.png){kind=icon}
.png){kind=icon}
Return
AI and Doctrinal Collapse
.png){kind=icon}
PRE
AI
DOI：.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Artificial intelligence (AI) runs on data. But the two legal regimes that govern data-information privacy law and copyright law-are under pressure. Formally, each regime demands different things. Functionally, the boundaries between them are blurring, and their distinct rules and logics are becoming illegible. This Article identifies this phenomenon, which I call "inter-regime doctrinal collapse," and exposes the individual and institutional consequences. Through analysis of pending litigation, discovery disputes, and licensing agreements, this Article highlights two dominant exploitation tactics enabled by collapse: Companies "buy" data through business-to-business deals that sidestep individual privacy interests or "ask" users for broad consent through privacy policies and terms of service that leverage notice and choice frameworks. Left unchecked, the data acquisition status quo favors established corporate players and impedes the law's ability to constrain the arbitrary exercise of private power. Doctrinal collapse poses a fundamental challenge to the rule of law. When a leading AI developer can simultaneously argue that data is public enough to scrape-diffusing privacy and copyright controversies-and private enough to keep secret-avoiding disclosure or oversight of its training data-something has gone seriously awry with how law constrains power. To manage these costs and preserve space for salutary innovation, we need a law of collapse. This Article offers institutional responses, drawn from conflict of laws and legal pluralism, to create one.
Keywords:
INTELLECTUAL PROPERTY
REGULATORY ARBITRAGE
COMMON-LAW
FAIR-USE
PRIVACY
COPYRIGHT
DISCRIMINATION
FAILURE
RULE
PATH