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This paper introduces a socio-technical typology of bias in data-driven machine learning and artificial intelligence systems. The typology is linked to the conceptualisations of legal anti-discrimination regulations, so that the concept of structural inequality-and, therefore, of undesirable bias-is defined accordingly. By analysing the controversial Austrian "AMS algorithm" as a case study as well as examples in the contexts of face detection, risk assessment and health care management, this paper defines the following three types of bias: firstly, purely technical bias as a systematic deviation of the datafied version of a phenomenon from reality; secondly, socio-technical bias as a systematic deviation due to structural inequalities, which must be strictly distinguished from, thirdly, societal bias, which depicts-correctly-the structural inequalities that prevail in society. This paper argues that a clear distinction must be made between different concepts of bias in such systems in order to analytically assess these systems and, subsequently, inform political action.

This Article takes a fresh approach to Chevron deference. Chevron requires judges to defer to agency interpretations of statutes and justifies this on a theory of statutory authorization for agencies. This Article, however, points to a pair of constitutional questions about the role of judges – questions that have not yet been adequately asked, let alone answered. One question concerns independent judgment. Judges have a constitutional office or duty of independent judgment, under which they must exercise their own independent judgment about what the law is. Accordingly, when they defer to agency interpretations of the law, it must be asked whether they are violating their duty to exercise their own independent judgment. A second question concerns systematic bias. Under the Fifth Amendment right to the due process of law, judges cannot engage in systematic bias. Therefore, when they defer to agency interpretations of the law, it must be asked whether they are engaging in systematic bias in favor of the government and against Americans, thus denying them the due process of law. These constitutional questions require judges to reconsider Chevron. Rather than dwell on the usual statutory question about authorization, judges (including lower court judges) need to focus on the constitutional questions about their own role.

Introduction. Fairness, politics, and American media -- Point: journalists are out of touch with America -- Counterpoint: journalists' views do not affect their reporting -- Point: the media have a liberal bias -- Counterpoint: claims of "biased media" are exaggerated -- Point: concentrated media ownership harms the public -- Counterpoint: the media are healthier than ever -- Conclusion: reforming the media

We demonstrate that female incumbents are of higher average candidate quality than male incumbents. This quality difference is the result of barriers to entry faced by potential female candidates, although the observed effects of this quality differential on vote share are partially masked by the fact that female incumbents are also more likely to be opposed or to be opposed by high-quality challengers. Using data from House elections for 1984-1992, we estimate that the gender-based differential in candidate quality yields an extra six percentage points of vote share for female incumbents. 7 Tables, 1 Appendix, 32 References. Adapted from the source document.