Decision Procedure Research Articles

Moral uncertainty for consequentialists

Abstract How might an agent's moral uncertainty affect what they ought to do? One approach posits principles independent of all first-order moral theories to provide impartial guidance to those uncertain about which moral theory is true; a popular candidate is the principle of maximizing expected choiceworthiness (MEC). Another approach focuses on what first-order moral theories themselves might say about the moral implications of moral uncertainty. This paper considers the latter question in the context of consequentialism by exploring how two consequentialist strategies for dealing with non-moral uncertainty could be extended to moral uncertainty. My conclusion is that a consequentialist could plausibly adopt maximizing expected goodness as a standard of rightness, but not MEC, and that neither is likely to be part of the best consequentialist decision procedure. This result refutes the common suspicion that MEC represents a distinctively consequentialist approach to moral uncertainty.

Optimizing Student Management Strategies and Student Engement in Vocational Technical Colleges

This research aimed to assess the efficacy of student management practices and their influence on academic engagement among vocational-technical students in China. The study evaluated crucial aspects such as the admissions procedure, student assistance programs, attendance tracking, and technology to pinpoint obstacles and potential areas for improvement. Data was gathered using quantitative approach to assess their perspectives on management practices and academic involvement. The results indicated that using technology had a beneficial effect on student involvement. However, there were notable areas for improvement, such as student support services, attendance tracking, and the admissions process. The student support services were deemed unsatisfactory, with restricted availability and inadequate influence on academic achievements. The attendance tracking system was operational, but it did not impact student participation. On the other hand, the admissions procedure was equitable, but it lacked individualized assistance for students. Furthermore, the research revealed that students had modest intrinsic motivation, self-regulated learning, and goal-setting. Nevertheless, the level of academic aid provided needed to be improved, and the potential for collaborative learning was not fully realized due to participation difficulties. The study revealed that the mental health care provided was insufficient, and the inflexible academic schedule hindered students’ capacity to engage in interdisciplinary studies or modify their course loads based on individual circumstances. In addition, students expressed a lack of participation in decision-making procedures, which led to feelings of disconnection.

Procedural fairness in algorithmic decision-making: the role of public engagement

AbstractDespite the widespread use of automated decision-making (ADM) systems, they are often developed without involving the public or those directly affected, leading to concerns about systematic biases that may perpetuate structural injustices. Existing formal fairness approaches primarily focus on statistical outcomes across demographic groups or individual fairness, yet these methods reveal ambiguities and limitations in addressing fairness comprehensively. This paper argues for a holistic approach to algorithmic fairness that integrates procedural fairness, considering both decision-making processes and their outcomes. Procedural fairness emphasizes the importance of fair decision-making procedures, which aligns with theories of relational justice that stress the quality of social relations and power dynamics. We highlight the need for substantive procedural fairness to ensure better outcomes and address forward-looking responsibilities. Additionally, we propose leveraging Public Engagement, a core dimension within the well-established Responsible Research and Innovation framework, to enhance procedural fairness in ADM systems. Our contribution underscores the value of Public Engagement in fostering fairer ADM processes, thereby expanding the current focus beyond technical outcome-based approaches to encompass broader procedural considerations.

A New Method for Joint Sparse DOA Estimation

To tackle the issue of poor accuracy in single-snapshot data processing for Direction of Arrival (DOA) estimation in passive radar systems, this paper introduces a method for judiciously leveraging multi-snapshot data. This approach effectively enhances the accuracy of DOA estimation and spatial angle resolution in passive radar systems. Additionally, in response to the non-convex nature of the mixed norm, we propose a hyperbolic tangent model as a replacement, transforming the problem into a directly solvable convex optimization problem. The rationality of this substitution is thoroughly demonstrated. Lastly, through a comparative analysis with existing discrete grid DOA estimation methods, we illustrate the superiority of the proposed approach, particularly under conditions of medium signal-to-noise ratio, varying numbers of snapshots, and close target angles. This method is less affected by the number of array elements, and is more usable in practices verified in real-world scenarios.

Partisan Punitive Practice in Varėna District (1944–1952)

One of the least analysed aspects of the partisan war in Lithuania between 1944 and 1953 is the punitive practice of partisans. The aim of Total Irreversible Human Loss in Lithuania Between 1944 and 1953, a programme conducted by the Special Investigation Department of the Genocide and Resistance Research Centre of Lithuania, is to explore in detail the relationship between the partisans and the population during the war, to reveal the variety of executions conducted by partisans, and to clarify the decision-making procedures of partisan organisations with respect to the population. The objectives of the programme are to carry out a complex historical-statistical study and to prepare a classification of cases and a statistical data set; to collect data on the relationship of partisan organisations with the population and on the activities of courts-martial and other partisan institutions; and to carry out historical and legal analysis of data and to assess the legitimacy, validity and effects of partisan decisions concerning the population. It is also necessary to clarify, supplement and correct errors in the Soviet era card files that are stored at the Genocide and Resistance Research Centre and serve as the database for people killed and injured by partisans. This article has been prepared on the basis of the study of death sentences, executions, and people killed in action by partisans in the period 1944–1952 in the district of Varėna, the area of former Varėna County. During the archival-historiographic study, cases of killings were examined in detail through the exploration of the circumstances, motives, and other information. An important part of the study was the analysis of partisan documents: court-martial reports, various proclamations, and warnings. The most serious areas of the punitive practices of partisans were also discussed: killings of families or minors, issues of guilt and innocence, and the circumstances of partisan warfare at the time. Between 1944 and 1952, 688 people were killed in the district of Varėna; a total of 858 recorded cases of executions or possible executions were studied. The social status of 497 victims and dates of birth of 443 victims were identified. The average age of victims was 35.6 years. Three main categories of victims can be identified: employees and officers of military and security forces (29.6%), Soviet administrative staff and employees (20.9%), and farmers and workers (a total of 30.6%; 22.1% and 8.5% respectively). Other categories by job, occupation, etc.: family members of employees of military and security organisations (2%), family members of administrative staff (4.8%), settlers (3%), informers and agents (3.2%), Soviet activists (2.8%), family members of activists (0.2%), members of Komsomol (0.8%), students (0.2%), and former partisans and people who were close to them (1.8%). Eighty convictions by partisan courts-martial were identified, and 23 other partisan documents (warnings, proclamations) were left at the places of execution. This accounts for 14.9% of all executions. Most soldiers, employees and officers of military and security forces perished or were executed in an ambush. The justification for killing Soviet administrative officials, employees, and other staff members was usually that those people were carrying out Soviet orders. Usually executions were carried out at people’s homes or outside homes and by giving a warning and providing a charge. Death penalties and executions of farmers and workers pose the most questions. Most are executions for collaboration with the Soviets and the sabotage of the partisan movement. Based on the information collected, it is however usually difficult to fully assess the legitimacy of such killings.

Between innovative ambitions and erratic everyday practices: urban planners’ ambivalences towards digital transformation

Great expectations are being projected onto digital transformation as a solution to planning under uncertainty and complexity, while demanding new skills from and posing challenges to professionals. We address the ambivalent inclusion of information and communication technologies (ICTs) in everyday planning practices. How do ambivalences towards digitalisation as either a transformative process or as an intrusion upon everyday routines play out in urban planning as a situated knowledge practice? We focus on the erratic embedding of digital technologies and data into planning practices. We gather insights from interviews with planners in small and medium-sized cities in Germany, Austria and Switzerland. The analytical focus on knowing in practice and situated knowledge allows for insights on how digital transformations shape planning from professionals’ perspectives. Our research shows that digital transformation requires infrastructure and routines to bring forward innovative ambitions, which in many contexts are disrupted by limited resources and hierarchical decision-making procedures.

Orbit-finite linear programming

An infinite set is orbit-finite if, up to permutations of atoms, it has only finitely many elements. We study a generalisation of linear programming where constraints are expressed by an orbit-finite system of linear inequalities. As our principal contribution we provide a decision procedure for checking if such a system has a real solution, and for computing the minimal/maximal value of a linear objective function over the solution set. We also show undecidability of these problems in case when only integer solutions are considered. Therefore orbit-finite linear programming is decidable, while orbit-finite integer linear programming is not.

The Brazilian State Water Resources Councils: diagnosis of civil society participation through criteria of access to information, parity, and decision-making procedures

The aim of the article was to investigate whether the Brazilian State Water Resources Councils, including the Federal District, ensure civil society participation through access to information, parity, and decision-making procedures. In this context, verification criteria were selected, with maximum score of 1 point assigned based on their suitability for the Councils, which were classified in terms of participation adequacy. The states that were deemed suitable, in descending order, were: Paraíba (1st position), Mato Grosso do Sul, Minas Gerais, and São Paulo (2nd position), Amazonas, Pará, Paraná, Rio de Janeiro, Rio Grande do Sul, Rondônia, and Santa Catarina (3rd position), Bahia, Ceará, Federal District, Espírito Santo, and Mato Grosso (4th position), Rio Grande do Norte and Tocantins (5th position), and Alagoas (6th position). The states deemed unsuitable were: Acre and Pernambuco (7th position), Piauí and Roraima (8th position), Goiás and Sergipe (9th position), and Amapá and Maranhão (10th position). As for the criteria, the ones that scored the highest were: the presence of the website and Internal Regulations of the Councils, decision-making by the Council in plenary sessions, the presence of Meeting Minutes on the website, identification of the Technical Chambers of the Councils on these channels, adherence to the regular meeting schedule, identification of the members who make up the Councils, and parity among the three sectors that constitute them. It was concluded that the State Water Resources Councils need to ensure equal participation for civil society members in their discussions and deliberations as well as provide public access to the information generated.

INTELLECTUAL SUPPORT OF THE PROCESSES OF SEARCHING AND EXTRACTION OF PRECEDENTS IN CASE-BASED REASONING APPROACH

Context. The situational approach is based on the real-time decision-making methods for solving current problem situation. An effective tool for implementing the concept of a situational approach is an experience-based technique that widely known as сasebased reasoning approach. Reasoning by precedents allows solving new (latest) problems using knowledge and accumulated experience of previously solved problems. Since cases (precedents) describing a scenario for solving a certain problem situation are stored in the case library, their search and retrieval directly determine the system response time. In these conditions, there is a need to find ways of solving an actual scientific and practical problem aimed at optimizing case searching and extracting processes. The object of the paper is the processes of searching and extracting of cases from the case library. Objective. The purpose of the article is to improve the process of cases searching in CBR approach by narrowing down the set of cases permissible for solving the current target situation, and excluding from further analysis such cases that do not correspond to the given set of parameters of the target situation. Method. The research methodology is based on the application of rough set theory methods to improve the decision-making procedure based on reasoning by precedents. The proposed two-stage procedure for narrowing the initial set of cases involves preliminary filtering of precedents whose parameter values belong to the given neighborhoods of the corresponding parameters of the target situation at the first stage, and additional narrowing of the obtained subset of cases by the methods of rough set theory at the second stage. The determination of the R-lower and R-upper approximations of a given target set of cases within the notation of rough set theory allows dividing (segmenting) the original set of cases available for solving the current problem stored in case library into three subgroups (segments). The search for prototype solutions can be performed among a selected subset of cases that can be accurately classified as belonging to a given target set; which with some degree of probability can be attributed to the given target set, or within the framework of the union of these two subsets. The third subset contains cases that definitely do not belong to the given target set and can be excluded from further consideration. Results. The problem of presentation and derivation of knowledge based on precedents has been considered. The procedure for searching for precedents in case library has been improved in order to reduce the system response time required to find the solution closest to the current problem situation by narrowing the initial set of cases. Conclusions. The case-based reasoning approach is received the further development by segmenting cases in terms of their belonging to a given target set of precedents uses methods of the rough set theory, then the search for cases is carried out within a given segment. The proposed approach, in contrast to the classic CBR framework, uses additional knowledge derived from obtained case segment; allows modeling the uncertainty regarding the belonging / non-belonging of a case to a given target set; removing from further consideration cases that do not correspond to a given target set.

Ethical Issues Faced by Data Monitoring Committees: Results from an Exploratory Qualitative Study.

To protect research participants and ensure scientific integrity in clinical trials, independent data monitoring committees (DMCs, also known as data and safety monitoring boards) increasingly oversee randomized clinical trials and recommend modifying or stopping research. Little is known about the ethical issues DMCs face. We conducted semistructured interviews of DMC members using a qualitative description approach with low-inference interpretation. We recruited respondents through consultation with experts, an online registry of DMC members, and snowball sampling. We interviewed 22 DMC members who were statisticians, clinicians, and/or ethicists that had overseen a wide variety of trials globally. We identified three themes: finding common ground on responsibilities with variation; the need for judgment but not necessarily ethics expertise; and the resulting emotional distress from navigating ethical challenges. In the first case, DMC members identified 19 distinct duties, with some ethical responsibilities rarely mentioned. In the second case, not all DMC members saw the need for ethicists on DMCs or ethics training. In the third case, ethical challenges sometimes led to strong negative emotions. Developing tailored ethics training and decision-making procedures may help DMCs respond more effectively to ethical challenges.

Legal Certainty in the Division of Joint Property after Divorce

This study aims to analyze the legal certainty in the distribution of joint property after divorce, with an emphasis on the challenges faced in the implementation of the law in Indonesia. The division of joint property is a crucial issue in the context of divorce which often causes disputes between former spouses, where the principles of justice and equality should take precedence. In this study, a normative juridical approach is used to examine laws and regulations, legal doctrines, and court decisions related to the division of common property, with a focus on Law Number 1 of 1974 concerning Marriage and the Civil Code. The results show that despite the legal provisions governing the division of common property, its implementation is often hampered by various factors, including differences in interpretation among judges, the existence of cultural values that influence decisions, and technical obstacles in asset valuation. Variations in court decisions create legal uncertainty that not only harms one party, but also impacts the welfare of children involved in divorce. Uncertainty about the rights and obligations of each party has the potential to cause prolonged conflicts and harm all parties. As part of the analysis, the study also highlights the social and economic impact of legal uncertainty in the distribution of assets, especially for the financially weaker parties. To improve fairness and certainty in the division of common property, this study recommends the need for more detailed and uniform guidelines in court decision-making procedures, as well as harmonization between national and local regulations. Thus, it is hoped that the process of distributing joint property after divorce can be carried out in a fairer, more efficient, and transparent manner, so that the interests of all parties, especially children, can be well protected.

Nurses' perception of threats to human dignity in caring for patients with COVID-19: A qualitative study

PurposeIdentifying threats to patients' dignity is crucial for maintaining and promoting their dignity. Preserving patient dignity should be regarded as both a patient’s right and a moral obligation. This study was conducted to evaluate nurses' understanding of threats to human dignity in the care of patients with COVID-19. MethodsThis qualitative study was conducted using conventional content analysis in various clinical departments in Iran. Clinical nurses from different departments were selected through purposeful sampling. Data were collected via in-depth semi-structured interviews with 15 clinical nurses over two months in 2021 and analyzed using qualitative content analysis. ResultsDuring data analysis, two main categories and ten subcategories were identified: 1) Unethical behaviors (lack of respect for patient privacy, lack of patient involvement in decision-making procedures, ignoring the patient as an individual, aggressive behaviors, stigmatization, and failure to provide palliative and end-of-life care to patients and their families); 2) Organizational factors (inadequate financial support, lack of patient-care facilities, strict restrictions, and employing less experienced nurses in COVID wards). ConclusionThe present study showed that most participants expressed concerns about violations of patients' dignity and identified many threats to it. Based on the findings, it is suggested that other factors threatening patients' dignity be identified, the threats eliminated, and healthy treatment environments created to promote patients' dignity.

Dynamic output feedback model predictive control for polytopic uncertain systems under decode and forward cooperative relay protocol

This paper addresses the robust model predictive control (RMPC) problem for a class of polytopic uncertain systems under the decode and forward cooperative relay protocol (DFCP). In order to combat signal fading from sensors to controllers and improve communication reliability, spatial diversity is achieved through cooperative terminal relay signals. At each transmission instant, the terminal only selects a better signal for transmission and a switched system is constructed. The aim of this paper is to design a set of desired dynamic output feedback controllers in the framework of RMPC such that the switched system with the underlying DFCP is exponentially stable. By taking the influence of the randomness of DFCP derived from a three nodes model composed of DF relay, a new objective function based on the mathematical expectation of the traditional quadratic function of MPC is established. Then, the orthogonal complement technique is applied to handle the inherent couplings of variables to formulate a solvable optimisation problem. Moreover, the sufficient conditions are provided to guarantee the recursive feasibility of the MPC strategy and the stability of the established closed-loop system in terms of the average dwell time (ADT) method. Finally, three experiments are given to illustrate the effectiveness of the proposed method.

Devising a project risk management method under scrum conditions based on cognitive approach

Any project implemented using Scrum is characterized by the impact of risks, including negative changes in the environment and crisis circumstances. Therefore, the processes related to risk management, which is the object of this paper, become important. The problem solved in this study is to improve the efficiency of projects through the construction of a long-term strategy for reducing the level of risk and avoiding negative consequences for projects in the context of Scrum. The proposed method of risk management has been developed on the basis of the application of the synthesis of management of intelligent decision-making technologies and formalized methods. Difficult external circumstances are characterized by a high degree of uncertainty and do not always contribute to the successful implementation of the project. Therefore, this method of project risk management under Scrum conditions based on a cognitive approach is characterized by a combined combination of cognitive analysis, mathematical modeling, and expert methods. As part of the method, a model of project risk management under Scrum conditions has been built in the form of a fuzzy cognitive map, which could ensure determining the optimal strategic decision in dynamics, taking into account the effects of various factors. The result of applying this method is compliance with time limits, reduction of overspending of resources and losses in the project, as well as adaptation to rapidly changing circumstances and adequate response. The method of project risk management is characterized by solving the problem of formalizing management decision-making procedures and their information support, taking into account the availability of both quantitative and qualitative data. Within the framework of this method, a project risk management procedure under Scrum conditions has been proposed, which contributes to the systematization, monitoring, and control of risks under the conditions of complex, rapidly changing crisis circumstances

Development and implementation of a guideline-based decision support system for etiological diagnosis of Sustained Monomorphic Ventricular Tachycardia (SMVT)

Abstract Background Guideline (GL)-based decision support systems (DSSs) play a significant role in supporting physicians in their decision-making processes by providing structured clinical guidance. While these systems have shown significant success in enhancing practitioner performance and patient outcomes in general practice, their application in the context of ventricular arrhythmias remains limited. Moreover, the clinical etiological diagnosis of ventricular arrhythmias presents various challenges for healthcare professionals, such as adherence to updated diagnostic criteria and understanding of complex arrhythmia mechanisms. Purpose In this study, we aim to design, implement, and evaluate a guideline-based decision support systems for etiological diagnosis of sustained monomorphic ventricular tachycardia (SMVT), which could potentially address critical challenges associated with the disease diagnosis and management. Methods To comprehensively capture the semantics embedded in clinical guidelines, we first developed a dedicated knowledge graph tailored to the clinical decision-making. This involved extracting entities and relationships pertinent to key decision procedures from ESC guidelines for ventricular arrhythmias, clinical textbooks or literatures. Subsequently, we translated instances within the knowledge graph into archetypes within openEHR, amplifying the interoperability of clinical information. To enhance the interpretability of the DSS, we established executable diagnostic and treatment processes to offer visual representation of clinical steps in diagnosis and treatment. Ultimately, we constructed a decision support engine to implement the GL-DSS, and its effectiveness was evaluated with anonymous real-world data. Results The proposed GL-DSS was found to be quite feasible and could provide etiological diagnosis for SMVT. The knowledge base for the constructed GL-DDS included more than 2000 entities and relations, which played a vital role in representing disease pathogenesis. The proposed system can map the clinical entities to a set of openEHR archetypes, thus mitigate the interoperability issues of the hospital information systems and CDSS data integration. Also, this module improved system usability and ensured that guidelines could be easily translated and updated into decision support tools. Real-word medical records from 20 patient were collected for model evaluation, the results showed that the GL-DSS covered most of the entities and relations between diseases and diagnostic evidence recorded in clinical texts and achieved a diagnosis accuracy of 80%. Conclusions The results demonstrated that our proposed GL-DSS could completely and accurately capture the diagnostic information under the concrete EHR data. Thus, the implement decision support system could have the potential to improve clinical decision-making, patient care, and outcomes in this specialized medical domain.

Unveiling the Ethical Dilemmas of Digital Piracy: A Comprehensive Exploration of Motivations, Attitudes, and Behaviors

Driven by several elements, including the unwillingness to pay for material, the spread of subscription services, and the profitability of illegal activity, digital piracy has grown to be a common problem in the contemporary world. Along with financial damages for businesses and content creators, this phenomenon has legal repercussions for individuals involved in piracy and cybersecurity issues. The effective fight against digital piracy depends on an awareness of the drivers and hazards connected with this illegal activity. With an eye towards a thorough knowledge of this intricate problem, in this study, the focus centers on the reasons, attitudes, and actions behind digital piracy. Through examining how people defend their behavior in particular situations, in this study, the aim is to clarify the ethical issues and decision-making procedures related to piracy—even among otherwise law-abiding people. Combining a variety of the relevant literature and ideas, including situation ethics theory, in this study, we seek to provide insights for legislators, business players, and academics eager to meet the difficulties presented by digital piracy. This study adds to the continuous discussion on lessening the detrimental effects of digital piracy on content creators, businesses, and cybersecurity by looking at the underlying reasons for piracy and supporting legal access to material. Along with a dearth of research on the origins and moral questions of digital piracy, there is a lot of contradictory material. By examining the factors behind this unlawful activity, clarifying the complex dynamics involved, and offering understanding of the causes of digital piracy, this study seeks to close a significant void in the knowledge. The findings of this study will enable individuals to develop strategies for handling this prevalent issue in the digital era. Developing successful interventions that can reduce this illegal conduct and safeguard the interests of content producers, businesses, and cybersecurity overall depends on an awareness of the reasons behind digital piracy. This study advances the knowledge of the difficulties presented by this global phenomenon by investigating the ethical issues and decision-making procedures related to digital piracy.

Better Hardness Results for the Minimum Spanning Tree Congestion Problem

AbstractIn the spanning tree congestion problem, given a connected graph G, the objective is to compute a spanning tree T in G that minimizes its maximum edge congestion, where the congestion of an edge e of T is the number of edges in G for which the unique path in T between their endpoints traverses e. The problem is known to be $$\mathbb{N}\mathbb{P}$$ N P -hard, but its approximability is still poorly understood, and it is not even known whether the optimum solution can be efficiently approximated with ratio o(n). In the decision version of this problem, denoted $${\varvec{K}-\textsf {STC}}$$ K - STC , we need to determine if G has a spanning tree with congestion at most K. It is known that $${\varvec{K}-\textsf {STC}}$$ K - STC is $$\mathbb{N}\mathbb{P}$$ N P -complete for $$K\ge 8$$ K ≥ 8 , and this implies a lower bound of 1.125 on the approximation ratio of minimizing congestion. On the other hand, $${\varvec{3}-\textsf {STC}}$$ 3 - STC can be solved in polynomial time, with the complexity status of this problem for $$K\in { \left\{ 4,5,6,7 \right\} }$$ K ∈ 4 , 5 , 6 , 7 remaining an open problem. We substantially improve the earlier hardness results by proving that $${\varvec{K}-\textsf {STC}}$$ K - STC is $$\mathbb{N}\mathbb{P}$$ N P -complete for $$K\ge 5$$ K ≥ 5 . This leaves only the case $$K=4$$ K = 4 open, and improves the lower bound on the approximation ratio to 1.2. Motivated by evidence that minimizing congestion is hard even for graphs of small constant radius, we also consider $${\varvec{K}-\textsf {STC}}$$ K - STC restricted to graphs of radius 2, and we prove that this variant is $$\mathbb{N}\mathbb{P}$$ N P -complete for all $$K\ge 6$$ K ≥ 6 .

Enhancing Robo-Advisors: A Study of Personalized Financial Planning Through AI-Driven Insights

The emergence of robo-advisors has revolutionized the financial advisory field, presenting automated investment suggestions tailored to individual investors' distinct goals and risk appetites. This research paper aims to explore the dynamic evolution of robo-advisory services, delving into the ways artificial intelligence (AI) and data-derived insights can be harnessed to provide an even more personalized and efficient financial planning encounter. Through an exploration of advanced algorithms, machine learning methodologies, and user-centered design concepts, this investigation strives to uncover the techniques robo-advisors use to refine their decision-making procedures, accommodating the distinct financial ambitions of each investor. By means of practical analyses, illustrative case studies, and a discerning assessment of industry tendencies, this research illuminates the obstacles and prospects inherent in attaining genuine personalization within the domain of automated financial guidance.

What’s Impossible about Algorithmic Fairness?

The now well-known impossibility results of algorithmic fairness demonstrate that an error-prone predictive model cannot simultaneously satisfy two plausible conditions for group fairness apart from exceptional circumstances where groups exhibit equal base rates. The results sparked, and continue to shape, lively debates surrounding algorithmic fairness conditions and the very possibility of building fair predictive models. This article, first, highlights three underlying points of disagreement in these debates, which have led to diverging assessments of the feasibility of fairness in prediction-based decision-making. Second, the article explores whether and in what sense fairness as defined by the conjunction of the implicated fairness conditions is (un)attainable. Drawing on philosophical literature on the concept of feasibility and the role of feasibility in normative theory, I outline a cautiously optimistic argument for the diachronic feasibility of fairness. In line with recent works on the topic, I argue that fairness can be made possible through collective efforts to eliminate inequalities that feed into local decision-making procedures.

A Practical Decision Procedure for Quantifier-Free, Decidable Languages Extended with Restricted Quantifiers

A Practical Decision Procedure for Quantifier-Free, Decidable Languages Extended with Restricted Quantifiers