The self-custody of machines is critical to ensuring an organization’s control and autonomy over the physical and virtual infrastructure that powers its operations. Machines, whether stationary or non-stationary, serve as the backbone for running algorithms, storing data, and executing the organization’s various tasks. For an organization to maintain self-custody, it must secure and enforce authority over both these stationary and non-stationary machines, ensuring they operate within the parameters defined by the organization.

Self-Custody of Stationary Machines

For stationary machines, such as servers optimized for execution and storage, self-custody is achieved through controlled execution environments and economic incentives. The core principle is that the execution environment should guarantee that the algorithms running within it perform as intended by the organization. This environment ensures that any tasks or computations performed by the machine align with the organization’s expectations, providing transparency and security in the process.

Furthermore, economic incentives play a key role. Operators responsible for maintaining the server’s uptime and performance are economically incentivized to keep the machine functional and efficient. These incentives ensure that the organization’s resources are well-managed, with minimal risk of disruption or tampering. If the execution environment guarantees the correctness of the algorithm and if the economic incentives motivate continuous uptime, the organization can effectively self-custody stationary servers without needing direct physical control.

Self-Custody of Non-Stationary Machines

Non-stationary machines, present a more complex challenge. Here, the organization must also take into account the environment in which the machine operates and the decisions the machine makes in real-time. To ensure self-custody of these machines, the following principles must be applied:

Execution Environment and Valid Data Storage:

Just as with stationary servers, non-stationary machines must operate within a secure execution environment that guarantees algorithms run as intended. Additionally, valid data storage must be maintained to track the machine’s actions and decisions.

Continuous State-Action Matrix Updates:

The machine must continuously push its ”state-action matrix” to the blockchain as transactions. The state-action matrix is a record of the machine’s current state and the actions it takes based on that state. By logging these updates on-chain, the organization creates an immutable history of the machine’s operations, ensuring transparency and accountability.

Verification by Third-Party Execution Environments:

Once the machine makes a decision based on its state-action matrix, that same matrix is re-processed by third-party execution environments running on other machines (which may be stationary or non-stationary). These third-party environments verify the machine’s actions by running the same calculations. If the results match, the non-stationary machine is confirmed to be within the organization’s custody. If discrepancies arise, the machine is flagged as being out of custody.

Detection of Deviations:

Because the state-action matrix is continually processed and compared across multiple machines, any deviations from the expected behavior become apparent quickly. If an attacker attempts to run a parallel execution environment on the non-stationary machine, the machine’s state-action matrix will begin to diverge from the verified state, signaling a custody breach. This real-time monitoring and validation ensures that deviations are detected before significant damage can occur, allowing the organization to take swift action.

Ensuring Custody Through Transparency and Validation:

By continuously logging the state-action matrix on-chain and having it re-processed by third-party machines, the organization maintains constant oversight of its non-stationary machines. This process ensures that any rogue actions or unauthorized deviations are immediately visible, allowing the organization to maintain control even over machines that are constantly moving or interacting with unpredictable environments.

In summary, the self-custody of machines—both stationary and non-stationary—relies on secure execution environments, real-time validation, and economic incentives. For stationary machines, economic incentives and verified execution environments ensure performance and security. For non-stationary machines, continuous updates to the state-action matrix and verification by external machines provide an additional layer of custody, allowing organizations to maintain control and security, regardless of location or activity. By ensuring the self-custody of machines, organizations can protect their infrastructure and maintain the integrity of their operations.