Certifying and removing disparate impact

What does it mean for an algorithm to be biased? In U.S. law, unintentional bias is encoded via disparate impact, which occurs when a selection process has widely different outcomes for different groups, even as it appears to be neutral. This legal determination hinges on a definition of a protected class (ethnicity, gender, religious practice) and an explicit description of the process. When the process is implemented using computers, determining disparate impact (and hence bias) is harder. It might not be possible to disclose the process. In addition, even if the process is open, it might be hard to elucidate in a legal setting how the algorithm makes its decisions. Instead of requiring access to the algorithm, we propose making inferences based on the data the algorithm uses. We make four contributions to this problem. First, we link the legal notion of disparate impact to a measure of classification accuracy that while known, has received relatively little attention. Second, we propose a test for disparate impact based on analyzing the information leakage of the protected class from the other data attributes. Third, we describe methods by which data might be made unbiased. Finally, we present empirical evidence supporting the effectiveness of our test for disparate impact and our approach for both masking bias and preserving relevant information in the data. Interestingly, our approach resembles some actual selection practices that have recently received legal scrutiny.Comment: Extended version of paper accepted at 2015 ACM SIGKDD Conference on Knowledge Discovery and Data Minin

Progress report on a new search for free e/3 quarks in the cores of 10(15) - 10(16) eV air showers

The Leeds 3 sq m Wilson cloud chamber is being used in a new search for free e/3 quarks close to the axes of 10 to the 15th power - 10 to the 16th power eV air showers. A ratio trigger circuit is used to detect the incidence of air shower cores; the position of the shower center and the axis direction are determined from photographs of current-limited spark chambers. It is thus possible, for the first time, to know where we have looked for quarks in air showers and to select for scanning only those cloud chamber photographs where we have good evidence that the shower axis was close to the chamber. 250 g/sq cm of lead/concrete absorber above the cloud chamber serve to reduce particle densities and make a quark search possible very close to the shower axes. The current status of the search is given

The asparagus rust in Iowa.

During the summer our attention was called to the appearance of Asparagus Rust on Muscatine Island by Mrs. Alice Walton Beatty. Early in September the rust was found in considerable quantities in one of the asparagus beds on the college farm; since then it has been observed at many points by ourselves and Mr. M. Cumming, in and about Ames. It was also reported to us from McBride, Iowa, by Mr. H. A. Mueller, in September, 1900, as being abundant at that place and at Mt. Pleasant by Mr. E. E. Hodson

Soil pH governs production rate of calcium carbonate secreted by the earthworm Lumbricus terrestris

Lumbricus terrestris earthworms exposed to 11 soils of contrasting properties produced, on average, 0.8 ± 0.1 mgCaCO3 earthworm−1 day−1 in the form of granules up to 2 mm in diameter. Production rate increased with soil pH (r2 = 0.68, p < 0.01). Earthworms could be a significant source of calcite in soils

Dynamical trapping and relaxation of scalar gravitational fields

We present a framework for nonlinearly coupled scalar-tensor theory of gravity to address both inflation and core-collapse supernova problems. The unified approach is based on a novel dynamical trapping and relaxation of scalar gravity in highly energetic regimes. The new model provides a viable alternative mechanism of inflation free from various issues known to affect previous proposals. Furthermore, it could be related to observable violent astronomical events, specifically by releasing a significant amount of additional gravitational energy during core-collapse supernovae. A recent experiment at CERN relevant for testing this new model is briefly outlined.Comment: 4 pages; version to appear in PL

The surface area and reactivity of granitic soils: I. Dissolution rates of primary minerals as a function of depth and age deduced from field observations

Surface area-normalised dissolution rates of the primary minerals in two distinct granitic soils located in 1) the Dartmoor National Park, England and 2) Glen Dye, Scotland were determined as a function of depth. Each soil was sampled to a depth of ~ 1 m. The maximum soil ages based on 14C analysis of the humin fraction of the soil are 15,600 and 4400 years for the Dartmoor and Glen Dye soil profiles, respectively. The measured BET surface areas of the soil minerals are close to 5 m2/g in the B and C horizons, but decrease to less than 1 m2/g close to the surface. Retrieved geometric surface area normalised mineral dissolution rates are most rapid at the surface and at the bedrock–soil interface; this behaviour is interpreted to stem from a combination of the approach to equilibrium of the soil waters with depth and more rapid dissolution rates of fresh versus weathered surfaces. At the soil surface, the relative mineral dissolution rate order is found to be quartz > feldspar > mica, with quartz geometric surface area dissolution rates as fast as 2.6 to 4.1 × 10− 13 mol/m2/s. As observed in a number of past studies, field based rates obtained in this study are significantly slower than corresponding rates obtained from laboratory studies, suggesting that these latter rates may not accurately describe the reactivity of primary minerals in soils

A Physical Interpretation of Stagnation Pressure and Enthalpy Changes in Unsteady Flow

This paper provides a physical interpretation of the mechanism of stagnation enthalpy and stagnation pressure changes in turbomachines due to unsteady flow, the agency for all work transfer between a turbomachine and an inviscid fluid. Examples are first given to illustrate the direct link between the time variation of static pressure seen by a given fluid particle and the rate of change of stagnation enthalpy for that particle. These include absolute stagnation temperature rises in turbine rotor tip leakage flow, wake transport through downstream blade rows, and effects of wake phasing on compressor work input. Fluid dynamic situations are then constructed to explain the effect of unsteadiness, including a physical interpretation of how stagnation pressure variations are created by temporal variations in static pressure; in this it is shown that the unsteady static pressure plays the role of a time-dependent body force potential. It is further shown that when the unsteadiness is due to a spatial nonuniformity translating at constant speed, as in a turbomachine, the unsteady pressure variation can be viewed as a local power input per unit mass from this body force to the fluid particle instantaneously at that point

Google DeepMind and healthcare in an age of algorithms

Data-driven tools and techniques, particularly machine learning methods that underpin artificial intelligence, offer promise in improving healthcare systems and services. One of the companies aspiring to pioneer these advances is DeepMind Technologies Limited, a wholly-owned subsidiary of the Google conglomerate, Alphabet Inc. In 2016, DeepMind announced its first major health project: a collaboration with the Royal Free London NHS Foundation Trust, to assist in the management of acute kidney injury. Initially received with great enthusiasm, the collaboration has suffered from a lack of clarity and openness, with issues of privacy and power emerging as potent challenges as the project has unfolded. Taking the DeepMind-Royal Free case study as its pivot, this article draws a number of lessons on the transfer of population-derived datasets to large private prospectors, identifying critical questions for policy-makers, industry and individuals as healthcare moves into an algorithmic age

The person-based nature of prejudice: Individual difference predictors of intergroup negativity

Person-based factors influence a range of meaningful life outcomes, including intergroup processes, and have long been implicated in explaining prejudice. In addition to demonstrating significant heritability, person-based factors are evident in expressions of generalised prejudice, a robust finding that some people (relative to others) consistently score higher in prejudice towards multiple outgroups. Our contemporary review includes personality factors, ideological orientations (e.g., authoritarianism), religiosity, anxiety, threat, disgust sensitivity, and cognitive abilities and styles. Meta-analytic syntheses demonstrate that such constructs consistently predict prejudice, often at the upper bounds of effect sizes observed in psychological research. We conclude that prejudice theories need to better integrate person- and situation-based factors, including their interaction, to capture the complexity of prejudice and inform intervention development