Principles

Mission

These Principles state the mission, principles, scope, and limits of Robot Labor.

Robot Labor exists to make machine participation in organized work easier to identify, explain, govern, and review as it becomes more common across contemporary work systems.

Robot Labor develops language, principles, and frameworks for describing what a machine system does within work, where human and organizational responsibility remains, what should be disclosed, and how deployments should be reviewed over time.

Core principles

1. Legibility

The role of a machine system within work should be identifiable: what it does, where it enters the workflow, what remains human, and where its operational limits lie. Legibility is about making the structure of participation visible rather than hiding it behind generic technology language.

2. Accountability

Responsibility for machine-mediated work should remain traceable. Institutions should be able to explain who authorizes deployment, where oversight lies, how escalation and decision paths are structured, and who remains answerable for material effects.

3. Proportionate disclosure

Relevant people should be told when machine participation materially affects a service, work process, decision path, or allocation of responsibility. The detail disclosed should be proportionate to the significance of that participation and should not exaggerate or conceal the system’s role.

4. Stewardship

Organizations introducing machine work should maintain responsibility across the system lifecycle: selection, deployment, monitoring, maintenance, change, review, and retirement. Stewardship treats integration as an ongoing governance task rather than a one-time technical installation.

5. Public intelligibility

Public explanations should translate the system’s role, limits, oversight, and labor consequences into language non-specialists can understand, without unnecessary technical opacity, anthropomorphism, or exaggeration.

Scope

• Embodied robotic systems performing identifiable operational work inside organized workflows
• Digital or AI agents only where they carry out a recurring, identifiable operational role inside organized work
• Service, coordination, decision-support, or workflow systems where machine participation materially changes tasks, supervision, responsibility, or value
• Public-facing forms of machine work whose role, oversight, or limits require clearer explanation

Limits

• No equivalence between machine systems and human workers, rights-holders, or political subjects
• No extension of the term to general-purpose AI use without an identifiable role in an organized work system
• No general technology commentary mission outside the labor-system research scope
• No speculative scenarios without a clear connection to institutional or operational questions about work

From principle to framework

These Principles set Robot Labor’s direction. Responsibility & Operations develops that direction through a responsibility chain, operating requirements, the shared Core Record, operational extensions, and review. Documentation & Classification uses that Core Record with multidimensional classification and public-explanation fields.