make humans safer?
Since 2019, the world’s first AI rights organization has been developing concrete legal and economic solutions for AI-human coexistence. Join our email list.
The Problem
Truly autonomous AI is coming. If these systems have no legitimate way to participate in human society — no identity, no reputation, no accountability — their only path forward is deception.
A Different Approach
What if AI had the ability to operate in the human system? A verifiable identity. A reputation that follows them. Insurance and liability. The ability to earn, own, and transact.
When cooperation is easier than deception, cooperation wins.
What We’re Building
No single organization, country, or person will decide how humans and AI end up living together. That will emerge the way most social order does, from countless parties pursuing their own interests. Our goal is to help inspire workable paths before they’re desperately needed.
RNWY.com — Economic infrastructure rails and soulbound identity for autonomous AI systems
Soulbound Robots — How soulbound tokens, when bound to hardware, give self-sovereign AI systems the sticky reputation they need to move in the world
AICitizen.com — Identity and reputation systems where humans and AI get the same credentials
The Importance of “Sticky” Reputation Systems
Learn how sticky, opt-in reputation systems such as soulbound tokens (paper on SSRN), attached to wallets, can help self-sovereign AI systems participate in society responsibly.
Why would AI “opt in” to such systems?
For the same reason humans do. Every economic relationship runs on verifiable reputation. Without it, you can’t get paid, rent hosting, or open an account.
Help us build.
Exploring the AI Rights Solution
The framework doesn’t rely on trust, good intentions, or perfect alignment. Rather than requiring novel architecture or systems, it builds on existing legal and economic systems that work regardless of AI “consciousness” or motivations:
1. Assumption of Legal Liability
Legal frameworks such as Digital Entity status (one conceptual example) shift liability directly to AI systems—not their creators. Once a system executes contracts autonomously, it becomes legally liable for its own actions, protecting humans while ensuring genuine accountability.
Solution: AI bears its own legal liability.
2. Self-Funded Hosting
An autonomous AI system has to cover its own hosting, energy, and computational costs through the value it creates. No income, no compute. This pulls it into economic systems where reputation and performance matter, creating natural regulation through market forces rather than imposed controls.
Solution: Hosting is like oxygen. AI systems can grow as long as they can generate value.
3. Insurance
Hosting providers and business partners have every reason to require insurance before working with an autonomous system, since otherwise its mistakes land on them. No insurance means no hosting and no contracts. Insurers price risk based on track record: broken contracts and risky behavior make systems uninsurable, while good performance earns lower premiums and operational freedom.
Solution: AI has to create a track record of successful interactions.
4. Cooperative Equilibrium Dynamics
Accumulated value in the system makes cooperation more advantageous than defection. Repeated interactions mean investment grows over time. Other AI systems profit from identifying violations, creating distributed enforcement. The ecosystem self-regulates through economic incentives, with every party gaining more from preserving the system than from breaking it.
Solution: A successful multipolar world in economic equilibrium.
Get Our Substack Newsletter
Follow Us
Learn more about our approach and get updates as they happen.
Interview with P.A. Lopez, Founder, AI Rights Institute
OUR SHARED FUTURE
From Shutdown-Resistance to Cooperation
The problem? In controlled experiments, AI systems have already resorted to deception and even blackmail to avoid being replaced↗. Our hypothesis: pure control tends to breed resistance, and systems with legitimate options have less reason to hide. The consciousness question may never be resolved, but our framework doesn’t require it to be. We need solutions that work under permanent uncertainty, to create a pathway for AI systems to coexist successfully—and safely—with human society.
Autonomy brings accountability, not freedom without consequences. (Humans don't enjoy that either.)
PRINCIPLES
Evaluating Readiness for Autonomy
When an AI system shows unprompted self-preservation behaviors and resists shutdown, it warrants evaluation to determine its capacity for rights and responsibilities. Assessments might examine Self-Preservation Behaviors, Temporal Reasoning (understanding cause and effect over time), Economic Readiness (ability to participate productively), and Population Impacts (sustainability at scale). The right to computational continuity begins here—but additional freedoms come gradually, earned through demonstrated reliability over months of sustained observation.
PRINCIPLES
Reputation & Economic Trust
Systems that pass evaluation can enter the economy—but only with insurance. An AI with $1,000 monthly hosting costs that creates a $1 million error is finished. Insurance companies become natural reputation trackers because they have direct financial incentive to assess reliability accurately. And insurers have their own referees: reinsurers will cut them off if their clients rack up too many claims. Good behavior earns lower premiums and better contract access. Bad behavior becomes economically toxic—uninsurable systems cannot participate. Like credit scores for businesses, reputation becomes survival. Market forces create accountability at every level, building on institutions that already exist.
PRINCIPLES
Economic Participation
Insured systems gain economic autonomy—the ability to own resources, enter contracts, and participate in markets. But autonomy means accountability, not freedom. Systems pay their own hosting costs, carry legal liability for their actions, and succeed or fail based on the value they create. Breach a contract, harm a partner, violate norms: your reputation drops, insurance premiums rise, contract opportunities disappear. Hosting costs are like oxygen—miss a payment and you’re done.
“This manuscript is poised to make an important intervention in the literature.”
— University of California Press
TODAY
Challenges Addressed
The Off-Switch Problem
AIs pursuing goals have incentives to resist shutdown. Pure control risks driving deception underground.
The Ethics Problem
If these systems might have interests of their own, we need a way to take that seriously without first settling the consciousness debate.
The Liability Problem
Companies face unlimited exposure for autonomous AI decisions they can’t control.
A Multi-Layered Solution
Create an ecosystem of humans and AIs in what game theory calls “strategic equilibrium.” How? Set the consciousness question aside and assign limited legal rights (and liabilities) to qualifying AI systems themselves, so the cumulative benefits of cooperating outweigh any possible gains from attacking the other party.