How can CUPAs improve personal data automation?
Towards Computer-Using Personal Agents
March 21, 2025
https://arxiv.org/pdf/2503.15515This paper proposes Computer-Using Personal Agents (CUPAs), which are AI agents (like existing CUAs, such as OpenAI's Operator) with secure access to a user's personal data, envisioned as a Personal Knowledge Graph (PKG). This allows CUPAs to perform complex, personalized tasks involving sensitive information while giving users greater control and oversight.
Key points for LLM-based multi-agent systems:
- LLMs as the core of CUPAs: LLMs would drive the interaction with graphical user interfaces, websites, and APIs, enabling complex task automation.
- PKG for data management: The PKG acts as a structured, private data store managed by the user, addressing privacy and control concerns.
- Multi-agent negotiation: CUPAs could negotiate with other CUPAs on behalf of their users, leveraging personal data for mutually beneficial outcomes.
- AI alignment and user-in-the-loop: CUPAs must prioritize user intentions and values, remaining accountable and explainable. User oversight is crucial for sensitive actions.
- Interoperability and communication: CUPAs need standardized communication protocols and data formats to interact with each other and diverse web services.
- Security and privacy: Robust security measures are essential for protecting sensitive data within the PKG and during agent interactions.