Explainable Artificial Intelligence is key for any successful implementation at scale.
Here are some of the aspects of Explainable AI :
Systems provide the evidence or reason(s) for all outputs.
Systems provide explanations that are understandable to individual users.
The explanation correctly reflects the system’s process for generating the output.
The system only operates under conditions for which it was designed or when the system reaches sufficient confidence in its output.
IP analysis has always been considered as a great use case for AI systems because of the multiple factors such as rich large text data and several interconnects.
However, for large scale adoption in Industry the following are needed:
- Lack of Bias