Fairness Considerations Research Articles

Searching for ‘Environmental Justice’ in EU Environmental Law

Environmental justice (‘EJ’) receives a lot of attention in the environmental social sciences and in U.S. law. But in Europe, it has so far been largely ignored in legal literature and policy debates, which seems difficult to reconcile with an anthropocentric understanding of current environmental law. This article focuses on distributive and procedural dimensions of EJ and on considerations of intragenerational fairness within the EU. General features of EU environmental law are examined in search of ‘hidden’ elements that might help or frustrate this goal. Themain finding is that other fields of law and policy are likely more significant enablers of EJ in Europe. To the extent that EU environmental law contributes, it seems largely an accidental result that is not guaranteed by its design. Substantive EU environmental law pursues a territorially uniform level of environmental protection and seems to have, with the possible exception of environmental impact assessments, no direct mechanisms to consider inequities between human populations. Examples are found of rules that even have clearly adverse consequences for underprivileged populations. The Aarhus Convention provides theoretical opportunities for procedural justice, but the current implementation in practice fails to achieve those and might even operate counterproductively as a mechanism that further benefits the already powerful. Primary EU environmental law largely mirrors these findings. Nevertheless, a correct interpretation of sustainable development in Article 11 of the Treaty on the Functioning of the European Union (TFEU) is identified as a potential key to better integrate EJ in EU policy. environmental justice, EU environmental law, anthropocentrism, distributive effects, offsets, procedural justice, Aarhus Convention, offsets, Article 191 TFEU, Article 11 TFEU

I am entitled to it! Social power and context modulate disadvantageous inequity aversion

Previous research consistently indicated that social power influences one's fairness consideration. However, it is unclear how social power and context jointly affect inequity aversion and whether these processes would be manifested in brain activities. In this study, participants were randomly assigned into either high or low power condition and then took part in a modified ultimatum game (UG) as responders in both gain and loss contexts, with their event-related potentials (ERPs) recorded. Behavioral results showed that powerful participants were more likely to reject unfair offers in both contexts compared with powerless ones. In addition, powerful participants showed a more negative feedback-related negativity (FRN) loss-win difference wave (d-FRN) upon presentation of proposed offers compared with powerless participants only in the gain context. Interestingly, in a later time window, differences of P300 responses to proposed offers were modulated by social power in both gain and loss contexts. These results suggested that powerful people were more sensitive to fairness levels and FRN may manifest fairness consideration in a gain context, but not in a loss context. Meanwhile, P300 is sensitive to fairness considerations in both gain and loss contexts.

Fairness-Aware Federated Learning With Unreliable Links in Resource-Constrained Internet of Things

In order to make full use of the network data and guarantee user privacy simultaneously, federated learning (FL) is proposed to enable distributed intelligence for local nodes without sharing data with each other. However, in practice, due to resource limitations, traditional FL suffers from node scheduling and parameter transmission failure, which not only affects the final performance but also further reduces the fairness of the participating nodes. This article addresses the challenge and proposes an FL method to enhance the performance of FL on the basis of guaranteeing the fairness of the local nodes in a resource-constrained Internet of Things (IoT) network. Specifically, an analytical model is first constructed to characterize the performance of FL with joint considerations of node fairness, unreliable parameter transmissions as well as resource limitations. Thereafter, a statistically reweighted aggregation (SRA) scheme is proposed for parameter aggregation and the corresponding model is proved to be unbiased to that based on ideal parameter transmissions. With the knowledge of time dependency of the global model, we further extend SRA and propose a reliable SRA (RSRA) scheme. Additionally, we prove RSRA is able to achieve higher stability performance than SRA in model training. Furthermore, the convergence bound of the proposed RSRA is derived analytically, based on which an adaptive local training scheme is proposed under a given resource budget. Finally, extensive experiments are carried out with a public data set to validate the effectiveness of the proposed scheme with comparisons of other baseline schemes.

Identification of influencing components on water scarcity management performance for sustainability in limited water resource area: a review

Water management by policy makers is based on multi-perspective information. In the case of water, scarcity causes public health, economic, and ecosystem problems because of the lack of safe water when the demand exceeds its availability. This study identified the influencing components of water scarcity management performance by systematic review methods based on two English full-text databases: Scopus and ScienceDirect from 2012 to 2022. A total of 22 studies were selected from 850 records by using the inclusion criteria and performance evaluation by the scoring rubric method. Moreover, the article quality was assessed using a critical appraisal tool by the Joanna Briggs Institute (JBI) critical appraisal checklist method. The result of this review revealed that the main influencing components of water scarcity management are related to the availability of water quantity and demand. Water availability is associated with the hydrological cycle which has uncertainty due to climate change. While the demand components depend on water use, population, industry and urbanization. Most of the studies in the literature review considered only water balance of water availability and demand. Such an approach is insufficient to achieve water security for sustainable development goals. Additional components including environmental components such as water quality degradation should be considered as these components can reduce the availability of freshwater resources. From an economic point of view, the benefit of water utilization should be prioritized in scarce water management in consideration of fairness in water rights. It is also essential to consider the contribution to socio-economic aspects from stakeholder meetings and participation.

User Grouping in Multiuser Satellite MIMO Downlink With Fairness Consideration

In this letter, a multi-user satellite MIMO downlink including a multi-beam GEO satellite and multiple user terminals (UTs) is considered. In order to make every UT get the service fairly, all UTs need to be divided into multiple groups so that UTs in the same group can be served simultaneously, and different groups can be served sequentially in different time slots. The user grouping problem is investigated in this letter with the objective of maximizing the average channel capacity per time slot, and a genetic based user grouping (GBUG) algorithm is proposed. Simulations show that the average channel capacity obtained by GBUG is larger than that of the existing algorithms in the ZF and MMSE precoding system.

Review on the sustainability of phase-change materials used in buildings

Phase-change materials have become a vital solution for saving energy and reducing greenhouse gas emissions from buildings. However, the production processes of phase-change materials affect their cost, impact societies, and may result in harmful emissions to the environment. In this study, we perform a review on the sustainability of phase-change materials considering performance, economic, environmental, and social aspects. While there is an extensive literature on the performance and efficiency of phase-change materials, there is limited consideration of social fairness and the environmental impact. So, we analyze the lifecycles of four different phase-change materials: a salt hydrate, a hydrocarbon, and two types of biobased materials. Our results show that hydrocarbon phase-change materials have the highest purchasing cost, the highest effect on the environment, and their production is associated with social risks related to safety and health. On the other hand, biobased (plant-based) materials are affordable, safe, provide new market opportunities for crops, and have minimal environmental harm if biofertilizers are used. The use of manurial fertilizers do not give biobased phase-change materials an advantage over other types. We also note that social fairness in production should be respected for sustainable phase-change materials solutions.

Fairness in Music Recommender Systems: A Stakeholder-Centered Mini Review.

The performance of recommender systems highly impacts both music streaming platform users and the artists providing music. As fairness is a fundamental value of human life, there is increasing pressure for these algorithmic decision-making processes to be fair as well. However, many factors make recommender systems prone to biases, resulting in unfair outcomes. Furthermore, several stakeholders are involved, who may all have distinct needs requiring different fairness considerations. While there is an increasing interest in research on recommender system fairness in general, the music domain has received relatively little attention. This mini review, therefore, outlines current literature on music recommender system fairness from the perspective of each relevant stakeholder and the stakeholders combined. For instance, various works address gender fairness: one line of research compares differences in recommendation quality across user gender groups, and another line focuses on the imbalanced representation of artist gender in the recommendations. In addition to gender, popularity bias is frequently addressed; yet, primarily from the user perspective and rarely addressing how it impacts the representation of artists. Overall, this narrative literature review shows that the large majority of works analyze the current situation of fairness in music recommender systems, whereas only a few works propose approaches to improve it. This is, thus, a promising direction for future research.

Social comparisons differentially affect fair and unfair processing in ultimatum bargaining

Several theoretical frameworks have attempted to illustrate the influence of social contexts on decision-making and well-being. Traditional economic models assume that absolute income is the crucial determinant of one's well-being, while the comparative models state that social comparisons influence and even determine well-being and decisions. Here we investigated the impact of social comparisons on decision-making using a modified three-player Ultimatum Game and ERP technique. We found two independent effects: First, social comparisons did not affect decision-making when a fair norm was enforced. Second, social comparisons affected fairness consideration for unfair offers only—responders were less likely to accept unfair offers in upward comparisons but more likely to accept unfair offers in downward comparisons. These results revealed that people were envy-free of fair offers while affected mainly by social comparisons when the equality norm was broken. Event-related brain potentials showed that in the early time window (260–320 ms), compared to fair offers, unfair offers elicited a larger negative-going medial frontal negativity (MFN) in upward than parallel and downward comparisons, and in the late stage (320–650 ms), compared to fair offers, unfair offers led to equally less positive-going P300 in upward and downward comparisons relative to parallel comparison. Although partly consistent with the relative standing assumption, both traditional economic models and comparative models require revision to account for the results.

Fairness and equity in resource allocation and decision-making

Fairness and equity considerations in the allocation of social goods and the development of algorithmic systems pose new challenges for decision-makers and interesting questions for the EC community. We overview a list of papers that point towards emerging directions in this research area.

Can China's carbon emissions trading scheme promote balanced green development? A consideration of efficiency and fairness

The carbon emission trading scheme (ETS) is an important market-based tool for achieving carbon neutrality. The existing research on the policy effect of ETS focuses on emission reduction effect and economic effect respectively. In view of this, based on the connotations of green development, we embed fairness toward the environment into the green development system to construct a balanced green development index to measure two dimensions, namely, efficiency and fairness. Theoretically understand the synergistic development effect of economic growth and ecological environment quality produced by the implementation of ETS, and analyze the impact of carbon market on balanced green development. A multiperiod difference-in-differences (DID) model explores the impact of China's carbon ETS on the green equilibrium level by using Chinese provincial panel data for the period 2008–2018. First, the results demonstrate that China's balanced green development level is weakly coordinated overall and there is a global spatial agglomeration effect. Second, the carbon ETS has significantly improved the level of balanced green development which promotes the degree of coordination between green economic growth and environmental fairness, offering an effective path that includes efficiency and fairness for green development. Third, there are regional differences in the impact of the carbon ETS on green equilibrium levels. The effect on the western region of China was significantly higher than that of the central and eastern regions of China. Compared with the existing research, the study breaks the single research perspective. From the perspective of efficiency and fairness, we propose improvements in the construction of a national unified carbon emissions trading market to strengthen the balanced green development. This paper provides a theoretical basis and policy reference for deepening China's green and high-quality development under the “carbon peaking and carbon neutrality” goal.

Satisfaction of outpatient oncologists with their work.

Job satisfaction is a fundamental ingredient in the life quality of a modern person; for a health care worker, it determines to a large extent the quality and accessibility of health care services they provide. Our aim is identification of key reasons for low job satisfaction among outpatient oncologists at cancer care centres (CCC) and identification of the best ways to address them. 110 oncologists working in outpatient CCC in Moscow, Moscow region and Ivanovo region participated in this research. Respondents’ job satisfaction was assessed using V.A. Rozanova’s Job Satisfaction Assessment Questionnaire. Virtually a quarter (23.6%) of oncologists were dissatisfied with their work; male respondents and surgical employees reported significantly higher levels of dissatisfaction. Wage levels and equity, working hours, teamwork and coordination in carrying out collective tasks and managerial style were the main areas of dissatisfaction. Measures to improve the work process included enhancing the resource outfit, fair consideration of each employee's achievements when distributing incentives, clear allocation of responsibility for collective project tasks, creating opportunities for paid part-time work and arranging regular meals at the expense of the health care organisation. Raising managers’ awareness of the results can contribute to improvements in oncologists’ performance, work process satisfaction, productivity and performance, quality of care and access to it, as well as public satisfaction and confidence in the health-care system as a whole.

Internet of Things applications placement to minimize latency in multi-tier fog computing framework

The application placement strategies in the hierarchical fog-cloud environment based on the directed acyclic graph (DAG) for rapid execution is an NP-hard optimization problem. Although heuristics have been proposed to generate sub-optimal solutions based on non-preemptive placement policy, merging multiple DAG-based applications into one application is simple but ineffective for minimizing the overall makespan due to the lack of consideration of fairness among multiple DAG-based applications. We design an application placement strategy based on dynamic scheduling that can effectively utilize the schedule gaps in the virtual machines of the different layers to minimize the makespan that meets the deadlines.

Fairness in International Taxation: The Ability-to-Pay Case for Taxing Worldwide Income

Copyright © 2001 by J. Clifton Fleming, Jr., Robert J. Peroni & Stephen E. Shay. All rights reserved.The ability-to-pay fairness concept is a key factor underlying the historic U.S. policy of relying principally on the income tax to finance federal government expenditures. Indeed a major justification for this reliance, as opposed to significant dependence on consumption levies, is that the income tax is a system for spreading the costs of government in a way that advances fairness by giving substantial deference to comparative ability-to-pay.Consequently, one would expect tax policy analysts to routinely examine the equity implications of international income tax rules by applying the fairness criterion with the same rigor as in the domestic context. But surprisingly, there has been relatively little discussion in the literature regarding the role of the ability-to-pay concept in analyzing international tax policy issues. This may be because the composition of international investment historically has been dominated by the direct foreign investments of multinational corporations, which pose perplexing issues in evaluating fairness concerns. Even if true, however, this is an inadequate reason to forego analysis of fairness considerations when scrutinizing the important international dimension of a modern income tax. In this article, we examine the role that fairness concerns, embedded in the abilityto-pay concept, play in justifying the U.S. policy of taxing U.S. residents on their worldwide incomes.

Investigating Gender Differences in Canadian Plastic Surgery Online Patient Education.

The public interest and demand for cosmetic surgery is growing in North America. As practices continue to advertise cosmetic procedures, male consumers must also be given fair consideration in a market targeted mostly towards women. This study investigated the advertising trends of plastic surgery clinics to assess for prevailing gender differences among online Canadian plastic surgery practice advertising. The 2021 College of Physicians and Surgeons directory for each province and territory was utilized to identify all practicing plastic surgeons. A systematic search with Google (Mountain View, CA) was conducted to analyze the websites of Canadian plastic surgery centers in the following manner: "[physician name] [province of practice]." A total of 209 websites and 13,838 images were identified and analyzed. Of these images, 12,386 (90%) were female and 1452 (10%) were male patients or models. Although only 20% had a male services page, 62% of all centers offered gynecomastia procedures. The most common procedures targeting men were blepharoplasty (95%), liposuction (93%), and abdominoplasty (93%). The Prairies region had significantly fewer websites with male-only pages compared with all other Canadian regions. Despite the increase in cosmetic surgery procedures for males, the market for cosmetic surgery procedures targeted towards males remains insignificant. An increase in the advertising of in-demand male cosmetic procedures can allow for a broader consumer market and a subsequent increase in benefits for plastic surgeons.

Punishment cost affects third-parties' behavioral and neural responses to unfairness

Third-party punishment plays a crucial role in fairness norm enforcement. The present study investigated how punishment cost would affect third-parties' behavioral and neural responses to unfairness using a modified Third-Party Dictator Game and functional magnetic resonance imaging (fMRI). Participants acted as third-parties and decided how many monetary units (MUs) to invest to punish norm violations in two punishment cost contexts. Participants' every MU investment reduced dictators' payoff by 6 MUs in the low punishment cost context and 3 MUs in the high one. Participants' invested MUs reflected the cost they would like to pay to punish dictators while dictators' reduced MUs represented the amount of punishment they received. Behavioral results showed participants' fairness ratings were not affected by punishment cost. However, punishment amount decreased in the high punishment cost context where participants invested more MUs and spent more time for decision-making. Neurally, left anterior insula (AI) and bilateral dorsolateral prefrontal cortex (dlPFC) showed stronger responses to unfair relative to fair allocations in both contexts. Moreover, dorsal anterior cingulate cortex (dACC) was more active during unfair allocations in the high punishment cost context than in the low one and the difference of dACC activity between these two conditions was positively correlated with the difference of reaction times. Overall, the present study demonstrated that punishment cost would not affect people's fairness perception but increase the conflicts between norm enforcement and self-interest. The decision for punishment was the outcome of integrating fairness and economic considerations.

Exploring racial and gender disparities in voice biometrics

Systemic inequity in biometrics systems based on racial and gender disparities has received a lot of attention recently. These disparities have been explored in existing biometrics systems such as facial biometrics (identifying individuals based on facial attributes). However, such ethical issues remain largely unexplored in voice biometric systems that are very popular and extensively used globally. Using a corpus of non-speech voice records featuring a diverse group of 300 speakers by race (75 each from White, Black, Asian, and Latinx subgroups) and gender (150 each from female and male subgroups), we explore and reveal that racial subgroup has a similar voice characteristic and gender subgroup has a significant different voice characteristic. Moreover, non-negligible racial and gender disparities exist in speaker identification accuracy by analyzing the performance of one commercial product and five research products. The average accuracy for Latinxs can be 12% lower than Whites (p < 0.05, 95% CI 1.58%, 14.15%) and can be significantly higher for female speakers than males (3.67% higher, p < 0.05, 95% CI 1.23%, 11.57%). We further discover that racial disparities primarily result from the neural network-based feature extraction within the voice biometric product and gender disparities primarily due to both voice inherent characteristic difference and neural network-based feature extraction. Finally, we point out strategies (e.g., feature extraction optimization) to incorporate fairness and inclusive consideration in biometrics technology.

FMEA-AI: AI fairness impact assessment using failure mode and effects analysis

Recently, there has been a growing demand to address failures in the fairness of artificial intelligence (AI) systems. Current techniques for improving fairness in AI systems are focused on broad changes to the norms, procedures and algorithms used by companies that implement those systems. However, some organizations may require detailed methods to identify which user groups are disproportionately impacted by failures in specific components of their systems. Failure mode and effects analysis (FMEA) is a popular safety engineering method and is proposed here as a vehicle to support the conducting of “AI fairness impact assessments” in organizations. An extension to FMEA called “FMEA-AI” is proposed as a modification to a familiar tool for engineers and manufacturers that can integrate moral sensitivity and ethical considerations into a company’s existing design process. Whereas current impact assessments focus on helping regulators identify an aggregate risk level for an entire AI system, FMEA-AI helps companies identify safety and fairness risk in multiple failure modes of an AI system. It also explicitly identifies user groups and considers an objective definition of fairness as proportional satisfaction of claims in calculating likelihood and severity of fairness-related failures. This proposed method can help industry analysts adapt a widely known safety engineering method to incorporate AI fairness considerations, promote moral sensitivity and overcome resistance to change.

The Effect of Task Difficulty and Self-Contribution on Fairness Consideration: An Event-Related Potential Study.

Self-contribution may be an influential factor in fairness consideration and consequent behavioral decisions. Few studies have investigated simultaneous effects of task difficulty and self-contribution on fairness consideration outcomes and associated neurophysiological responses. To elucidate modulation effects of task difficulty and self-contribution on fairness consideration, 30 recruited participants played a modified ultimatum game (UG) while undergoing event-related potential measurements. A 2 (task difficulty: hard vs. easy) × 3 (contribution: other-contribution vs. both-contribution vs. self-contribution) × 2 (fairness type: fair vs. unfair) within-subject design was adopted. A significant interaction between fairness type and contribution was observed in the behavioral data, with unfair offers being more acceptable in the other-contribution condition than in the self-contribution or both-contribution conditions. In the early processing time window, feedback-related negative magnitudes were greater in the hard condition than in the easy condition. P300 responses were more pronounced when participants contributed equally to the proposer than in the self- and other-contribution conditions. These results demonstrated that individuals’ decisions are influenced by their own effort contributions relative to those of others in cooperative contexts.

Fixed price equilibria on peer‐to‐peer platforms: Lessons from time‐based currencies

There are many online platforms for peer-to-peer exchange that introduce a platform-specific currency and fix prices to some extent. We model such platforms as pure exchange economies and characterize all fixed price equilibria. We demonstrate the inherent inefficiency following from the combination of fixed prices and voluntary trade and show that simple additional Pareto improving trades exist. While our theoretical analysis predicts that fixed prices lead to less trade than competitive prices, we also discuss some potential advantages of price restrictions, in particular, with respect to simplicity and fairness considerations. Strikingly, it is not those agents with the most attractive goods who have the highest willingness to participate in a fixed price platform. In an empirical illustration, we explore how these theoretical insights unfold in reality by describing patterns of several platforms covering around 100k transactions. This work is informative for the market design of peer-to-peer platforms and for markets with price restrictions more generally.

Group Membership Modulates Fairness Consideration Among Deaf College Students-An Event-Related Potential Study.

Group interaction is an essential way of social interaction and plays an important role in our social development. It has been found that when individuals participate in group interactions, the group identity of the interaction partner affects the mental processing and behavioral decision-making of subjects. However, little is known about how deaf college students, who are labeled distinctly different from normal hearing college students, will react when facing proposers from different groups in the ultimatum game (UG) and its time course. In this study, we recruited 29 deaf college students who played the UG in which they received extremely unfair, moderately unfair, or fair offers from either outgroup members (normal hearing college students) or ingroup members (deaf college students), while their brain potentials were recorded. The behavioral results showed that group membership did not impact the acceptance rate of deaf college students. But, event-related potential (ERP) analysis demonstrated an enhanced feedback-related negativity (FRN) elicited by ingroup members compared to outgroup members. Importantly, we found that under fairness conditions, deaf college students induced more positive P2 and P3 facing ingroup members compared to outgroup members. Our results demonstrated that group membership may modulate the performance of deaf college students in the UG and the existence of ingroup bias among deaf college students. This provides some evidence for the fairness characteristics of special populations, so that to improve the educational integration of colleges and universities.