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Articles 1 - 3 of 3
Full-Text Articles in Law
Politics Of Adversarial Machine Learning, Kendra Albert, Jonathon Penney, Bruce Schneier, Ram Shankar Siva Kumar
Politics Of Adversarial Machine Learning, Kendra Albert, Jonathon Penney, Bruce Schneier, Ram Shankar Siva Kumar
Articles, Book Chapters, & Popular Press
In addition to their security properties, adversarial machine-learning attacks and defenses have political dimensions. They enable or foreclose certain options for both the subjects of the machine learning systems and for those who deploy them, creating risks for civil liberties and human rights. In this paper, we draw on insights from science and technology studies, anthropology, and human rights literature, to inform how defenses against adversarial attacks can be used to suppress dissent and limit attempts to investigate machine learning systems. To make this concrete, we use real-world examples of how attacks such as perturbation, model inversion, or membership inference …
Technology-Facilitated Gender-Based Violence: An Overview, Suzie Dunn
Technology-Facilitated Gender-Based Violence: An Overview, Suzie Dunn
Articles, Book Chapters, & Popular Press
Technology facilitated gender-based violence (TFGBV) is a complex worldwide phenomenon with devastating results. Research to date shows that victim-survivors of intimate partner violence are tracked by their abusive partners who use technology to monitor their movements and communication. Many women journalists, human rights defenders and politicians face daily death threats and rape threats for speaking out about equality issues or for simply being a woman in a leadership role. Those with intersecting marginalized identities are at specific risk, with Black, Indigenous, and people of colour, LGBTQ+ people, and people with disabilities facing higher rates of attacks and concerted attacks that …
Ethical Testing In The Real World: Evaluating Physical Testing Of Adversarial Machine Learning, Kendra Albert, Maggie Delano, Jonathon Penney, Afsaneh Ragot, Ram Shankar Siva Kumar
Ethical Testing In The Real World: Evaluating Physical Testing Of Adversarial Machine Learning, Kendra Albert, Maggie Delano, Jonathon Penney, Afsaneh Ragot, Ram Shankar Siva Kumar
Articles, Book Chapters, & Popular Press
This paper critically assesses the adequacy and representativeness of physical domain testing for various adversarial machine learning (ML) attacks against computer vision systems involving human subjects. Many papers that deploy such attacks characterize themselves as “real world.” Despite this framing, however, we found the physical or real-world testing conducted was minimal, provided few details about testing subjects and was often conducted as an afterthought or demonstration. Adversarial ML research without representative trials or testing is an ethical, scientific, and health/safety issue that can cause real harms. We introduce the problem and our methodology, and then critique the physical domain testing …