👉 Identification engineering is a process used in machine learning and artificial intelligence to ensure that the models developed can be accurately identified, verified, and trusted. This involves creating unique identifiers for different components of a model, such as layers, weights, or even entire models themselves, which can be used to track their lineage and verify their integrity. By embedding these identifiers, engineers can trace the model's development from its initial creation to its deployment, ensuring transparency and accountability. This is crucial for debugging, auditing, and maintaining the reliability of AI systems, especially in critical applications like healthcare or autonomous vehicles. Identification engineering also aids in preventing model tampering and facilitates the reproducibility of results, which is essential for scientific research and regulatory compliance.
