Intrusion Detection Systems
Ethics & Safety
The degree to which an AI system's decisions can be understood and traced by humans.
Detailed Explanation
Interpretability in AI refers to how transparently and understandably a system’s decision-making process can be explained to humans. It ensures that users and developers can trace the reasoning behind outputs, fostering trust, accountability, and safety. High interpretability helps identify biases and errors, making AI systems more reliable and aligned with ethical standards.
Use Cases
- •Use case: Enhancing medical AI diagnostics to enable doctors to understand decision rationale, ensuring greater trust and safety in patient treatment.
Related Terms
Other terms in the Ethics & Safety category