Awareness in Practice: Tensions in Access to Sensitive Attribute Data for Antidiscrimination

Organizations cannot address demographic disparities that they cannot see. Recent research on machine learning and fairness has emphasized that awareness of sensitive attributes, such as race and sex, is critical to the development of interventions. However, on the ground, the existence of these data cannot be taken for granted. This paper uses the domains of employment, credit, and healthcare in the United States to surface conditions that have shaped the availability of sensitive attribute data. For each domain, we describe how and when private companies collect or infer sensitive attribute data for antidiscrimination purposes. An inconsistent story emerges: Some companies are required by law to collect sensitive attribute data, while others are prohibited from doing so. Still others, in the absence of legal mandates, have determined that collection and imputation of these data are appropriate to address disparities. This story has important implications for fairness research and its future applications. If companies that mediate access to life opportunities are unable or hesitant to collect or infer sensitive attribute data, then proposed techniques to detect and mitigate bias in machine learning models might never be implemented outside the lab. We conclude that today's legal requirements and corporate practices, while highly inconsistent across domains, offer lessons for how to approach the collection and inference of sensitive data in appropriate circumstances. We urge stakeholders, including machine learning practitioners, to actively help chart a path forward that takes both policy goals and technical needs into account

Cross-Sector Review of Drivers and Available 3Rs Approaches for Acute Systemic Toxicity Testing

Acute systemic toxicity studies are carried out in many sectors in which synthetic chemicals are manufactured or used and are among the most criticized of all toxicology tests on both scientific and ethical grounds. A review of the drivers for acute toxicity testing within the pharmaceutical industry led to a paradigm shift whereby in vivo acute toxicity data are no longer routinely required in advance of human clinical trials. Based on this experience, the following review was undertaken to identify (1) regulatory and scientific drivers for acute toxicity testing in other industrial sectors, (2) activities aimed at replacing, reducing, or refining the use of animals, and (3) recommendations for future work in this area

Nonpoor children in head start: Explanations and implications

According to the Head Start Act (1998), children are income-eligible for the program if their “families' incomes are below the poverty line.” There are a number of statutory exceptions to this general rule and, according to the Head Start Bureau, the result is that about 6 percent of the children in the program are not poor. But the major national surveys of Head Start families report that 30 percent or more of Head Start children are not “poor.” This paper confirms and explains the high proportion of nonpoor children in Head Start: at enrollment, at least 28 percent are not poor; at midyear, at least 32 percent are not poor; and by the end of the program year, at least 34 percent and perhaps more than 50 percent are not poor. Although the presence of some of these nonpoor children seems to be an appropriate or at least understandable aspect of running a national program with Head Start's current organizational structure, the presence of others seems much less warranted and raises substantial questions of horizontal equity. Moreover, taken together, the large number of nonpoor children suggests that the program is not well targeted to fulfill its mission of providing compensatory services to developmentally disadvantaged children-and reveals the essential ambiguity of Head Start's role in the wider world of early care and education. The income and program dynamics that have led to so many nonpoor children being in Head Start are also at work in many other programs, and, thus, our findings demonstrate the need to understand better how income eligibility is determined across various means-tested programs.

Accessibility: Global Gateway to Health Literacy

Abstract available at publisher's web site