F-Secure releases a taxonomy of 26 AI consumer harms
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F-Secure has released a taxonomy of harms for consumer AI, organizing 26 harms by "intervention point," covering five relationship categories: chatbot→consumer, agent→consumer, threat actor→consumer, threat actor→agent, and threat actor→chatbot. Each harm is traced through 19 intermediate layers—including foundation models, agent runtimes, memory storage, and consumer devices—to a specific defense location. The taxonomy notes that many harms can only be fixed by the companies that develop the models and operate the products.
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- Hacker News AITaxonomy of 26 Ways AI Can Make Your Life Worse
A principal threat intelligence researcher presents a taxonomy of 26 consumer AI harms across five relationship types—chatbot to consumer, agent to consumer, threat actor to consumer, threat actor to agent, and threat actor to chatbot—organized around points of intervention rather than a direct harm-to-defense mapping. Each harm is traced through one or more of 19 intermediary layers, such as a foundation model, agent runtime, memory store, or consumer device, with defenses attached where they would actually have to be built. The author notes many harms can only be fixed by the companies making the models and running the products, and that the work in progress has thin evidence for some entries.
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