Humanagent

Humanagent refers to the practice or role in which humans act as agents within automated systems, providing direction, oversight, and judgment to artificial agents. In this framing, a human agent defines goals, monitors outputs, and can intervene at critical points, while AI or software agents handle data processing, planning, and execution. The term is not a single standardized concept, and its precise meaning can vary by context, but it commonly denotes human-directed collaboration with autonomous or semi-autonomous systems.

Contexts and implementations typically involve mixed-initiative or human-in-the-loop workflows. Examples include customer-support platforms where a human supervisor can take over conversations, content moderation pipelines with human review for ambiguous cases, data-labeling processes guided by human feedback, and robotics or industrial automation where a human can intervene to adjust behavior or correct course. Related notions include human-in-the-loop AI, where humans review model outputs; reinforcement learning from human feedback (RLHF), which uses human judgments to shape models; and mixed-initiative systems, in which humans and machines alternate control.

Advantages of the humanagent arrangement include improved decision quality, safety, and ethical alignment, as well as the ability to handle edge cases beyond the data available to automated systems. It can also enhance accountability by preserving human oversight in critical tasks. Challenges include potential latency and higher costs, the risk of fatigue or inconsistent input from human agents, and the need for clear decision rights and well-designed interfaces. The term remains a flexible descriptor used across domains rather than a single standardized framework.