Saved by Chad Hudson
Unsupervised Learning NO. 391
Fundamentally, the machine learning methodology used in modern AI systems is susceptible to attacks through the public APIs that expose the model, and against the platforms on which they are deployed. This report focuses on the former and considers the latter to be the scope of traditional cybersecurity taxonomies.
Apostol Vassilev • Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations
4.5 THE ROLE OF AI IN SURVEILLANCE: A DOUBLE-EDGED SWORD
Samuel Thorpe • The Essential Beginner’s Guide to AI
AI technology and machine learning are now being applied to a vast array of tasks—things like translating languages, autonomous self-driving vehicles, lip-reading, and facial recognition.
Gerry Valentine • The Thriving Mindset: Tools for Empowerment in a Disruptive World
Around 2014–15 the U.S. National Security Agency deployed an AI system called Skynet that placed people on a “suspected terrorists” list based on the electronic patterns of their communications, writings, travel, and social media postings. According to one report, that AI system “engages in mass surveillance of Pakistan’s mobile phone network, and
... See moreYuval Noah Harari • Nexus: A Brief History of Information Networks from the Stone Age to AI
Navigating the complexities of AI in surveillance is a delicate task.