What are the Biggest Risks of AI in Critical Infrastructure?

Part 2: The Promise vs the Risk

In Part 1 of this 5-part series on AI's impact on networks, BackBox experts addressed common questions to help set the stage for AI adoption. In Part 2, we examine the promise versus the risk of AI in networks.

To kick off Part 2, BackBox CEO Rekha Shenoy discusses one of the biggest risks of using AI in critical infrastructure and security - hallucinations. When AI provides an answer that is inaccurate and mechanisms are not in place to mitigate this risk, the implications can impact not just an enterprise but critical infrastructure and, in turn, nations. Unfixed errors can spread over time.

For more details, watch the video below:

For more details 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:

• Why are hallucinations and bias especially dangerous in networks?
• Why does transparency matter so much?
• What should organizations ask vendors about AI data sources?