Why are Hallucinations and Bias Especially Dangerous in Networks?

Part 2: The Promise vs the Risk

This is the second installment in Part 2 of our 5-part series, where BackBox CEO Rekha Shenoy discusses key questions about the promise versus the risk of AI in networks.

Here, we explore why AI hallucinations, bias, and data quality issues are especially serious in network automation. In network infrastructure, errors or unexpected behaviors can lead to outages or cause security exposures. It's crucial to understand the use case for AI in the network as well as the organization's level of fault tolerance to weigh the risk against your capacity to actively manage and mitigate it.

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:

• What are the biggest risks of AI in critical infrastructure?
• Why does transparency matter so much?
• What should organizations ask vendors about AI data sources?