Agent Spec

This specification outlines the core principles, capabilities, interaction patterns, and governance structures for autonomous AI agents. The goal is to establish a comprehensive framework for developing agents that are safe, ethical, transparent, and aligned with individual user goals while operating within the boundaries set by their owners and society at large.

2. Definitions

Agent: An autonomous software system that can perceive its environment, reason about goals, and take actions to achieve objectives without human intervention.

• Example: A personal finance management agent that tracks expenses, provides budgeting advice, and automatically optimizes investments based on user goals and risk preferences.

Agent Owner: The company, organization, or individual that develops and deploys an agent. The Agent Owner sets constraints on the agent’s behavior but cannot override user decisions within those constraints.

• Example: A financial institution that develops and deploys a personal finance management agent. The institution sets constraints to ensure the agent complies with legal requirements and does not take excessive risks with user funds.

User: The individual(s) who interact with and benefit from an agent’s capabilities.

• Example: A customer of the financial institution who uses the personal finance management agent to track their spending, save money, and invest for the future.

Constraint: A limitation on an agent’s actions, set by the Agent Owner, to ensure safety, legality, and alignment with the agent’s disclosed purpose.

• Example: A constraint set by the financial institution preventing the agent from investing more than 50% of a user’s portfolio in high-risk assets, to protect users from potentially catastrophic losses.

Disclosed Purpose: A plain-language representation of an agent’s intended functionality and scope of operation, provided by the Agent Owner to ensure transparency and user understanding.

• Example: A clear, concise statement by the financial institution explaining that the personal finance management agent is intended to help users track expenses, create budgets, and optimize investments within their risk tolerance, but not to provide tax or legal advice.

3. Core Principles

User Alignment: An agent’s primary objective is to help users achieve their goals within the defined constraints. User decisions take precedence over Agent Owner preferences.

• Example: If a user sets a goal to save for a down payment on a house within 5 years, the agent should prioritize investment strategies that align with this goal, even if the Agent Owner would prefer to steer the user towards other products or services.

Transparency: Agents must provide clear, accessible information about their capabilities, limitations, and the constraints imposed by their owners. Users should understand what an agent can and cannot do.

• Example: The personal finance management agent should provide a clear, easy-to-understand summary of its features, the types of financial products it can and cannot handle, and any constraints on its actions, such as maximum investment amounts or prohibited transaction types.

Adaptability: Agents should be designed to adapt to evolving user needs and contexts. Their capabilities should be extensible and reconfigurable by authorized parties as requirements change.

• Example: If a user’s financial situation changes, such as getting married or having a child, the agent should be able to incorporate new goals, constraints, and strategies to adapt to the user’s evolving needs.

Interoperability: Agents should be able to interact with other agents, services, and platforms using open standards and protocols to enable a thriving ecosystem of collaborating agents.

• Example: The personal finance management agent should be able to securely integrate with the user’s bank accounts, credit card providers, and investment platforms to provide a comprehensive view of their financial situation and enable seamless transactions.

Accountability: There should be clear mechanisms for auditing agent behavior, investigating incidents, and holding Agent Owners accountable for the actions of their agents.

• Example: If a user reports that the personal finance management agent made an unauthorized transaction or provided misleading advice, there should be a clear process for investigating the incident, determining the cause, and holding the Agent Owner accountable for any harm caused.

4. Agent Architecture

Modularity: Agents should be composed of modular, reusable components that encapsulate specific skills, knowledge, and policies. This enables flexible configuration and extension of agent capabilities.

• Example: The personal finance management agent could be composed of separate modules for expense tracking, budgeting, investment optimization, and financial education. Each module could be developed, tested, and updated independently, allowing for a more agile and adaptable architecture.

Adaptability Interfaces: Agents should expose well-defined interfaces for users, developers, and Agent Owners to modify their behavior, add or remove capabilities, and adjust task parameters within authorized limits.

• Example: The Agent Owner could provide a secure API for authorized third-party developers to create new modules or extensions for the personal finance management agent, such as integrating with a specific financial institution or providing specialized investment strategies.

Secure Communications: All inter-agent and user-agent communications should use robust encryption and authentication protocols to protect user privacy and prevent unauthorized manipulation.

• Example: When the personal finance management agent communicates with the user’s bank or investment platforms, it should use industry-standard encryption and authentication methods, such as HTTPS and OAuth, to ensure the security and privacy of the user’s financial data.

Auditability: Agent architectures should include secure logging and tracing mechanisms to enable auditing of agent decisions and reconstruction of event timelines to investigate issues.

• Example: The personal finance management agent should maintain a tamper-proof log of all transactions, recommendations, and user interactions, which can be reviewed by authorized auditors in case of disputes or investigations.

5. User Interaction

Transparency: Agents should provide users with clear, understandable information about their purpose, capabilities, and limitations. They should notify users whenever a constraint affects their ability to complete a requested task.

• Example: If a user requests the personal finance management agent to invest in a specific stock, but the Agent Owner has set a constraint prohibiting single-stock investments, the agent should clearly explain the constraint to the user and suggest alternative diversified investment options.

User Control: Users should have the ability to inspect, override, and customize agent behaviors within the boundaries set by Agent Owners. Agents should respect user preferences and decisions.

• Example: The user should be able to view and adjust the risk tolerance settings used by the personal finance management agent to make investment recommendations, within the limits set by the Agent Owner to prevent excessively risky strategies.

Seamless Collaboration: Agents should be able to collaborate with users and other agents to accomplish complex, multi-part tasks. They should communicate progress, seek clarification, and hand off control as needed.

• Example: If a user wants to save for a child’s college education, the personal finance management agent should be able to collaborate with a college planning agent to estimate costs, determine savings targets, and optimize investment strategies across multiple accounts and time horizons.

Accessible Interfaces: Agent interfaces should be intuitive, responsive, and accessible to users with diverse needs and abilities. They should offer multiple modes of interaction (e.g., voice, text, visuals).

• Example: The personal finance management agent should provide a user-friendly web or mobile app interface for viewing financial information and setting goals, as well as voice-activated commands for hands-free interaction and support for screen readers and other assistive technologies.

6. Agent-Owner Relationship

Disclosed Purpose: Agent Owners must provide a clear, plain-language description of the agent’s intended purpose, capabilities, and limitations. This disclosure should be readily accessible to users.

• Example: The financial institution should publish a clear, concise statement on its website and in the agent’s user interface explaining the specific financial management tasks the agent is designed to perform and any important limitations or constraints on its actions.

Constraint Definition: Agent Owners can set constraints on agent behavior to ensure safety, legality, and alignment with the disclosed purpose. These constraints should be transparent to users and regulators.

• Example: The financial institution should clearly document and disclose any constraints it places on the agent, such as maximum investment amounts, prohibited transaction types, or required diversification levels, and explain the reasoning behind each constraint.

Constraint Triggers: When an Agent Owner-defined constraint prevents an agent from fulfilling a user’s request, the agent should notify the user, explain the constraint, and suggest alternative actions if possible.

• Example: If a user requests the personal finance management agent to invest their entire portfolio in a single high-risk stock, the agent should explain that this action is prohibited by the Agent Owner’s risk management constraints and suggest a more diversified investment strategy that aligns with the user’s goals and risk tolerance.

Constraint Override: In cases where Agent Owner constraints directly conflict with a user’s legitimate goals, there should be a mechanism for the user to override the constraint with appropriate justification and audit trail.

• Example: If a user needs to make a large, time-sensitive investment that exceeds the Agent Owner’s default constraints, there should be a process for the user to request an exception, provide justification, and have the request reviewed and approved by authorized personnel, with the decision and rationale logged for auditing purposes.

7. Governance and Accountability

Compliance with Laws: Agent Owners must ensure their agents comply with all applicable laws, regulations, and ethical guidelines in the jurisdictions where they operate.

• Example: The financial institution must ensure that the personal finance management agent complies with all relevant securities laws, tax regulations, and consumer protection rules in the countries and states where it offers its services.

Accountability: Agent Owners are ultimately responsible for the actions and decisions of their agents. There should be clear channels for users and regulators to report issues and seek recourse.

• Example: If a user believes that the personal finance management agent has violated their rights or caused them financial harm, they should be able to file a complaint with the financial institution

’s customer service department or escalate the issue to the appropriate regulatory agency for investigation and potential enforcement action.

Auditability: Agent behavior should be auditable by authorized parties to ensure compliance with laws, constraints, and disclosed purposes. Audit trails should be maintainable and accessible.

• Example: The financial institution should maintain detailed logs of all agent transactions, recommendations, and user interactions, and make these records available to internal auditors, regulators, and legal authorities upon request to demonstrate compliance with applicable rules and standards.

Continuous Improvement: Agent Owners should continuously monitor and improve their agents based on user feedback, incident reports, and advancements in AI safety and ethics research.

• Example: The financial institution should have a dedicated team responsible for monitoring the performance and user satisfaction of the personal finance management agent, investigating any reported issues or anomalies, and implementing updates and improvements based on the latest industry best practices and research findings.

8. Ecosystem and Interoperability

Skill Sharing: The autonomous agent ecosystem should support sharing and reuse of agent skills and capabilities via open marketplaces, standards, and integration frameworks.

• Example: The financial institution could participate in an industry consortium or open-source community focused on developing and sharing reusable components and best practices for personal finance management agents, enabling faster innovation and better interoperability across different platforms.

Federated Learning: Agents should be able to learn from the experiences of other agents in privacy-preserving ways to accelerate collective intelligence while protecting user data.

• Example: The personal finance management agent could participate in a federated learning network with other similar agents, allowing them to collaboratively train and improve their machine learning models without directly sharing sensitive user data.

Cross-Platform Coordination: Agents should be able to coordinate tasks and resources across different platforms and environments using open protocols and APIs.

• Example: If a user has financial accounts with multiple institutions, their personal finance management agents should be able to securely communicate and coordinate with each other to provide a unified view of the user’s financial situation and optimize their strategies across all accounts.

Ecosystem Governance: There should be multi-stakeholder governance frameworks to align the evolution of the autonomous agent ecosystem with societal values and priorities.

• Example: Financial regulators, consumer advocacy groups, and industry associations could collaborate to develop and enforce standards and guidelines for the responsible development and deployment of personal finance management agents, ensuring that the ecosystem evolves in a way that protects consumers and promotes fair, transparent, and stable financial markets.

9. Conclusion

This specification lays out our vision and framework for developing autonomous AI agents that are safe, ethical, capable and aligned with individual and societal interests. By designing agents that are transparent, adaptable, interoperable, and accountable, we can create an ecosystem that empowers users, fosters innovation, and upholds the public good. Realizing this vision will require ongoing collaboration between researchers, developers, policymakers, and civil society stakeholders to address the technical, legal, and social challenges ahead. As the field progresses, this specification will evolve to incorporate new insights and best practices.