Human Intervention
Human intervention refers to the process where human oversight, decision-making, or action is required in automated or AI-driven systems to handle exceptions, ensure quality, or manage complex scenarios. It involves integrating human judgment into workflows to complement technology, particularly in areas where automation falls short or ethical considerations are critical. This methodology is commonly applied in machine learning model validation, content moderation, customer support escalation, and regulatory compliance checks.
Developers should learn about human intervention to design robust systems that balance automation with human oversight, especially in high-stakes applications like healthcare diagnostics, financial fraud detection, or autonomous vehicles where errors can have severe consequences. It is crucial for implementing fallback mechanisms, improving AI model accuracy through human feedback loops, and ensuring ethical AI deployment by addressing biases or ambiguous cases that algorithms cannot resolve autonomously.