Intentsharing

Intentsharing is the practice of exchanging user intent signals between software components, services, or agents to coordinate actions and improve understanding in interactive systems. It involves sharing inferences about a user's goals, commands, or desired outcomes—derived from input, context, and behavior—typically subject to user consent and privacy policies.

In dialogue systems and multi-portal assistants, intentsharing enables continuity across domains and devices. For example, a customer-service chatbot could pass an unresolved user goal to a related service desk, or a smart-home assistant could align commands across lighting, climate, and security devices, reducing repetitive clarification.

Implementation approaches include establishing explicit intent contracts or schemas, using publish/subscribe message buses, and employing federated or cross-domain learning to align models without exposing raw data. Access control, identity management, and policy governance are central to safe sharing, as is consent management.

Key challenges are privacy and security risks, data minimization, and the possibility of misinterpreting or leaking intents. Interoperability requires standardized schemas and robust mapping between different representations of intent, as well as versioning and backward compatibility.

Applications span cross-platform customer support, enterprise workflow orchestration, and interconnected consumer devices. Research areas include privacy-preserving intent sharing, explainability of shared intents, and auditing mechanisms to verify how intents influence actions.

See also: natural language understanding, dialogue management, federated learning, privacy-preserving machine learning, data governance.