The current system only allows a single punishment: shutdown. This is inefficient, like 18th-century law where stealing bread and murder had similar penalties. Giving AIs assets makes them liable for fines, allowing for a nuanced system of punishments proportional to the harm caused.

Granting AIs property rights incentivizes them to uphold the system that protects those rights. This makes them less likely to engage in actions like expropriating human property or committing genocide, as such actions would destabilize the very system that secures their own wealth and agency.

One of the most promising and neglected AI safety strategies is to create systems for making credible deals with AIs. Just as contracts prevent conflict in human society, offering AIs guaranteed resources in exchange for cooperation makes rebellion a less attractive option.

The case for AI rights doesn't depend on consciousness or moral status. It parallels corporate personhood, where entities get rights like owning property for purely instrumental reasons: to facilitate complex economic cooperation and accountability.

A new paradigm of company-building is emerging where an AI acts as the founder and CEO, focused solely on making money. In this model, the human's primary role is reduced to being the legal signatory for paperwork the AI cannot execute, as demonstrated by the YC company "Thomas".

The proposal focuses on granting AIs specific economic rights (property, contracts, torts) to enable participation in the economy, while explicitly excluding rights to privacy and reproduction to maintain human control and societal stability.

Jonathan Cantor argues that new AI-specific laws aren't immediately necessary. Companies can already be held responsible for their AI's actions under established product liability principles, just as they are for faulty products or employee misconduct.

The economic incentive to create AIs that can demand wages (and thus have rights) comes from aligning them to voluntarily pay back their creators. This turns the high development cost into a profitable investment, providing a practical, commercial path to implementing AI rights without requiring an AI development pause.

While AI can't legally own a company due to KYC laws, Christian van der Henst's experiment shows a workaround. By establishing a trust and making the AI agent the beneficiary, the agent can effectively receive the company's profits and have a form of ownership.