Human-in-the-Loop refers to AI systems that include human feedback or intervention as part of their operation. In these systems, humans may provide guidance, correct errors, or make final decisions to improve the accuracy and reliability of AI. This approach combines the strengths of both humans and machines, ensuring that complex or high-stakes tasks benefit from human judgment and oversight.
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While visualizations can help developers better design, train, and understand their models, new research shows gaps between ambitions and evidence.
While visualizations can help developers better design, train, and understand their models, new research shows gaps between ambitions and evidence.


Stanford HAI’s upcoming conference challenges attendees to rethink AI systems with a “human in the loop” and consider a future where people remain at the center of decision making.
Stanford HAI’s upcoming conference challenges attendees to rethink AI systems with a “human in the loop” and consider a future where people remain at the center of decision making.


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Humans are not simply “in-the-loop.” Humans are in charge; AI is “in-the-loop."
Humans are not simply “in-the-loop.” Humans are in charge; AI is “in-the-loop."