As robotic systems advance in autonomy, they evolve into entities that no longer depend on constant human oversight. These systems, which once followed simple programming instructions, are becoming independent in their decision-making processes, often operating in environments where human intervention is minimal or delayed. Today, the vast majority of these autonomous robots remain under the custody of centralized entities—whether it’s a person managing their autonomous vehicle, a corporation overseeing fleets of drones, or a government running automated subway systems.

In these centralized structures, the entity that owns the robot also owns the actions of the robot. That is, when an autonomous car runs a red light, it’s the owner who faces the consequences. Likewise, when an autonomous drone delivers packages, the company that deployed it is responsible for the delivery. Ownership equates to custody—of both the robot and its actions. This centralized model works well for today’s robotic infrastructure but falls short in a world driven by decentralized principles, such as in network states.

In the context of a network state—a self-organized and decentralized group of entities (e.g., DAOs) operating on consensus—the centralized control of autonomous systems no longer applies. The very essence of decentralized governance challenges the traditional custody paradigm. So, how can a network state achieve self-custody over autonomous systems? To explore this, we must first delve into a more familiar realm: decentralized software.

Software as Precedent for Custody of Autonomous Systems Historically, software systems were centrally owned and operated—think apps, websites, or banks, all controlled by a single entity. Responsibility for these systems rested with their owners, just like the robots of today. However, the rise of blockchain introduced decentralized software systems, disrupting this ownership structure. These decentralized systems operate without central control, instead distributing control among a network of independent actors—miners or validators.

The key difference here is that while each validator processes different transactions, they collectively maintain a unified state. No one machine can independently control the system, and consensus among the network participants ensures security, accuracy, and consistency. These validators hold custody of the system in a decentralized manner. They manage the machines, which in turn manage the software—similar to how a centralized entity once managed both.

As decentralized software systems mature, their principles will naturally extend into decentralized hardware systems, particularly robotics. We already see hardware examples of this with Bitcoin mining, where Application-Specific Integrated Circuits (ASICs) perform a specialized task—mining blocks—while remaining in consensus with the network.

Non-Stationary Machines: Robots in a Decentralized World Imagine that these stationary machines, like ASIC miners, become non-stationary. Autonomous robots, capable of moving through the physical world, will perform actions while also remaining in consensus with a decentralized network. These machines would not just process calculations; they would execute physical tasks based on consensus rules.

In this model, each autonomous robot maintains its own state and action matrix—its internal log of decisions and movements. At predefined intervals, the robot submits this data to a validator for verification. Validators, acting as decentralized custodians, ensure that the robot’s actions align with the network’s agreed-upon rules. Should a robot fail to submit its state or should it deviate from the validator’s consensus, it would automatically cease operation until the conflict is resolved.

This form of robotic self-custody mirrors the structure of decentralized software, but it introduces an additional layer of complexity: the physical actions of the robot. While validators in blockchain networks ensure transaction accuracy, robotic validators would ensure the physical execution of tasks remains in line with decentralized principles. The robot’s ”state and action matrix” becomes its ledger—a record that validators must confirm.