📮 Maildrop 07.01.25: Bias in AI: Ensuring fairness and equity in threat intelligence
The things to know about AI and cyber threats | Tools for the next generation of enterprises in the AI era
📮 Maildrop 07.01.25: Bias in AI: Ensuring fairness and equity in threat intelligence
Imagine a world where cyberattacks are not just prevented but predicted and neutralized before they occur.
This is the promise of defining how threats evolve using large language models (LLMs) to transform the cybersecurity landscape and improve online safety.
➤ More on this is discussed in the introduction of this new series.
"We all know AI can inherit biases from its training data."
This simple truth carries profound implications for using AI in threat intelligence. In a world where split-second decisions can have lasting consequences, the potential for AI to unfairly target individuals or groups based on biased data is a significant concern.
Imagine an AI system that is more likely to flag emails from certain countries as suspicious simply because of historical biases in the data it was trained on.
Such discriminatory outcomes are ethically unacceptable and can lead to missed threats and damaged reputations.
What’s important to know?
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