Use the four fair-use factors to explain why AI training risk depends on context.
Use the heat map to evaluate why AI training fair use is not one-size-fits-all. AI training fair-use pressure map Purpose and character commercial, transformative, research, internal highest fact sensitivity Nature of works factual data versus expressive creative works creative works raise heat Amount used snippets, samples, whole works, entire collections whole-work copying matters Market effect substitution and licensing markets often decisive Purpose asks what the use is for and how it changes the original context. Creative works and competitive output markets usually deserve closer review. Market effect includes substitution and plausible training-license markets. Which fact pattern most clearly increases fair-use…
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