On mapping values in AI Governance

We propose here a conceptual framework by which to analyze legal-regulatory problematics of algorithmic decision-making systems, focusing on mechanisms of value production in their design and deployment. An aim of our intervention is to develop an investigative model for application to algorithmic decision systems with regulatory effects, including predictive artificial intelligence applications and recommender systems that filter data and suggest courses of action. Technical systems that integrate complex algorithmic techniques perform critical and sensitive functions that are both object and instrument of regulatory governance, functions such as predicting behavior, steering information flows, assessing risk, etc. These functions, however, are not simple or static phenomena, but rather contextual, partial performances of complex socio-technical dynamics. One of our interests is to discern what is valorized in this new regulatory ecology. Accordingly, we are sketching a framework to target terms and tokens of value as they are produced, reproduced, incorporated, and translated among design processes, legal practices and background conditions structuring their use. Rather than asking which values AI should satisfy in contested governance contexts, we address conceptually prior questions concerning how values manifest and ‘map’ among context-sensitive computational and social processes in the first place. Furthermore, current research often takes for granted that an AI application is produced against the backdrop of a stable and pre-defined set of values and legal practices. Existing research does not yet adequately account for the ways in which laws and values as produced in and through the ecology of the AI application differ from idealized presuppositions assumed to preexist development of the latter. For the purpose, our contribution engages three broad lines of inquiry: one, we take forward calls for a materialized study of law, such as put forward broadly by Alain Pottage, and as put forward more recently and specifically with respect to computational technologies by Mireille Hildebrandt, among others; two, we contribute to the elaboration of a critical practice for AI, in the tradition of Philip Agre; and three, our attention to assemblages potentially contributes to debates over techno-regulation or regulation by design

Error analysis for mesospheric temperature profiling by absorptive occultation sensors

International audienceAn error analysis for mesospheric profiles retrieved from absorptive occultation data has been performed, starting with realistic error assumptions as would apply to intensity data collected by available high-precision UV photodiode sensors. Propagation of statistical errors was investigated through the complete retrieval chain from measured intensity profiles to atmospheric density, pressure, and temperature profiles. We assumed unbiased errors as the occultation method is essentially self-calibrating and straight-line propagation of occulted signals as we focus on heights of 50?100 km, where refractive bending of the sensed radiation is negligible. Throughout the analysis the errors were characterized at each retrieval step by their mean profile, their covariance matrix and their probability density function (pdf). This furnishes, compared to a variance-only estimation, a much improved insight into the error propagation mechanism. We applied the procedure to a baseline analysis of the performance of a recently proposed solar UV occultation sensor (SMAS ? Sun Monitor and Atmospheric Sounder) and provide, using a reasonable exponential atmospheric model as background, results on error standard deviations and error correlation functions of density, pressure, and temperature profiles. Two different sensor photodiode assumptions are discussed, respectively, diamond diodes (DD) with 0.03% and silicon diodes (SD) with 0.1% (unattenuated intensity) measurement noise at 10 Hz sampling rate. A factor-of-2 margin was applied to these noise values in order to roughly account for unmodeled cross section uncertainties. Within the entire height domain (50?100 km) we find temperature to be retrieved to better than 0.3 K (DD) / 1 K (SD) accuracy, respectively, at 2 km height resolution. The results indicate that absorptive occultations acquired by a SMAS-type sensor could provide mesospheric profiles of fundamental variables such as temperature with unprecedented accuracy and vertical resolution. A major part of the error analysis also applies to refractive (e.g., Global Navigation Satellite System based) occultations as well as to any temperature profile retrieval based on air density or major species density measurements (e.g., from Rayleigh lidar or falling sphere techniques)

Endstates in multichannel spinless p-wave superconducting wires

Multimode spinless p-wave superconducting wires with a width W much smaller than the superconducting coherence length \xi are known to have multiple low-energy subgap states localized near the wire's ends. Here we compare the typical energies of such endstates for various terminations of the wire: A superconducting wire coupled to a normal-metal stub, a weakly disordered superconductor wire and a wire with smooth confinement. Depending on the termination, we find that the energies of the subgap states can be higher or lower than for the case of a rectangular wire with hard-wall boundaries.Comment: 10 pages, 7 figure

From a kinetic equation to a diffusion under an anomalous scaling

A linear Boltzmann equation is interpreted as the forward equation for the probability density of a Markov process (K(t), i(t), Y(t)), where (K(t), i(t)) is an autonomous reversible jump process, with waiting times between two jumps with finite expectation value but infinite variance, and Y(t) is an additive functional of K(t). We prove that under an anomalous rescaling Y converges in distribution to a two-dimensional Brownian motion. As a consequence, the appropriately rescaled solution of the Boltzmann equation converges to a diffusion equation

Scattering of rare-gas atoms at a metal surface: evidence of anticorrugation of the helium-atom potential-energy surface and the surface electron density

Recent measurements of the scattering of He and Ne atoms at Rh(110) suggest that these two rare-gas atoms measure a qualitatively different surface corrugation: While Ne atom scattering seemingly reflects the electron-density undulation of the substrate surface, the scattering potential of He atoms appears to be anticorrugated. An understanding of this perplexing result is lacking. In this paper we present density functional theory calculations of the interaction potentials of He and Ne with Rh(110). We find that, and explain why, the nature of the interaction of the two probe particles is qualitatively different, which implies that the topographies of their scattering potentials are indeed anticorrugated.Comment: RevTeX, 4 pages, 10 figure