Human judgments

The critical process of human-in-the-loop validation: it provides essential, contextual, and ethical input to train, refine, and verify machine learning models.

Human Judgments (HJ) is the indispensable component in AI/ML workflows, leveraging human cognitive abilities for tasks machines cannot reliably handle. It’s used primarily for data labeling (annotating millions of examples) and quality assurance (validating AI outputs): for instance, 55% of AI-generated content still requires human review for accuracy and nuance. HJ is crucial for ethical and contextual decision-making, such as determining acceptable outcomes in autonomous vehicle dilemmas (e.g., the Moral Machine project) or mitigating model biases in justice systems, where models may otherwise suggest harsher judgments than a human would. This process ensures model efficacy and builds trust in AI systems.

https://moralmachine.net