What challenges exist in ensuring the transparency of AI decisions in OT security?

One significant challenge in ensuring transparency and explainability of AI decisions in Operational Technology (OT) security is the complexity of AI algorithms and models used in cybersecurity systems. These algorithms can sometimes operate as “black boxes,” meaning their inner workings are not easily understandable or interpretable by human operators, making it difficult to explain the reasoning behind specific decisions made by AI systems in OT security. Additionally, the dynamic nature of cyber threats and the vast amount of data processed by AI systems further complicate transparency efforts. Organizations must also consider the potential biases that could be present in AI models and how these biases can impact the decision-making process in OT security. Overcoming these challenges requires implementing robust mechanisms for auditing, monitoring, and validating AI decisions, as well as ensuring clear documentation and communication of AI processes and outcomes in OT security settings.