Benhamou book challenges AI value allocation and copyright equity

A new book by Benhamou argues that current artificial intelligence value allocation models contain fundamental flaws regarding copyright equity. The publication asserts that existing systems systematically overlook contributors to creative works used in training datasets. Benhamou contends these inequities are embedded within current intellectual property frameworks rather than being accidental oversights. The analysis focuses specifically on marginalized creators whose labor enables generative models but who receive no compensation. This critique emerges as lawmakers globally debate opt-in consent and remuneration standards for AI training data. Industry stakeholders have not yet formally responded to the book’s specific allegations of structural bias. The work contributes to ongoing legal and ethical disputes over fair use in machine learning. It proposes reevaluating how economic value is assigned to human input in automated systems. The argument challenges prevailing industry assumptions about data sourcing legitimacy.