Eticas

The gold standard in automated bias detection + responsible AI compliance.

High school admissions in New York City

The New York City Department of Education has deployed algorithms in order to process student admissions into New York City’s public high school system. The system in place utilizes a multipurpose algorithm (called the ‘Gale-Shapley’ algorithm) that matches students with schools after evaluating a variety of criteria (Herold 2013). It processes a set of information from students and their parents, including a rank-ordered list of schools they prefer, and then institutional data, like certain qualities about each school and admissions rules (ibid). Various questions concerning the system have been raised. Firstly, on account of the algorithm’s metrics, students have a rather low probability to be admitted into one of their preferred public high schools in the city (Abrams 2017). Secondly, researchers have found evidence that the algorithm disproportionately matches lower-income students with lower-performing schools (Nathanson, Corcoran and Baker-Smith 2013). And, despite parents being entitled to know how students are assigned to schools and to see the metrics used by the algorithms at work, teachers and parents have reported receiving opaque and unclear decisions from the algorithm (Zimmer 2016).