Interview on \u3cem\u3eThe Black Box Society\u3c/em\u3e

Hidden algorithms drive decisions at major Silicon Valley and Wall Street firms. Thanks to automation, those firms can approve credit, rank websites, and make myriad other decisions instantaneously. But what are the costs of their methods? And what exactly are they doing with their digital profiles of us? Leaks, whistleblowers, and legal disputes have shed new light on corporate surveillance and the automated judgments it enables. Self-serving and reckless behavior is surprisingly common, and easy to hide in code protected by legal and real secrecy. Even after billions of dollars of fines have been levied, underfunded regulators may have only scratched the surface of troublingly monopolistic and exploitative practices. Drawing on the work of social scientists, attorneys, and technologists, The Black Box Society offers a bold new account of the political economy of big data. Data-driven corporations play an ever larger role in determining opportunity and risk. But they depend on automated judgments that may be wrong, biased, or destructive. Their black boxes endanger all of us. Faulty data, invalid assumptions, and defective models can’t be corrected when they are hidden. Frank Pasquale exposes how powerful interests abuse secrecy for profit and explains ways to rein them in. Demanding transparency is only the first step. An intelligible society would assure that key decisions of its most important firms are fair, nondiscriminatory, and open to criticism. Silicon Valley and Wall Street need to accept as much accountability as they impose on others. In this interview with Lawrence Joseph, Frank Pasquale describes the aims and methods of the book

Analytic continuation of Wolynes theory into the Marcus inverted regime

The Wolynes theory of electronically nonadiabatic reaction rates [P. G. Wolynes, J. Chem. Phys. 87, 6559 (1987)] is based on a saddle point approximation to the time integral of a reactive flux autocorrelation function in the nonadiabatic (golden rule) limit. The dominant saddle point is on the imaginary time axis at $t_{\rm sp}=i\lambda_{\rm sp}\hbar$, and provided $\lambda_{\rm sp}$ lies in the range $-\beta/2\le\lambda_{\rm sp}\le\beta/2$, it is straightforward to evaluate the rate constant using information obtained from an imaginary time path integral calculation. However, if $\lambda_{\rm sp}$ lies outside this range, as it does in the Marcus inverted regime, the path integral diverges. This has led to claims in the literature that Wolynes theory cannot describe the correct behaviour in the inverted regime. Here we show how the imaginary time correlation function obtained from a path integral calculation can be analytically continued to $\lambda_{\rm sp}<-\beta/2$, and the continuation used to evaluate the rate in the inverted regime. Comparisons with exact golden rule results for a spin-boson model and a more demanding (asymmetric and anharmonic) model of electronic predissociation show that the theory it is just as accurate in the inverted regime as it is in the normal regime.Comment: 9 pages, 8 figure

Post-Election Audits: Restoring Trust in Elections

With the intention of assisting legislators, election officials and the public to make sense of recent literature on post-election audits and convert it into realistic audit practices, the Brennan Center and the Samuelson Law, Technology and Public Policy Clinic at Boalt Hall School of Law (University of California Berkeley) convened a blue ribbon panel (the "Audit Panel") of statisticians, voting experts, computer scientists and several of the nation's leading election officials. Following a review of the literature and extensive consultation with the Audit Panel, the Brennan Center and the Samuelson Clinic make several practical recommendations for improving post-election audits, regardless of the audit method that a jurisdiction ultimately decides to adopt

Health insurance for HIV prevention & treatment: predictors of health insurance enrollment among HIV+ women in Kenya

Background: The global push to achieve the 90-90-90 targets designed to end the HIV epidemic has called for the removing of policy barriers to prevention and treatment, and ensuring financial sustainability of HIV programs. Universal health insurance is one tool that can be used to this end. In sub-Saharan Africa, where HIV prevalence and incidence remain high, the use of health insurance to provide comprehensive HIV care is limited. This study looked at the factors that best predict social health insurance enrollment among HIV positive pregnant women using data from the Academic Model Providing Access to Healthcare (AMPATH) in western Kenya. Methods: Cross-sectional clinical encounter data were extracted from the electronic medical records (EMR) at AMPATH. We used univariate and multivariate logistic regressions to estimate the predictors of health insurance enrollment among HIV positive pregnant women. The analysis was further stratified by HIV disease severity (based on CD4 cell count ) to test the possibility of differential enrollment given HIV disease state. Results: Approximately 7% of HIV infected women delivering at a healthcare facility had health insurance. HIV positive pregnant women who deliver at a health facility had twice the odds of enrolling in insurance [2.46 Adjusted Odds Ratio (AOR), Confidence Interval (CI) 1.24-4.87]. They were 10 times more likely to have insurance if they were lost to follow-up to HIV care during pregnancy [9.90 AOR; CI 3.42-28.67], and three times more likely to enroll if they sought care at an urban clinic [2.50 AOR; 95% CI 1.53-4.12]. Being on HIV treatment was negatively associated with health insurance enrollment [0.22 AOR; CI 0.10-0.49]. Stratifying the analysis by HIV disease severity while statistically significant did not change these results. Conclusions: The findings indicated that health insurance enrollment among HIV positive pregnant women was low mirroring national levels. Additionally, structural factors, such as access to institutional delivery and location of healthcare facilities, increased the likelihood of health insurance enrollment within this population. However, behavioral aspects, such as being lost to follow-up to HIV care during pregnancy and being on HIV treatment, had an ambiguous effect on insurance enrollment. This may potentially be because of adverse selection and information asymmetries. Further understanding of the relationship between insurance and HIV is needed if health insurance is to be utilized for HIV treatment and prevention in limited resource settings.Othe