Fairness in Water Quality: A Descriptive Approach

Muscle strength is important for firefighters work capacity. Laboratory tests used for measurements of muscle strength, however, are complicated, expensive and time consuming. The aims of the present study were to investigate correlations between physical capacity within commonly occurring and physically demanding firefighting work tasks and both laboratory and field tests in full time (N = 8) and part-time (N = 10) male firefighters and civilian men (N = 8) and women (N = 12), and also to give recommendations as to which field tests might be useful for evaluating firefighters' physical work capacity. Laboratory tests of isokinetic maximal (IM) and endurance (IE) muscle power and dynamic balance, field tests including maximal and endurance muscle performance, and simulated firefighting work tasks were performed. Correlations with work capacity were analyzed with Spearman's rank correlation coefficient (rs). The highest significant (p<0.01) correlations with laboratory and field tests were for Cutting: IE trunk extension (rs = 0.72) and maximal hand grip strength (rs = 0.67), for Stairs: IE shoulder flexion (rs = −0.81) and barbell shoulder press (rs = −0.77), for Pulling: IE shoulder extension (rs= −0.82) and bench press (rs = −0.85), for Demolition: IE knee extension (rs = 0.75) and bench press (rs = 0.83), for Rescue: IE shoulder flexion (rs = −0.83) and bench press (rs = −0.82), and for the Terrain work task: IE trunk flexion (rs = −0.58) and upright barbell row (rs = −0.70). In conclusion, field tests may be used instead of laboratory tests. Maximal hand grip strength, bench press, chin ups, dips, upright barbell row, standing broad jump, and barbell shoulder press were strongly correlated (rs≥0.7) with work capacity and are therefore recommended for evaluating firefighters work capacity

Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality

As virtually all aspects of our lives are increasingly impacted by algorithmic decision making systems, it is incumbent upon us as a society to ensure such systems do not become instruments of unfair discrimination on the basis of gender, race, ethnicity, religion, etc. We consider the problem of determining whether the decisions made by such systems are discriminatory, through the lens of causal models. We introduce two definitions of group fairness grounded in causality: fair on average causal effect (FACE), and fair on average causal effect on the treated (FACT). We use the Rubin-Neyman potential outcomes framework for the analysis of cause-effect relationships to robustly estimate FACE and FACT. We demonstrate the effectiveness of our proposed approach on synthetic data. Our analyses of two real-world data sets, the Adult income data set from the UCI repository (with gender as the protected attribute), and the NYC Stop and Frisk data set (with race as the protected attribute), show that the evidence of discrimination obtained by FACE and FACT, or lack thereof, is often in agreement with the findings from other studies. We further show that FACT, being somewhat more nuanced compared to FACE, can yield findings of discrimination that differ from those obtained using FACE.Comment: 7 pages, 2 figures, 2 tables.To appear in Proceedings of the International Conference on World Wide Web (WWW), 201

Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk

Guidelines for the management of atherosclerotic cardiovascular disease (ASCVD) recommend the use of risk stratification models to identify patients most likely to benefit from cholesterol-lowering and other therapies. These models have differential performance across race and gender groups with inconsistent behavior across studies, potentially resulting in an inequitable distribution of beneficial therapy. In this work, we leverage adversarial learning and a large observational cohort extracted from electronic health records (EHRs) to develop a "fair" ASCVD risk prediction model with reduced variability in error rates across groups. We empirically demonstrate that our approach is capable of aligning the distribution of risk predictions conditioned on the outcome across several groups simultaneously for models built from high-dimensional EHR data. We also discuss the relevance of these results in the context of the empirical trade-off between fairness and model performance

Theories of Distributive Justice and Limitations on Taxation: What Rawls Demands from Tax Systems Symposium - Rawls and the Law: Panel VI: Property, Taxation, and Distributive Justice

This Essay attempts to map out how such an inquiry would be conducted in light of Rawls. Rather than searching in theories of justice for required precepts of taxation, we might more fruitfully ask what constraints, if any, a particular theory of justice imposes on the tax system. Application of such an approach to Rawls\u27s theory of justice may explain his apparent preference for a flat consumptionbased tax. This preference is otherwise quite puzzling in light of much of what Rawls wrote about economic justice, and might lead us to expect him to endorse a progressive income tax. If Rawls\u27s discussion of economic justice is treated as offering limitations rather than mandates for taxation, then a variety of tax systems may be part of a just Rawlsian society, including a flat consumption-based tax. Extension of this approach to other political theories might produce a shorter list of acceptable taxes, depending on the extent to which the chosen theory is likely to constrain government action

Fairness of Exposure in Rankings

Rankings are ubiquitous in the online world today. As we have transitioned from finding books in libraries to ranking products, jobs, job applicants, opinions and potential romantic partners, there is a substantial precedent that ranking systems have a responsibility not only to their users but also to the items being ranked. To address these often conflicting responsibilities, we propose a conceptual and computational framework that allows the formulation of fairness constraints on rankings in terms of exposure allocation. As part of this framework, we develop efficient algorithms for finding rankings that maximize the utility for the user while provably satisfying a specifiable notion of fairness. Since fairness goals can be application specific, we show how a broad range of fairness constraints can be implemented using our framework, including forms of demographic parity, disparate treatment, and disparate impact constraints. We illustrate the effect of these constraints by providing empirical results on two ranking problems.Comment: In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, London, UK, 201

A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity

We map the recently proposed notions of algorithmic fairness to economic models of Equality of opportunity (EOP)---an extensively studied ideal of fairness in political philosophy. We formally show that through our conceptual mapping, many existing definition of algorithmic fairness, such as predictive value parity and equality of odds, can be interpreted as special cases of EOP. In this respect, our work serves as a unifying moral framework for understanding existing notions of algorithmic fairness. Most importantly, this framework allows us to explicitly spell out the moral assumptions underlying each notion of fairness, and interpret recent fairness impossibility results in a new light. Last but not least and inspired by luck egalitarian models of EOP, we propose a new family of measures for algorithmic fairness. We illustrate our proposal empirically and show that employing a measure of algorithmic (un)fairness when its underlying moral assumptions are not satisfied, can have devastating consequences for the disadvantaged group's welfare

Breaking the Constitutional Deadlock: Lessons from Deliberative Experiments in Constitutional Change

This work provides comparative insights into how deliberation on proposed constitutional amendments might be more effectively pursued. It reports on a new nationwide survey of public attitudes to constitutional reform, examining the potential in Australia of innovative Canadian models of reform led by Citizens' Assemblies. Assembly members are selected at random and are demographically representative of the wider public. They deliberate over reforms for several months while receiving instruction from experts in relevant fields. Members thus become 'public-experts': citizens who stand in for the wider public but are versed in constitutional fundamentals. The author finds striking empirical evidence that, if applied in the Australian context, public trust would be substantially greater for Citizens' Assemblies compared with traditional processes of change. The article sets these results in context, reading the Assemblies against theories of deliberative democracy and public trust. One reason for greater public trust in the Assemblies' may be an ability to accommodate key values that are otherwise in conflict: majoritarian democratic legitimacy, on the one hand, and fair and well-informed (or 'deliberatively rational') decision-making, on the other. Previously, almost no other poll had asked exactly how much Australians trust in constitutional change. However, by resolving trust into a set of discrete public values, the polling and analysis in this work provide evidence that constitutional reform might only succeed when it expresses, at once, the values of both majoritarian and deliberative democracy

Equality, Liberty, and a Fair Income Tax

This Article summarizes various formal theories of justice and of income taxation. It explores the nature of the American perception of justice. First, it provides an overview of the two political concepts that have shaped our country—liberty and equality. It then summarizes the American tradition, labeled moral economic individualism, that articulates the meanings of liberty and equality that resonate most strongly within the national psyche. It surveys empirical evidence of American beliefs about distributive justice and taxation. The Article concludes that American beliefs in liberty and equality support a mildly progressive hybrid income-consumption tax, rather than a pure income tax or a flat-rate consumption tax. Such a tax acknowledges the pluralistic meanings of liberty and equality under the unifying umbrella of a fluid and flexible conception of fair tax

Fairness and the sufficiency turn in urban transport

This commentary considers the research and policy implications of applying the sufficiency principle to urban transport. It explores “enoughness” against a backdrop of increasing carbon emissions in the transport sector, inevitable ceilings for resource intense movement, and the essential requirement of providing access to opportunities in cities. Given the relative lack of progress, increasingly polarizing political debate and urgent requirement for change, this commentary advocates for a more direct and open engagement with a sufficiency turn in urban transport. Most importantly, fundamental questions about a fair distribution of remaining emissions and finite street space within the transport sector must be considered. This engagement can build on the emerging field of transport equity while joining up social justice perspectives of the “here and now” with sustainability justice recognising global society, future generations, and nature. While acknowledging the political risks of embracing sufficiency in urban transport, this commentary builds on this rationale and directly engages with the idea of establishing budgets for transport-related carbon emissions and space consumption. It encourages further exploration and presents critical questions for future research and policy practice based on Martens et al.’s (Martens et al., 2019) three transport equity components of considering mobility benefits and burdens, the disaggregation of social groups, and determining the distribution principle