40 citations · 51 across the 4 of their papers we have counts for
6 papers
"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…
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…
Legal Risks of Adversarial Machine Learning Research
Ram Shankar Siva Kumar, Jonathon Penney, Bruce Schneier +1
Adversarial Machine Learning is booming with ML researchers increasingly targeting commercial ML systems such as those used in Facebook, Tesla, Microsoft, IBM, Google to demonstrat…
Politics of Adversarial Machine Learning
Kendra Albert, Jonathon Penney, Bruce Schneier +1
In addition to their security properties, adversarial machine-learning attacks and defenses have political dimensions. They enable or foreclose certain options for both the subject…
Failure Modes in Machine Learning Systems
Ram Shankar Siva Kumar, David O Brien, Kendra Albert +2
In the last two years, more than 200 papers have been written on how machine learning (ML) systems can fail because of adversarial attacks on the algorithms and data; this number b…
Law and Adversarial Machine Learning
Ram Shankar Siva Kumar, David R. O'Brien, Kendra Albert +1
When machine learning systems fail because of adversarial manipulation, how should society expect the law to respond? Through scenarios grounded in adversarial ML literature, we ex…