RAIDS: Rethinking Data Systems as Responsible Intelligent Infrastructure
For data system designers and users, this work provides a conceptual framework to integrate responsibility (support, constraints, actionability) into data-to-decision pipelines, but remains a vision without implementation or evaluation.
The paper proposes RAIDS, a vision for data systems that treat responsibility as execution semantics rather than post-hoc metadata, introducing operator-level responsibility contracts and responsibility preservation as a systems objective. It outlines a research agenda for building such systems.
Data systems are evolving from information infrastructure into decision infrastructure. Yet responsibility mechanisms have not kept pace: an output can be accurate or efficient while still lacking sufficient support, satisfied constraints, and actionability for responsible use. We propose RAIDS (Responsible and Intelligent Data System), a vision for data systems as responsible intelligent infrastructure. RAIDS treats responsibility not as post-hoc metadata, but as execution semantics for holistic data-to-decision and data mining pipelines. Its core abstraction is an operator-level responsibility contract: each operator exposes an output together with support, constraint, and actionability state under an explicit responsibility context, and these contracts compose across pipelines. These states capture whether an output is grounded, whether execution satisfies relevant limits, and which action modes are permissible. We introduce responsibility preservation as the organizing systems objective: responsibility state should remain sufficient as execution proceeds, or the system should repair, replan, escalate, refuse, or otherwise change course. We outline a BlueSky research agenda for RAIDS, spanning responsibility-preserving execution, responsibility-aware optimization, provenance, oversight, and evaluation.