Governing Copyright Responsibly in the Era of Generative AI

URL SCAN: Governing Copyright Responsibly in the Era of Generative AI
FIRST LINE: # Computer Science > Computers and Society

The Dissection

This paper is a forensic inventory of legal lag presented as a governance solution. Its coding of 40 instruments, 1,337 category assignments, and 835 segments usefully exposes procedural protection, weak reflexivity, and the absence of a general author-facing attribution duty. But its central maneuver is to convert industrial extraction and labor substitution into an administrative allocation problem: assign responsibilities to developers, publishers, collecting societies, funders, institutions, regulators, and authors, then call the system responsible.

It maps the paperwork surrounding the transformation of authorship into training fuel. It does not seriously confront whether authors remain economically necessary once models can absorb, recombine, and underprice cognitive work.

The Core Fallacy

The paper confuses governance of extraction with preservation of the extracted class.

Attribution, transparency, provenance, reporting, and compensation mechanisms may improve evidence, bargaining power, or rent capture for organized rights-holders. They do not restore mass demand for human authors, wages, or productive participation. Under P1–P3, copyright is a lag defense: it can delay, document, or redistribute the consequences of automation, but it cannot force an AI economy to continue requiring human creative labor.

The six-instrument design may regulate the carcass. It cannot resurrect the labor-consumption circuit.

Hidden Assumptions

• Training-use provenance can be collected accurately and cheaply across opaque, multinational data pipelines.
• Legal duties can be enforced across jurisdictions faster than developers can relocate, restructure, or automate around them.
• Benefits will reach individual authors rather than concentrate in publishers, platforms, collecting societies, and large rights aggregators.
• Attribution or payment can offset the economic effect of substitution rather than merely create a thin licensing rent.
• Individual authors possess enough coordination and bargaining capacity to use the proposed protections.
• Responsible Research and Innovation categories predict material economic outcomes rather than describing institutional self-presentation.
• Better copyright governance can preserve a meaningful human economic domain at scale.

Social Function

Primary classification: partial truth serving transition management, with an ideological-anesthetic effect.

The paper accurately identifies governance failure. Its anesthetic function is the reframing: the central crisis becomes insufficient procedure, responsibility allocation, and reflexivity instead of ownership and control of AI capital and the collapse of productive participation. Institutions receive a respectable vocabulary for appearing responsive while the underlying extraction regime remains intact.

Its reforms could create narrow survival niches for sovereign publishers, rights aggregators, verification intermediaries, and authors with defensible catalogues. That is rent capture for organized survivors, not rescue for authors as a class.

The Verdict

This is a competent map of the legal smoke alarm, not fire suppression. It documents institutions waking late to discover that authors lack visibility into a machine that may make their labor optional. The proposed governance architecture can improve auditability, bargaining, and limited redistribution. It cannot defeat P1–P3 or reverse the death of post-WWII capitalism. Under the Discontinuity Thesis, this is transition management: rules for pricing and documenting the carcass, not a mechanism to bring the animal back to life.