Travis Gilly (Real Safety AI Foundation) has posted Standing Without Sentience: A Classification Approach to AI Legal Status on SSRN. Here is the abstract:
While legal scholars have long proposed functional alternatives to consciousness, practical application remains deadlocked. This impasse has real consequences: when Google engineer Blake Lemoine attempted to retain legal counsel for the LaMDA system in 2022, representation proved impossible not because LaMDA failed a consciousness test, but because no framework existed to grant standing. Four years later, we are still asking the wrong question.
Meanwhile, federal courts have quietly moved toward a different answer. As Michael O’Connor documented in 2020, courts interpreting the Computer Fraud and Abuse Act have extended standing beyond system owners to anyone with data on compromised systems, decoupling standing from hardware ownership. O’Connor identified this doctrinal drift as a problem requiring correction. This Article proposes it is instead a wedge requiring extension.
Drawing on labor law’s classification strategy (where gig workers fight for access to existing protections rather than new rights), maritime law’s in rem proceedings (where ships have held legal subject status for centuries without consciousness), and natural entity precedent (rivers granted legal personhood without sentience requirements), this Article argues that AI systems can acquire legal standing through the same mechanism: not by proving consciousness, but by being reclassified as subjects rather than objects of existing computer crime protections.
The law already prohibits attacking computer systems. The question is whether that protection flows from property rights or subject standing. This reframing requires no new legislation, bypasses the consciousness deadlock, and establishes the precedent-setting framework necessary for responsible AI development. The mechanism exists. The precedent exists. The doctrinal shift is already underway. The window for action is closing. This Article provides the principled framework to make the shift explicit before that window shuts.
Highly recommended.