Guardrails

Guardrails in artificial intelligence refer to the safety measures, policies, and technical constraints designed to ensure AI systems behave responsibly and within defined ethical or operational boundaries. They can include content filters, access controls, human oversight mechanisms, and model alignment techniques that prevent harmful or unintended outputs. In large language models and generative AI, guardrails help maintain factual accuracy, prevent bias, and reduce the risk of misuse. Building effective guardrails is essential for balancing innovation with accountability, ensuring AI remains trustworthy and aligned with human values. As AI becomes more autonomous, these safeguards play a crucial role in maintaining transparency, fairness, and safety across applications.