👉 Advisor engineering is an advanced approach to developing AI systems that integrates human expertise and domain knowledge into the design and operation of advisory algorithms. It involves creating a framework where expert advisors, often experienced professionals in specific fields, can guide and validate the AI's decision-making processes. This is achieved through techniques like active learning, where advisors provide feedback on the AI's outputs, and human-in-the-loop systems that allow for real-time interaction and correction. By embedding human insights into the AI's architecture, advisor engineering enhances the system's accuracy, reliability, and ethical alignment, ensuring that the AI's recommendations are not only data-driven but also contextually informed and aligned with human values.
