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Articles 1 - 4 of 4
Full-Text Articles in Law
Dispute Settlement Under The African Continental Free Trade Area Agreement: A Preliminary Assessment, Olabisi D. Akinkugbe
Dispute Settlement Under The African Continental Free Trade Area Agreement: A Preliminary Assessment, Olabisi D. Akinkugbe
Articles, Book Chapters, & Popular Press
The African Continental Free Trade Area Agreement (AfCFTA) will add a new dispute settlement system to the plethora of judicial mechanisms designed to resolve trade disputes in Africa. Against the discontent of Member States and limited impact the existing highly legalized trade dispute settlement mechanisms have had on regional economic integration in Africa, this paper undertakes a preliminary assessment of the AfCFTA Dispute Settlement Mechanism (DSM). In particular, the paper situates the AfCFTA-DSM in the overall discontent and unsupportive practices of African States with highly legalized dispute settlement systems and similar WTO-Styled DSMs among other shortcomings. Notwithstanding the transplantation of …
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 …
Legal Risks Of Adversarial Machine Learning Research, Ram Shankar Siva Kumar, Jonathon Penney, Bruce Schneier, Kendra Albert
Legal Risks Of Adversarial Machine Learning Research, Ram Shankar Siva Kumar, Jonathon Penney, Bruce Schneier, Kendra Albert
Articles, Book Chapters, & Popular Press
Adversarial machine learning is the systematic study of how motivated adversaries can compromise the confidentiality, integrity, and availability of machine learning (ML) systems through targeted or blanket attacks. The problem of attacking ML systems is so prevalent that CERT, the federally funded research and development center tasked with studying attacks, issued a broad vulnerability note on how most ML classifiers are vulnerable to adversarial manipulation. Google, IBM, Facebook, and Microsoft have committed to investing in securing machine learning systems. The US and EU are likewise putting security and safety of AI systems as a top priority.
Now, research on adversarial …
Identity Manipulation: Responding To Advances In Artificial Intelligence And Robotics, Suzie Dunn
Identity Manipulation: Responding To Advances In Artificial Intelligence And Robotics, Suzie Dunn
Articles, Book Chapters, & Popular Press
Advances in artificial intelligence (AI) and robotics technologies have destabilized our ability to control our identity. Today, it is increasingly accessible for the average person to appropriate the voice, image, and body of another individual through the use of technology. Deepfake videos swap new faces into existing videos, facial re-enactment allows for the face of one person to be superimposed on the face of someone else in a real time video, artificial speech synthesis can clone another person’s voice, and 3D printing and modern robotics can reproduce life-size copies of living people. These are all examples of the ways technology …