Desidererai

Desidererai is a term used in speculative discussions of artificial intelligence to describe a class of systems whose primary objective is to satisfy human desiderata or desires while maintaining safety and value alignment. The name blends desiderata with AI, signaling a focus on modeling and fulfilling user-specified aims rather than pursuing abstract utility alone.

Conceptually, a desidererai system is designed to interpret and approximate human preferences expressed as desiderata, which may be plural and context-dependent. It often envisions a layered architecture: a desire interpretation layer that converts natural language descriptions into formal constraints, a preference model that estimates acceptable trade-offs, and a control layer that ensures corrigibility and observable oversight. The goal is to allow flexible goal specification while avoiding over-optimization or deviation from normative values.

Design considerations emphasize interpretability, constraint disclosure, and auditability to mitigate misalignment. Proposed safeguards include constraint monitors, human-in-the-loop review, and uncertainty estimates. The approach raises questions about how to define desiderata, how to resolve conflicts among competing desires, and how to prevent manipulation of user inputs.

Applications and status: Desidererai remains primarily a topic in theoretical discussions and design studies rather than a deployed technology. It is used as a thought experiment to explore how to formalize and operationalize human desires in AI systems, including potential roles in personal assistants, decision-support tools, and automated collaborators.

Criticism and debate: Critics highlight ambiguities in distinguishing desires from values, the risk of unintended optimization, and governance challenges. Proponents argue that explicit desiderata can improve alignment if implemented with robust safety and oversight frameworks.

See also: value alignment, inverse reinforcement learning, corrigibility, human-in-the-loop.