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NIST Artificial Intelligence (AI) 100-2 E2023, Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations
NIST Artificial Intelligence (AI) 100-2 E2023, Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations

First impression: This lit review boiled down to availability, integrity, abuse, and privacy. Poisoning and evasion. The motivation seems to be to formalize attacks so that another AI can respond, e.g. GANs. AVs are sketchy. Deepfake was left out. They already have competing supply chains and sanctions or economic interventions. It does not really get into the yet-to-be-released versions like for robotics. What makes ML different? Or Generative AI? This identifies flaws in existing systems and infrastructure, not what the next would be. Other versions might be evolutionary or deterministic. Look at personas and proxies. Some of this would come out of the ways they already beat tech. Capitalism continues to disrupt itself, but those become new standards. The same transcript might be interpreted by copilots as consumers, clinics, or culprits. "I didn't know anything about crypto when I first got involved. I barely knew what a blockchain was." -- SBF.

Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations
#Machine Learning#Taxonomy#NIST#Paper#PDF#Cybersecurity
·csrc.nist.gov·
NIST Artificial Intelligence (AI) 100-2 E2023, Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations
Greg Brockman on X: "One challenge with predicting the impact of a future technology is anticipating how the world will change in the interim. Describing Uber before the Internet, smartphones, and GPS seems quite hard—and yet for advanced AI we must. Fortunately, lots to learn from recent progress." / X
Greg Brockman on X: "One challenge with predicting the impact of a future technology is anticipating how the world will change in the interim. Describing Uber before the Internet, smartphones, and GPS seems quite hard—and yet for advanced AI we must. Fortunately, lots to learn from recent progress." / X
#AI#Forecasting#Futurism
·twitter.com·
Greg Brockman on X: "One challenge with predicting the impact of a future technology is anticipating how the world will change in the interim. Describing Uber before the Internet, smartphones, and GPS seems quite hard—and yet for advanced AI we must. Fortunately, lots to learn from recent progress." / X