Why is Explainability Critical?

Part 3: What Responsible AI Should Look Like

The eleventh question in our 5-part series on AI's impact on networks is a thought-provoking one. Network automation vendors are increasingly expected to clearly explain how their AI generates insights. It's crucial that these AI actions are safe, responsible, and fully aligned with your organization's goals for success.

To establish trust, engineers must understand the rationale behind AI decisions. I fully recognize and support the urgent need for transparency in this area.

Watch as I answer this important question in the video below:

For more information on using AI for network automation, visit our BackBox Platform Page. Ready to get started? Request a demoto see our solution in action.

Be sure to check out other blogs and videos in this series, including:

• What does AI as an advisor look like in practice?
• What defines responsible AI in network automation?
• How do you balance automation with human expertise?