[Benjamin Sobel] Abstract: This chapter addresses a crucial problem in artificial intelligence: many applications of machine learning depend on unauthorized uses of copyrighted data. Scholars and lawmakers often articulate this problem as a deficiency in copyright’s exceptions and limitations, reasoning that legal uncertainties surrounding today’s AI stem from the lack of a clear exception or limitation, and that such an exception or limitation could resolve the current predicament. In fact, the current predicament is a product of two systemic features of the copyright regime — the absence of formalities and the low threshold of copyright-able originality — combined with a technological environment that turns routine activities into acts of authorship. Equilibrating the economy for human expression in the AI age requires a solution that focuses not only on exceptions to existing copyrights, but also on the aforementioned doctrinal features that determine the ownership and scope of copyright entitlements at their inception.