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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.
The Belmont Report: Ethical principles and guidelines for the protection of human subjects of research
National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research · 1979
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Principles of Biomedical Ethics
Tom L. Beauchamp and James F. Childress · 2001
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Barriers to Clinical Trial Enrollment in Racial and Ethnic Minority Patients with Cancer
Lauren M. Hamel, Louis A. Penner, Terrance L. Albrecht, Elisabeth Heath, Clement K. Gwede, and Susan Eggly · 2016
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These Glasses Fool Facial Recognition Into Thinking You’re Someone Else
Madison Margolin · 2016
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Jacob Metcalf and Kate Crawford · 2016
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Targeted backdoor attacks on deep learning systems using data poisoning
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song · 2017
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Robust Physical-World Attacks on Deep Learning Models
Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Amir Rahmati, Chaowei Xiao, Atul Prakash, Tadayoshi Kohno, and Dawn Song · 2017
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Apps, arrests and abuse in Egypt, Lebanon and Iran
Article 19 · 2018
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Invisible, targeted infrared light can fool facial recognition software into thinking anyone is anyone else
Cory Doctorow · 2018
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LED Baseball Cap is Able to Fool Facial Recognition Tech
Luke Dormehl · 2018
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It’s Time to Do Something: Mitigating the Negative Impacts of Computing Through a Change to the Peer Review Process, March 2018
B. Hecht, L. Wilcox, J.P. Bigham, J. Schöning, E. Hoque, J. Ernst, Y. Bisk, L. De Russis, L. Yarosh, B. Anjum, D. Contractor, and C. Wu · 2018
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Considerations for ethics review of big data health research: A scoping review
Marcello Lenca, Agata Ferretti, Samia Hurst, Milo Puhan, Christian Lovis, and Effy Vayena · 2018
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People’s Councils for Ethical Machine Learning
Dan McQuillan · 2018
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S&E Indicators
National Science Foundation · 2018
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Invisible mask: Practical attacks on face recognition with infrared
Zhe Zhou, Di Tang, Xiaofeng Wang, Weili Han, Xiangyu Liu, and Kehuan Zhang · 2018
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AI Now 2019 Report
Kate Crawford, Roel Dobbe, Theodora Dryer, Genevieve Fried, Ben Green, Elizabeth Kaziunas, Amba Kak, Varoon Mathur, Erin McElroy, Andrea Nill Sánchez, Deborah Raji, Joy Lisi Rankin, Rashida Richardson, Jason Schultz, Sarah Myers West, and Meredith Whittaker · 2019
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AI won’t see you if you hold this color printout. So steer clear of any and all self-driving vehicles
Maria Dermentzi · 2019
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America under watch: Face surveillance in the united states
This colorful printed patch makes you pretty much invisible to AI
James Vincent · 2019
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Researchers foil people-detecting AI with an ‘adversarial’ T-shirt
Kyle Wiggers · 2019
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Adversarial t-shirt! Evading person detectors in a physical world
Kaidi Xu, Gaoyuan Zhang, S. Liu, Quanfu Fan, Mengshu Sun, H. Chen, Pin-Yu Chen, Yanzhi Wang, and X. Lin · 2019
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https://petsymposium.org/, 2020
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Clare Garvie and Laura M Moy · 2019
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Advhat: Real-world adversarial attack on arcface face id system
Stepan Komkov and Aleksandr Petiushko · 2019
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In hong kong protests, faces become weapons
Paul Mozur · 2019
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Dina-Temple Raston · 2019
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A general framework for adversarial examples with objectives
Mahmood Sharif, Sruti Bhagavatula, Lujo Bauer, and Michael K Reiter · 2019
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Sex and gender analysis improves science and engineering
Cara Tannenbaum, Robert P. Ellis, Friederike Eyssel, James Zou, and Londa Schiebinger · 2019
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Fooling automated surveillance cameras: Adversarial patches to attack person detection
Simen Thys, Wiebe Van Ranst, and Toon Goedemé · 2019
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These clothes use outlandish designs to trick facial recognition software into thinking you’re not human
Aaron Holmes · 2020
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The future of anti-surveillance fashion is bright (because the world is going to hell)
Rachel Kraus · 2020
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The Imperative for Transgender and Gender Nonbinary Inclusion
Heidi Moseson, Noah Zazanis, Eli Goldberg, Laura Fix, Mary Durden, Ari Stoeffler, Jen Hastings, Lyndon Cudlitz, Bori Lesser-Lee, Laz Letcher, Aneidys Reyes, and Juno Obedin-Maliver · 2020
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Adversarial Machine Learning: Difficulties in Applying Machine Learning Existing Cybersecurity Systems
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John Seabrook · 2020
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Making an invisibility cloak: Real world adversarial attacks on object detectors
Zuxuan Wu, Ser-Nam Lim, Larry Davis, and Tom Goldstein · 2020
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