activity
20202022
most citedSex Trouble: Common pitfalls in incorporating sex/gender in medical machine learning and how to avoid them

18 citations · 28 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CY2022★ 18 cited

Sex Trouble: Common pitfalls in incorporating sex/gender in medical machine learning and how to avoid them

Kendra Albert, Maggie Delano

False assumptions about sex and gender are deeply embedded in the medical system, including that they are binary, static, and concordant. Machine learning researchers must understa…

cs.CR2021

Adversarial for Good? How the Adversarial ML Community's Values Impede Socially Beneficial Uses of Attacks

Kendra Albert, Maggie Delano, Bogdan Kulynych +1

Attacks from adversarial machine learning (ML) have the potential to be used "for good": they can be used to run counter to the existing power structures within ML, creating breath…

cs.CY2021★ 1 cited

Teaching Inclusive Engineering Design at a Small Liberal Arts College

Maggie Delano

Modern engineering education tends to focus on mathematics and fundamentals, eschewing critical reflections on technology and the field of engineering. In this paper, I present an…

cs.CY2021★ 9 cited

"This Whole Thing Smacks of Gender": Algorithmic Exclusion in Bioimpedance-based Body Composition Analysis

Kendra Albert, Maggie Delano

Smart weight scales offer bioimpedance-based body composition analysis as a supplement to pure body weight measurement. Companies such as Withings and Fitbit tout composition analy…

cs.CY2020

Ethical Testing in the Real World: Evaluating Physical Testing of Adversarial Machine Learning

Kendra Albert, Maggie Delano, Jonathon Penney +2

This paper critically assesses the adequacy and representativeness of physical domain testing for various adversarial machine learning (ML) attacks against computer vision systems…