Encrypted autonomous agent verification in multi-tiered distributed systems across global or cloud networks
Systems and methods disclosed herein perform privacy-preserving evaluations of artificial intelligence (AI) agents. A first AI agent associated with a first entity obtains a machine-readable data structure defining one or more operative boundaries for a second AI agent associated with a second entity. The system generates a unique fixed reference value representing the machine-readable data structure by applying a first transformation operation set, and transmits the unique fixed reference value to a multi-agent storage to store the value. The system receives, via the multi-agent storage, a verification artifact from the second AI agent that indicates an observed value based on internal operational data of the second AI agent corresponding to the operative boundaries. The first AI agent determines a verification status of the verification artifact by comparing the unique fixed reference value with the observed value, and autonomously generates a verification record including a representation of the verification status.
1 . A system for performing privacy-preserving evaluations of artificial intelligence (AI) agents, the system comprising:
at least one hardware processor; and
at least one non-transitory memory storing instructions, which, when executed by the at least one hardware processor, cause the system to:
obtain, via a first AI agent associated with a first entity, a machine-readable data structure that defines one or more operative boundaries for a second AI agent associated with a second entity,
wherein the machine-readable data structure indicates at least one of: a model parameter of the second AI agent, a data signal used in operation of the second AI agent, or information related to a completed computational operation of the second AI agent;
generate a unique fixed reference value representing the machine-readable data structure by applying a first transformation operation set on the machine-readable data structure;
transmit the unique fixed reference value to a multi-agent storage,
wherein the multi-agent storage is configured to store the unique fixed reference value in association with an identifier string identifying the first AI agent, and
wherein the multi-agent storage comprises a memory structure accessible to multiple AI agents including the first AI agent and the second AI agent;
receive, via the multi-agent storage, a verification artifact from the second AI agent that indicates an observed value generated by applying a second transformation operation set on one or more portions of an internal operational dataset of the second AI agent corresponding to the one or more operative boundaries;
determine, via the first AI agent, a first verification status of the verification artifact by comparing the unique fixed reference value generated by the first AI agent with the observed value indicated by the verification artifact;
autonomously generate a verification record including a representation of the first verification status for the verification artifact;
transmit the verification record to the multi-agent storage, wherein the verification record is stored in association with respective identifier strings identifying the first AI agent and the second AI agent;
generate, via the second AI agent, a second verification record including a representation of a second verification status for a third AI agent associated with a third entity; and
store the second verification record in the multi-agent storage in association with respective identifier strings identifying the second AI agent and the third AI agent.
2 . The system of claim 1 , wherein the first transformation operation set comprises at least one of: a cryptographic hash function, a keyed hash function, or a deterministic encoding function.
3 . The system of claim 1 , wherein the verification status indicates that the observed value fails to satisfy the unique fixed reference value, and wherein the system is further caused to:
transmit, by the first AI agent, a notification message to a predetermined network address indicating the verification status for the verification artifact.
4 . The system of claim 1 ,
wherein the verification artifact includes a zero-knowledge proof generated by the second AI agent,
wherein the zero-knowledge proof indicates that the internal operational dataset satisfies the one or more operative boundaries defined by the machine-readable data structure, and
wherein the verification status is determined using the zero-knowledge proof.
5 . The system of claim 1 , wherein the verification record further includes one or more of: a timestamp, a digital signature of the first AI agent, or an indication of the machine-readable data structure.
6 . A non-transitory, computer-readable storage medium comprising instructions thereon, wherein the instructions, when executed by at least one data processor of a system, cause the system to:
obtain, using a first AI agent associated with a first entity, a machine-readable data structure that defines one or more operative boundaries for a second AI agent associated with a second entity;
determine a unique fixed reference value representing the machine-readable data structure by applying a first transformation operation set on the machine-readable data structure;
transmit the unique fixed reference value to a multi-agent storage that is configured to store the unique fixed reference value in association with an identifier string identifying the first AI agent;
obtain, via the multi-agent storage, a verification artifact from the second AI agent that indicates an observed value generated by applying a second transformation operation set on one or more portions of an internal operational dataset of the second AI agent corresponding to the one or more operative boundaries;
determine, using the first AI agent, a verification status of the verification artifact by comparing the unique fixed reference value generated by the first AI agent with the observed value indicated by the verification artifact;
determine, using the first AI agent, a reputation score for the second AI agent based on a plurality of verification artifacts associated with the second AI agent; and
generate a verification record including a representation of the verification status for the verification artifact.
7 . The non-transitory, computer-readable storage medium of claim 6 , wherein the verification status indicates that the observed value satisfies the unique fixed reference value, and wherein the system is further caused to:
autonomously execute, using the first AI agent, one or more computer-implemented actions to transmit one or more portions of a respective internal operational dataset to the second AI agent.
8 . The non-transitory, computer-readable storage medium of claim 6 , wherein the reputation score is determined by one or more of:
a weighted average of one or more verification statuses indicating satisfaction of a respective observed value with a respective unique fixed reference value,
a decay value applied on one or more verification statuses based on a time since last failure of satisfaction of the respective observed value with the respective unique fixed reference value, or
a penalty value applied on one or more verification statuses indicating a failure of satisfaction of the respective observed value with the respective unique fixed reference value.
9 . The non-transitory, computer-readable storage medium of claim 6 , wherein the system is further caused to:
automatically approve, using the first AI agent, a transaction associated with the second AI agent in response to the reputation score exceeding a predetermined threshold.
10 . The non-transitory, computer-readable storage medium of claim 6 ,
assign, by the first AI agent, a probationary status to the second AI agent in response to the reputation score being within a predetermined range.
11 . The non-transitory, computer-readable storage medium of claim 10 ,
remove the probationary status from the second AI agent in response to the reputation score exceeding the predetermined range for a predetermined time period.
12 . A computer-implemented method for performing privacy-preserving evaluations of artificial intelligence (AI) agents, the computer-implemented method comprising:
obtain, using a first AI agent set associated with a first entity, a machine-readable data structure that defines one or more operative boundaries for a second AI agent set associated with a second entity;
determine reference data representing the machine-readable data structure by applying a first transformation operation set on the machine-readable data structure;
transmit the reference data to a storage structure that is configured to store the reference data in association with an identifier string identifying the first AI agent set;
obtain, via the storage structure, a verification artifact from the second AI agent set that indicates observed data generated by applying a second transformation operation set on one or more portions of an internal operational dataset of the second AI agent set corresponding to the one or more operative boundaries;
determining, using the first AI agent set, a reputation score for the second AI agent set based on a plurality of verification artifacts associated with a third AI agent set associated with a third entity;
determine, using the first AI agent set, a verification status of the verification artifact by comparing the reference data generated by the first AI agent set with the observed data indicated by the verification artifact; and
generate a verification record including a representation of the verification status for the verification artifact.
13 . The computer-implemented method of claim 12 , wherein the machine-readable data structure represents one or more of: organizational guidelines, industry standards, or provider criteria.
14 . The computer-implemented method of claim 12 , wherein the storage structure is a distributed ledger.
15 . The computer-implemented method of claim 14 , wherein the verification record is stored as a transaction on the distributed ledger.
16 . The computer-implemented method of claim 12 , wherein the first AI agent set includes a plurality of AI agents, further comprising:
determine, using each AI agent of the first AI agent set, an agent-specific verification status for a particular verification artifact; and
determining the verification status based on a number of respective agent-specific verification statuses indicating satisfaction of the second AI agent set with the one or more operative boundaries exceeding a predetermined threshold.
17 . The computer-implemented method of claim 12 ,
wherein the verification artifact is routed to a plurality of AI agents within the first AI agent set in a predetermined sequence, and
wherein each AI agent in the predetermined sequence is configured to generate an agent-specific verification status indicating satisfaction of the verification artifact with the one or more operative boundaries.