Enacting the Pandemic: Analyzing Agency, Opacity, and Power in Algorithmic Assemblages

This article has two objectives: First, the article seeks to make a methodological intervention in the social study of algorithms. Second, the article traces ethnographically how an algorithm was used to enact a pandemic, and how the power to construct this disease outbreak was moved around through an algorithmic assemblage. The article argues that there is a worrying trend to analytically reduce algorithms to coherent and stable objects whose computational logic can be audited for biases to create fairness, accountability, and transparency (FAccT). To counter this reductionist and determinist tendency, the article proposes three methodological rules that allows an analysis of algorithmic power in practice. Empirically, the article traces the assembling of a recent epidemic at the European Centre for Disease Control and Prevention-the Zika outbreak starting in 2015-and shows how an epidemic was put together using an array of computational resources, with very different spaces for intervening. A key argument is that we, as analysts of algorithms, need to attend to how multiple spaces for agency, opacity, and power open and close in different parts of algorithmic assemblages. The crux of the matter is that actors experience different degrees of agency and opacity in different parts of any algorithmic assemblage. Consequently, rather than auditing algorithms for biased logic, the article shows the usefulness of examining algorithmic power as enacted and situated in practice

Dynamic equilibrium economies: a framework for comparing models and data

We propose a constructive, multivariate framework for assessing agreement between (generally misspecified) dynamic equilibrium models and data, a framework which enables a complete second-order comparison of the dynamic properties of models and data. We use bootstrap algorithms to evaluate the significance of deviations between models and data, and we use goodness-of-fit criteria to produce estimators that optimize economically relevant loss functions. We provide a detailed illustrative application to modeling the U.S. cattle cycle.Equilibrium (Economics) - Mathematical models ; Cattle trade

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks

In this work, we consider the distributed optimization of non-smooth convex functions using a network of computing units. We investigate this problem under two regularity assumptions: (1) the Lipschitz continuity of the global objective function, and (2) the Lipschitz continuity of local individual functions. Under the local regularity assumption, we provide the first optimal first-order decentralized algorithm called multi-step primal-dual (MSPD) and its corresponding optimal convergence rate. A notable aspect of this result is that, for non-smooth functions, while the dominant term of the error is in $O(1/\sqrt{t})$, the structure of the communication network only impacts a second-order term in $O(1/t)$, where $t$ is time. In other words, the error due to limits in communication resources decreases at a fast rate even in the case of non-strongly-convex objective functions. Under the global regularity assumption, we provide a simple yet efficient algorithm called distributed randomized smoothing (DRS) based on a local smoothing of the objective function, and show that DRS is within a $d^{1/4}$ multiplicative factor of the optimal convergence rate, where $d$ is the underlying dimension.Comment: 17 page

The U.S. system for measuring cross-border investment in securities: a primer with a discussion of recent developments

The tremendous growth in cross-border securities investment in recent years has called attention to the systems used by the United States and other countries to measure international securities flows and holdings. Ideally, the data gathered by the United States could tell us the extent to which foreign investors hold U.S. securities, the types of securities held, and the countries in which the securities are held, for example, and could identify trends in investment. This article looks at how well the data shed light on these topics. Special attention is given to the system's design and the implications of the design for data analysis. Also discussed are anticipated changes to the system and international efforts to improve data collection systems worldwide.International finance ; Securities

Virginia\u27s New Comprehensive Conflict of Interests Act: A Statutory Review

Recent news articles reflect the fact that conflict of interests problems can affect every person who serves the Commonwealth of Virginia in a governmental capacity. Public officers and employees are frequently faced with the Hobson\u27s choice of either remaining in public life at the expense of divestiture of their private financial holdings or running afoul of the conflict of interests laws. They are not only charged with knowledge of the Virginia Comprehensive Conflict of Interests Act, but are also required, in many instances, to take affirmative steps to avoid violating it. Thus, they must be aware of the situations in which they are particularly vulnerable to conflict of interests charges