February 6, 2023

Refining the Concept of a Nutritional Label for Data and Models

By Julia Stoyanovich (Assistant Professor of Computer Science at Drexel University)  and Bill Howe (Associate Professor in the Information School at the University of Washington) In August 2016,  Julia Stoyanovich and Ellen P. Goodman spoke in this forum about the importance of bringing interpretability to the algorithmic transparency debate.  They focused on algorithmic rankers, discussed the harms […]

Supplement for Revealing Algorithmic Rankers (Table 1)

Table 1: A ranking of Computer Science departments per csrankings.org, with additional attributes from the NRC assessment dataset. Here, the average count computes the geometric mean of the adjusted number of publications in each area by institution, faculty is the number of faculty in the department, pubs is the average number of publications per faculty […]

Revealing Algorithmic Rankers

By Julia Stoyanovich (Assistant Professor of Computer Science, Drexel University) and Ellen P. Goodman (Professor, Rutgers Law School) ProPublica’s story on “machine bias” in an algorithm used for sentencing defendants amplified calls to make algorithms more transparent and accountable. It has never been more clear that algorithms are political (Gillespie) and embody contested choices (Crawford), […]