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

Dysregulation of Kv3.4 channels in dorsal root ganglia following spinal cord injury.

Spinal cord injury (SCI) patients develop chronic pain involving poorly understood central and peripheral mechanisms. Because dysregulation of the voltage-gated Kv3.4 channel has been implicated in the hyperexcitable state of dorsal root ganglion (DRG) neurons following direct injury of sensory nerves, we asked whether such a dysregulation also plays a role in SCI. Kv3.4 channels are expressed in DRG neurons, where they help regulate action potential (AP) repolarization in a manner that depends on the modulation of inactivation by protein kinase C (PKC)-dependent phosphorylation of the channel\u27s inactivation domain. Here, we report that, 2 weeks after cervical hemicontusion SCI, injured rats exhibit contralateral hypersensitivity to stimuli accompanied by accentuated repetitive spiking in putative DRG nociceptors. Also in these neurons at 1 week after laminectomy and SCI, Kv3.4 channel inactivation is impaired compared with naive nonsurgical controls. At 2-6 weeks after laminectomy, however, Kv3.4 channel inactivation returns to naive levels. Conversely, Kv3.4 currents at 2-6 weeks post-SCI are downregulated and remain slow-inactivating. Immunohistochemistry indicated that downregulation mainly resulted from decreased surface expression of the Kv3.4 channel, as whole-DRG-protein and single-cell mRNA transcript levels did not change. Furthermore, consistent with Kv3.4 channel dysregulation, PKC activation failed to shorten the AP duration of small-diameter DRG neurons. Finally, re-expressing synthetic Kv3.4 currents under dynamic clamp conditions dampened repetitive spiking in the neurons from SCI rats. These results suggest a novel peripheral mechanism of post-SCI pain sensitization implicating Kv3.4 channel dysregulation and potential Kv3.4-based therapeutic interventions

Leukocytes Breach Endothelial Barriers by Insertion of Nuclear Lobes and Disassembly of Endothelial Actin Filaments

Israel Science Foundation (grant 87/12) Flight Attendant Medical Research Institute Foundation (FAMRI) (grant FAMRI032001_CoE), USA Minerva Foundation, Germany Wellcome Trust (grant 098291/Z/12/Z to S.N.

Infant BMI or Weight-for-Length and Obesity Risk in Early Childhood

Weight-for-length (WFL) is currently used to assess adiposity under 2 years. We assessed WFL- versus BMI-based estimates of adiposity in healthy infants in determining risk for early obesity