objects, the part of objects to (...) the whole group of objects, and the whole to the whole group of objects at the same time. We have investigated the properties of fuzzy (quasi) superhypergraphs based on any positive real number as valued fuzzy (quasi) superhypergraphs, considering the complement of valued fuzzy (quasi) superhypergraphs, the notation of isomorphism of valued fuzzy (quasi) superhypergraphs based on the permutations, and we have presented the isomorphic conditions of (self complemented) valued fuzzy (quasi) superhypergraphs. The concept of impact membership value of fuzzy (quasi) superhypergraphs is introduced in this study and it is applied in designing the real problem in the real world. Finally, the problem of business superhypernetworks is presented as an application of fuzzy valued quasi superhypergraphs in the real world. (shrink)

This text provides an introduction to the topic of rational decision making as well as a brief overview of the most common biases in judgment and decision making. "Decision Making" is relatively short (300 pages) and richly illustrated with approximately 100 figures. It is suitable for both self-study and as the basis for an upper-division undergraduate course in judgment and decision making. The book is written to be accessible to anybody with minimum (...) knowledge of mathematics (high-school level algebra and some elementary notions of set theory and probability, which are reviewed in the book). At the end of each chapter there is a collection of exercises that are grouped according to that chapter’s sections. Complete and detailed answers for each exercise are given in the last section of each chapter. The book contains a total of 121 fully solved exercises. (shrink)

What process ought to guide decision making for pediatric patients? The prevailing view is that decision making should be informed and guided by the best interest of the child. A widely discussed structural model proposed by Buchanan and Brock focuses on parents as surrogate decision makers and examines best interests as guiding and/or intervention principles. Working from two recent articles by Ross on “constrained parental autonomy” in pediatric decision making (which is grounded in (...) the Buchanan and Brock model), I discuss (supportively) features of Ross’s effort visa-vis the best interest standard. I argue that any pediatric decision-making model that brackets or formally limits an engagement with the child patient assumes too much. Further, any model that under appreciates the place of parents and their autonomy, and the dynamic parent-child relationship, misses an opportunity to broaden the clinical encounter by considering questions of justice for the child (Rawls) and within a family (Ross). In this context, I focus on the child’s emerging and ongoing emotional and intellectual development and autonomy—their capabilities and identifying primary goods. (shrink)

Research on human decision making is at the present time undergoing rapid changes. From previously being much focused on models and approaches with an origin in economy, much of the present day research finds its inspiration from disciplinary approaches concerned with incorporating more of the context that the decision making takes place in. This context includes psychological aspects of the decision maker and social-cultural aspects of the situation he or she acts in. All human (...) class='Hi'>decision making occurs in dynamically changing contexts. One factor contributing to this is that human beings or groups in many situations act as entrepreneurs trying to improve the situation for themselves or their organization. Given that this is the case, it is of increasing interest for both researchers and practitioners interested in the social aspects of decision making to consider the relation between creativity and decision making. (shrink)

What does it mean to respect autonomy and encourage meaningful consent to treatment in the case of patients who have dementia or are otherwise incompetent? This question has been thrown into sharp relief by the Law Lords' decision in R.v Bournewood Community and Mental Health NHS Trust, ex parte L.