Over the past few months, we were frequently asked how companies can look inside the “black box” of AI. No matter which industry, companies want model transparency. If you are in a regulated industry, such as Pharma or Insurance, you perfectly understand the need for transparency: you need to report to the government agencies. But even if you are not regulated, transparency is important for several reasons.
The biggest reason we’ve heard is that achieving peak accuracy is not enough. The models still need to be adopted internally, and stakeholders needed more to be convinced. While everyone agrees that AI is great at making very accurate predictions, the decision makers were not willing to make a confident decision without answers to questions such as:
- How is it making a prediction?
- What variables is it choosing to make more accurate predictions? And why?
People need to understand “Why” something is better and gain confidence in “How” it works. If you don’t have a data scientist, you might be lost. Our latest release introduces tools to help understand more about the final model, why it’s better, and assist you in convincing stakeholders. If you want to learn more, contact us now!