In today’s rapidly evolving business landscape, organizations must continuously adapt to stay competitive. AI-driven human resource (HR) analytics has emerged as a strategic tool to enhance workforce agility and inform decision-making processes. By leveraging advanced algorithms, machine learning models, and predictive analytics, HR departments can transform vast data sets into actionable insights, driving talent management, employee engagement, and overall organizational efficiency. AI’s ability to analyze patterns, forecast trends, and offer data-driven recommendations empowers HR professionals to make proactive decisions in (...) hiring, skill development, performance management, and retention. (shrink)

By embracing AI-driven HR analytics, organizations can anticipate market shifts, prepare their workforce for future challenges, and stay ahead of the competition. This study outlines the essential components of AI-driven HR analytics, demonstrates its impact on workforce agility, and concludes with potential future enhancements to further optimize HR functions. Key words: Predictive Workforce Analytics, Talent Optimization, Machine Learning in.

In today’s rapidly evolving business landscape, organizations must continuously adapt to stay competitive. AI-driven human resource (HR) analytics has emerged as a strategic tool to enhance workforce agility and inform decision-making processes. By leveraging advanced algorithms, machine learning models, and predictive analytics, HR departments can transform vast data sets into actionable insights, driving talent management, employee engagement, and overall organizational efficiency. AI’s ability to analyze patterns, forecast trends, and offer data-driven recommendations empowers HR professionals to make proactive decisions in (...) hiring, skill development, performance management, and retention. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into Human Resource Management (HRM) is fundamentally transforming how organizations approach recruitment, performance management, and employee engagement. This paper explores the multifaceted impact of AI on HR practices, highlighting its role in enhancing efficiency, reducing bias, and driving strategic decision-making. Through an in-depth analysis of AI-driven recruitment tools, performance management systems, and personalized employee engagement strategies, this study examines both the opportunities and challenges associated with AI in HRM. Ethical considerations, including data (...) privacy, algorithmic bias, and the potential displacement of human jobs, are critically discussed to provide a balanced perspective on the adoption of AI technologies in the HR domain. By presenting case studies of organizations successfully leveraging AI, this paper offers insights into the future trajectory of HRM in an increasingly AI-driven world. Ultimately, the findings underscore the need for HR professionals to adapt and innovate in response to the growing influence of AI, ensuring a harmonious balance between technological advancement and the human element in the workplace. (shrink)

This paper explores the application of AI-driven HR analytics in shaping workforce agility, focusing on how real-time data collection, analysis, and modeling foster an adaptable workforce. It highlights the role of predictive analytics in forecasting workforce needs, identifying skill gaps, and optimizing talent deployment. Additionally, the paper discusses how AI enhances strategic decision-making by providing precise metrics and insights into employee behavior, productivity, and satisfaction. The integration of AI into HR systems ultimately shifts HR from a traditionally reactive to (...) a highly proactive, data-driven function. (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)

In the contemporary landscape of public procurement, organizations face increasing complexities in managing procurement and vendor payment processes. This project focuses on developing a real-time procurement and vendor payment management system for North Eastern Electric Power Corporation Limited (NEEPCO), leveraging modern web technologies, including React, Node.js, Express, and SQL. The proposed system aims to centralize and automate the procurement lifecycle, enhancing operational efficiency, transparency, and compliance with government regulations. By integrating with the Government e-Marketplace (GeM), the system facilitates seamless procurement (...) from Micro and Small Enterprises (MSEs), promoting inclusivity and economic participation. The procurement data portal will provide real-time tracking of all procurement activities, from requisition to delivery, while automating workflows to reduce manual intervention and errors. The vendor payment portal will streamline payment processes, ensuring timely payments and realtime updates for vendors, thus fostering stronger relationships. Additionally, advanced analytics will be integrated into the system, enabling data-driven decision-making and improved financial management. The expected outcomes include reduced procurement cycle times, improved compliance, and enhanced vendor satisfaction. By addressing the challenges inherent in traditional procurement methods, this project will contribute significantly to NEEPCO's operational efficiency. Ultimately, the system aims to set a benchmark for procurement practices in the public sector, reinforcing the importance of adopting modern technologies to meet the demands of a dynamic marketplace. (shrink)

This paper explores the application of AI-driven HR analytics in shaping workforce agility, focusing on how real-time data collection, analysis, and modeling foster an adaptable workforce. It highlights the role of predictive analytics in forecasting workforce needs, identifying skill gaps, and optimizing talent deployment. Additionally, the paper discusses how AI enhances strategic decision-making by providing precise metrics and insights into employee behavior, productivity, and satisfaction. The integration of AI into HR systems ultimately shifts HR from a traditionally reactive to (...) a highly proactive, data-driven function. (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)

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)

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)

Abstract: The integration of Artificial Intelligence (AI) into leadership practices is rapidly transforming organizational dynamics and decision-making processes. This paper explores the ways in which AI enhances leadership effectiveness by providing data- driven insights, optimizing decision-making, and automating routine tasks. Additionally, it examines the challenges leaders face when adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to (...) offer a comprehensive overview of the opportunities AI presents for effective leadership, as well as the strategies required to address its associated challenges. (shrink)

Market crises amplify fear, disrupting rational decision-making of stock investment. This study examines the relationship between investors’ information priorities—such as intuition, company performance, technical analysis, and other factors—and their fear responses (freeze, flight, and hiding) during market crashes. Using the Bayesian Mindsponge Framework (BMF) to analyze data from 1,526 investors in China and Vietnam, the findings reveal complex dynamics. We found positive associations between investors’ prioritization of social influence and intuition for investment decision-making with being freeze (i.e., not (...) knowing what to do with the owned stock), between prioritization of professionals’ evaluation and intuition with fleeing (i.e. giving up stock investment permanently), and between prioritization of professionals’ evaluation and social influence with hiding (i.e., stopping investing in stock for a while). In contrast, prioritization of companies’ performance metrics (e.g., net profit, debt, etc.) was negatively associated with being freeze, fleeing, and hiding. Meanwhile, prioritization of professionals’ evaluation, technical analysis, and liquidity was negatively associated with being freeze, fleeing, and hiding, respectively. The study highlights the importance of disseminating transparent, accurate information through government and media channels, along with implementing financial education programs, to promote rational investment decisions and reduce fear-driven behaviors. (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)

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)

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)

There is wide consensus among bioethicists about the importance of autonomy when determining whether or not a patient has the right to refuse life-saving treatment (LST). In this context, autonomy has typically been understood in terms of the patient’s ability to make an informed decision. According to the traditional view, decision-making capacity (DMC) is seen as both necessary and sufficient for the right to refuse LST. Recently, this view has been challenged by those who think that considerations of (...) authenticity and putative counterexamples should lead us to revise the traditional account. In this paper, we respond to these revisionist arguments, and we defend the traditional view according to which we have autonomy-based reasons to respect a patient’s decision to refuse LST if and only if she has DMC. (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)

Algorithm Decision Making (ADM) systems designed to augment or automate human decision-making have the potential to produce better decisions while also freeing up human time and attention for other pursuits. For this potential to be realised, however, algorithmic decisions must be sufficiently aligned with human goals and interests. We take a Principal-Agent (P-A) approach to the questions of ADM alignment and trust. In a broad sense, ADM is beneficial if and only if human principals can trust algorithmic agents (...) to act faithfully on their behalf. This mirrors the challenge of facilitating P-A relationships among humans, but the peculiar nature of human-machine interaction also raises unique issues. The problem of asymmetric information is omnipresent but takes a different form in the context of ADM. Although the decision-making machinery of an algorithmic agent can in principle be laid bare for all to see, the sheer complexity of ADM systems based on deep learning models prevents straightforward monitoring. We draw on literature from economics and political science to argue that the problem of trust in ADM systems should be addressed at the level of institutions. Although the dyadic relationship between human principals and algorithmic agents is our ultimate concern, cooperation at this level must rest against an institutional environment which allows humans to effectively evaluate and choose among algorithmic alternatives. (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)

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)

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)

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)

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)

The Comprehensive Human Decision-Making Equation presents a robust model for understanding Holistic Free Will (HFW), conceptualizing decision-making as an autonomous, non-deterministic process within a complex network of influences. This model addresses the Infinite Regress issue by portraying free will as an emergent property of interacting layers, including internal beliefs, external contexts, emotional responses, cognitive biases, and habitual tendencies. Departing from traditional linear models, the equation adopts a systemic framework where each choice reflects a cumulative utility, integrating multiple components (...) such as personal, ethical, social, and temporal utilities. This holistic approach emphasizes the probabilistic nature of free will, challenging deterministic interpretations and highlighting the ethical and relational dimensions of autonomy. By situating free will within a structured yet adaptive process, the model supports the notion that true autonomy is ethically aligned, relational, and embedded in a flexible reality, thereby promoting communal and ethical development. (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)

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)

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)

Abstract: Artificial Intelligence (AI) has rapidly advanced, offering significant potential to transform business decision-making. This paper delves into how AI can be harnessed to enhance strategic decision-making within business contexts. It investigates the integration of AI-driven analytics, predictive modeling, and automation, emphasizing their role in improving decision accuracy and operational efficiency. By examining current applications and case studies, the paper underscores the opportunities AI offers, including improved data insights, risk management, and personalized customer experiences. It also addresses (...) the challenges businesses face when adopting AI, such as data privacy concerns, integration difficulties, and the need for skilled professionals. The paper concludes by offering recommendations for successfully implementing AI solutions to maximize benefits while mitigating potential challenges. (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)

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.

I identify an undertheorized problem with decisions we make with the aid of algorithms: the problem of inauthenticity. When we make decisions with the aid of algorithms, we can make ones that go against our commitments and values in a normatively important way. In this paper, I present a framework for algorithm-aided decision-making that can lead to inauthenticity. I then construct a taxonomy of the features of the decision environment that make such outcomes likely, and I discuss three (...) possible solutions to the problem. (shrink)

Abstract: Artificial Intelligence (AI) has rapidly evolved, offering transformative capabilities for business decision-making. This paper explores how AI can be leveraged to enhance strategic decision-making in business contexts. It examines the integration of AI-driven analytics, predictive modeling, and automation to improve decision accuracy and operational efficiency. By analyzing current applications and case studies, the paper highlights the opportunities AI presents, including enhanced data insights, risk management, and personalized customer experiences. Additionally, it addresses the challenges businesses face in (...) adopting AI, such as data privacy concerns, integration issues, and the need for skilled personnel. The paper concludes with recommendations for effectively implementing AI solutions to maximize their benefits while navigating potential pitfalls. (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)

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)

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)

Jennifer Hawkins (2024) offers two cases that challenge traditional accounts of decision-making capacity, according to which respect for a medical decision turns on an individual’s cognitive capacities at the time the decision is made (Hawkins 2024; Appelbaum and Grisso 1988). In each of her described cases (involving anorexia nervosa and grief, respectively), a patient makes a decision that—although instrumentally rational at the time—does not reflect the patient’s longer-term values due to being in a particular psychological state. (...) Importantly, this state does not impair the patient’s cognition, but rather predisposes them to make a decision that conflicts with their own broader values, beliefs, or desires. (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.

Management decision-making is a daily task that managers of various levels solve in every organization. Degree of difficulty of this process depends on the scope of authority, responsibility level, manager’s position in organizational hierarchy; on the changes in the environment, unpredictability of which causes emergence of significant amounts of alternatives. For this reason, managers do not rely only on intuition or personal experience (which limited with selective perception, cognitive ability, ability to withstand stress and/or the presence of bias), but (...) use tools (methods) that have stood the test of time and practice; are based at the analysis of a significant amount of primary and secondary information; involve team-building to find the optimal option or to generate ideas. A significant amount of research papers are devoted to such methods, however, the author forms a synergetic approach which contains a detailed analysis of their correlation with the key factors of the competitiveness of enterprise, such as organizational culture and leadership. Existing decision-making practices, problems and style of management at the tourism enterprises are revealed from conducted survey (the first half of 2014) in tourism firms of Dnepropetrovsk and Zaporizhzhia regions of Ukraine, in which 729 tourism managers took part. The most popular decision-making practices in tourism branch were specified, among them are modeling and monitoring of previous results. The study proved the hypothesis of the author concerning strong connection of decision-making management and type of organizational culture. Moreover, 63% of managers were dissatisfied with low attention to organizational culture at their companies. The basis for future research and the synergetic matrix for decision-making management were worked out in the article which give preconditions for further studies and improvements in tourism management of Ukrainian enterprises. (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)

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 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)

Shared Decision Making (‘SDM’) is one of the most significant developments in Western health care practices in recent years. Whereas traditional models of care operate on the basis of the physician as the primary medical decision maker, SDM requires patients to be supported to consider options in order to achieve informed preferences by mutually sharing the best available evidence. According to its proponents, SDM is the right way to interpret the clinician-patient relationship because it fulfils the ethical imperative (...) of respecting patient autonomy. However, there is no consensus about how decisions in SDM contexts relate to the principle of respect for autonomy. In response, I demonstrate that in order to make decisions about what treatment they will or will not receive, patients will be required to meet different conditions depending on the approach proponents of SDM take to understanding personal autonomy. Due to the fact that different conceptions of autonomy yield different obligations, I argue that if physicians and patients satisfied all the conditions described in standard accounts of SDM, then SDM would undermine patient autonomy. (shrink)

The study aimed to identify the reality of decision-making in the local NGOs in Gaza Strip. In order to achieve the objectives of the study and to test its hypotheses, the analytical descriptive method was used, relying on the questionnaire as a main tool for data collection. The study society was one of the decision makers in the local NGOs in Gaza Strip. The study population reached 78 local NGOs in Gaza Strip. A Census Method of the possible (...) study community was adopted, and the use of the Statistical Package for Social Sciences (SPSS) was mainly based on the analysis and analysis of the data obtained through the survey tool. The study reached a set of results, the most important of which are: NGOs follow a decision-making mechanism. NGOs examine the problems and causes of the organization. Organizations are less concerned with stakeholder participation. Make decision. The main recommendations of the study are: To promote systematic methods of decision-making in NGOs in Gaza Strip: Local NGOs in Gaza Strip should continue to develop their competencies in order to make sound and correct decisions and encourage them to follow the scientific methodologies in the mechanism of taking Decisions. (shrink)

In this paper, multi attribute decision making problem based on grey relational analysis in neutrosophic cubic set environment is investigated. In the decision making situation, the attribute weights are considered as single valued neutrosophic sets. The neutrosophic weights are converted into crisp weights. Both positve and negative GRA coefficients, and weighted GRA coefficients are determined. Hamming distances for weighted GRA coefficients and standard (ideal) GRA coefficients are determined. The relative closeness coefficients are derived in order to rank the (...) alternatives. The relative closeness coefficients are designed in ascending order. Finally, a numerical example is solved to demonstrate the applicability of the proposed approach. (shrink)

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)

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)

This paper examines the relationship of ethical decision-making by individuals to corporate business ethics and organizational performance of three groups: SMEs, Outstanding SMEs and Large Enterprises, in order to provide a reference for Taiwanese entrepreneurs to practice better business ethics. The survey method involved random sampling of 132 enterprises within three groups. Some 524 out of 1320 questionnaires were valid. The survey results demonstrated that ethical decision-making by individuals, corporate business ethics and organizational performance are highly related. In (...) summary, then, high levels of organizational performance were directly attributable to high levels of applied corporate and individual ethics. Furthermore, there is a demonstrable tendency for Outstanding SMEs to reject ethically unsound practices such as padded expense accounts, tax evasion and misleading advertising. The measurement criteria used to assess organizational performance, however, did not include an objective evaluation of financial performance. (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)