Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search

We present a framework for quantifying and mitigating algorithmic bias in mechanisms designed for ranking individuals, typically used as part of web-scale search and recommendation systems. We first propose complementary measures to quantify bias with respect to protected attributes such as gender and age. We then present algorithms for computing fairness-aware re-ranking of results. For a given search or recommendation task, our algorithms seek to achieve a desired distribution of top ranked results with respect to one or more protected attributes. We show that such a framework can be tailored to achieve fairness criteria such as equality of opportunity and demographic parity depending on the choice of the desired distribution. We evaluate the proposed algorithms via extensive simulations over different parameter choices, and study the effect of fairness-aware ranking on both bias and utility measures. We finally present the online A/B testing results from applying our framework towards representative ranking in LinkedIn Talent Search, and discuss the lessons learned in practice. Our approach resulted in tremendous improvement in the fairness metrics (nearly three fold increase in the number of search queries with representative results) without affecting the business metrics, which paved the way for deployment to 100% of LinkedIn Recruiter users worldwide. Ours is the first large-scale deployed framework for ensuring fairness in the hiring domain, with the potential positive impact for more than 630M LinkedIn members.Comment: This paper has been accepted for publication at ACM KDD 201

Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment

Automated data-driven decision making systems are increasingly being used to assist, or even replace humans in many settings. These systems function by learning from historical decisions, often taken by humans. In order to maximize the utility of these systems (or, classifiers), their training involves minimizing the errors (or, misclassifications) over the given historical data. However, it is quite possible that the optimally trained classifier makes decisions for people belonging to different social groups with different misclassification rates (e.g., misclassification rates for females are higher than for males), thereby placing these groups at an unfair disadvantage. To account for and avoid such unfairness, in this paper, we introduce a new notion of unfairness, disparate mistreatment, which is defined in terms of misclassification rates. We then propose intuitive measures of disparate mistreatment for decision boundary-based classifiers, which can be easily incorporated into their formulation as convex-concave constraints. Experiments on synthetic as well as real world datasets show that our methodology is effective at avoiding disparate mistreatment, often at a small cost in terms of accuracy.Comment: To appear in Proceedings of the 26th International World Wide Web Conference (WWW), 2017. Code available at: https://github.com/mbilalzafar/fair-classificatio

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

Effects of dairy consumption on SIRT1 and mitochondrial biogenesis in adipocytes and muscle cells

<p>Abstract</p> <p>Background</p> <p>Recent data from this laboratory suggest that components of dairy foods may serve as activators of SIRT1 (Silent Information Regulator Transcript 1), and thereby participate in regulation of glucose and lipid metabolism. In this study, an <it>ex-vivo/in-vitro </it>approach was used to examine the integrated effects of dairy diets on SIRT1 activation in two key target tissues (adipose and muscle tissue).</p> <p>Methods</p> <p>Serum from overweight and obese subjects fed low or high dairy diets for 28 days was added to culture medium (similar to conditioned media) to treat cultured adipocytes and muscle cells for 48 hours.</p> <p>Results</p> <p>Treatment with high dairy group conditioned media resulted in 40% increased SIRT1 gene expression in both tissues (p < 0.01) and 13% increased enzyme activity in adipose tissue compared to baseline. This was associated with increased gene expression of peroxisome proliferator-activated receptor-gamma coactivator 1 alpha (PGC-1α), nuclear respiratory factor 1 (NRF1), cytochrome oxidase c subunit 7 (Cox 7), NADH dehydrogenase and uncoupling protein 2 (UCP2) in adipocytes as well as uncoupling protein 3 (UCP3), NRF1 and Cox 7 in muscle cells (p < 0.05). Further, direct incubation of physiological concentrations of leucine and its metabolites α-Ketoisocaproic acid (KIC) and β-hydroxy-methylbuteric acid (HMB) with recombinant human SIRT1 enzyme resulted in 30 to 50% increase of SIRT1 activity (p < 0.05).</p> <p>Conclusions</p> <p>These data indicate that dairy consumption leads to systemic effects, which may promote mitochondrial biogenesis in key target tissues such as muscle and adipose tissue both by direct activation of SIRT1 as well as by SIRT1-independent pathways.</p

Leucine modulation of mitochondrial mass and oxygen consumption in skeletal muscle cells and adipocytes

<p>Abstract</p> <p>Background</p> <p>The effects of dairy on energy metabolism appear to be mediated, in part, by leucine and calcium which regulate both adipocyte and skeletal muscle energy metabolism. We recently demonstrated that leucine and calcitriol regulate fatty acid oxidation in skeletal muscle cells <it>in vitro</it>, with leucine promoting and calcitriol suppressing fatty acid oxidation. Moreover, leucine coordinately regulated adipocyte lipid metabolism to promote flux of lipid to skeletal muscle and regulate metabolic flexibility. We have now investigated the role of mitochondrial biogenesis in mediating these effects.</p> <p>Methods</p> <p>We tested the effect of leucine, calcitriol and calcium in regulation of mitochondrial mass using a fluorescence method and tested mitochondrial biogenesis regulatory genes as well mitochondrial component genes using real-time PCR. We also evaluated the effect of leucine on oxygen consumption with a modified perfusion system.</p> <p>Results</p> <p>Leucine (0.5 mM) increased mitochondrial mass by 30% and 53% in C2C12 myocytes and 3T3-L1 adipocytes, respectively, while calcitriol (10 nM) decreased mitochondrial abundance by 37% and 27% (p < 0.02). Leucine also stimulated mitochondrial biogenesis genes SIRT-1, PGC-1α and NRF-1 as well as mitochondrial component genes UCP3, COX, and NADH expression by 3–5 fold in C2C12 cells (p < 0.003). Adipocyte-conditioned medium reduced mitochondrial abundance (p < 0.001) and decreased UCP3 but increased PGC-1α expression in myocytes, suggesting a feedback stimulation of mitochondrial biogenesis. Similar data were observed in C2C12 myocytes co-cultured with adipocytes, with co-culture markedly suppressing mitochondrial abundance (p < 0.02). Leucine stimulated oxygen consumption in both C2C12 cells and adipocytes compared with either control or valine-treated cells. Transfection of C2C12 myocytes with SIRT-1 siRNA resulted in parallel suppression of SIRT-1 expression and leucine-induced stimulation of PGC-1α and NRF-1, indicating that SIRT-1 mediates leucine induced mitochondrial biogenesis in muscle cells.</p> <p>Conclusion</p> <p>These data suggest that leucine and calcitriol modulation of muscle and adipocyte energy metabolism is mediated, in part, by mitochondrial biogenesis.</p

Dynamic Mechanisms of Cell Rigidity Sensing: Insights from a Computational Model of Actomyosin Networks

Cells modulate themselves in response to the surrounding environment like substrate elasticity, exhibiting structural reorganization driven by the contractility of cytoskeleton. The cytoskeleton is the scaffolding structure of eukaryotic cells, playing a central role in many mechanical and biological functions. It is composed of a network of actins, actin cross-linking proteins (ACPs), and molecular motors. The motors generate contractile forces by sliding couples of actin filaments in a polar fashion, and the contractile response of the cytoskeleton network is known to be modulated also by external stimuli, such as substrate stiffness. This implies an important role of actomyosin contractility in the cell mechano-sensing. However, how cells sense matrix stiffness via the contractility remains an open question. Here, we present a 3-D Brownian dynamics computational model of a cross-linked actin network including the dynamics of molecular motors and ACPs. The mechano-sensing properties of this active network are investigated by evaluating contraction and stress in response to different substrate stiffness. Results demonstrate two mechanisms that act to limit internal stress: (i) In stiff substrates, motors walk until they exert their maximum force, leading to a plateau stress that is independent of substrate stiffness, whereas (ii) in soft substrates, motors walk until they become blocked by other motors or ACPs, leading to submaximal stress levels. Therefore, this study provides new insights into the role of molecular motors in the contraction and rigidity sensing of cells

Evo-devo of human adolescence: beyond disease models of early puberty

Despite substantial heritability in pubertal development, much variation remains to be explained, leaving room for the influence of environmental factors to adjust its phenotypic trajectory in the service of fitness goals. Utilizing evolutionary development biology (evo-devo), we examine adolescence as an evolutionary life-history stage in its developmental context. We show that the transition from the preceding stage of juvenility entails adaptive plasticity in response to energy resources, other environmental cues, social needs of adolescence and maturation toward youth and adulthood. Using the evolutionary theory of socialization, we show that familial psychosocial stress fosters a fast life history and reproductive strategy rather than early maturation being just a risk factor for aggression and delinquency. Here we explore implications of an evolutionary-developmental-endocrinological-anthropological framework for theory building, while illuminating new directions for research

Anti-diabetic effect of a preparation of vitamins, minerals and trace elements in diabetic rats: a gender difference

BACKGROUND: Although multivitamin products are widely used as dietary supplements to maintain health or as special medical food in certain diseases, the effects of these products were not investigated in diabetes mellitus, a major cardiovascular risk factor. Therefore, here we investigated if a preparation of different minerals, vitamins, and trace elements (MVT) for human use affects the severity of experimental diabetes. METHODS: Two days old neonatal Wistar rats from both genders were injected with 100 mg/kg of streptozotocin or its vehicle to induce diabetes. At week 4, rats were fed with an MVT preparation or vehicle for 8 weeks. Well established diagnostic parameters of diabetes, i.e. fasting blood glucose and oral glucose tolerance test were performed at week 4, 8 and 12. Moreover, serum insulin and blood HbA1c were measured at week 12. RESULTS: An impaired glucose tolerance has been found in streptozotocin-treated rats in both genders at week 4. In males, fasting blood glucose and HbA1c were significantly increased and glucose tolerance and serum insulin was decreased at week 12 in the vehicle-treated diabetic group as compared to the vehicle-treated non-diabetic group. All of the diagnostic parameters of diabetes were significantly improved by MVT treatment in male rats. In females, streptozotocin treatment resulted in a less severe prediabetic-like phenotype as only glucose tolerance and HbA1c were altered by the end of the study in the vehicle-treated diabetic group as compared to the vehicle-treated non-diabetic group. MVT treatment failed to improve the diagnostic parameters of diabetes in female streptozotocin-treated rats. CONCLUSION: This is the first demonstration that MVT significantly attenuates the progression of diabetes in male rats with chronic experimental diabetes. Moreover, we have confirmed that females are less sensitive to STZ-induced diabetes and MVT preparation did not show protection against prediabetic state. This may suggest a gender difference in the pathogenesis of diabetes

Dairy attentuates oxidative and inflammatory stress in metabolic syndrome123

Background: Oxidative and inflammatory stress are elevated in obesity and are further augmented in metabolic syndrome. We showed previously that dairy components suppress the adipocyte- and macrophage-mediated generation of reactive oxygen species and inflammatory cytokines and systemic oxidative and inflammatory biomarkers in obesity