As AI becomes deeply integrated into cybersecurity operations, it brings significant ethical challenges, particularly concerning fairness, transparency and accountability.

Bias in AI algorithms can lead to discriminatory outcomes, while the opaque “black box” nature of many AI systems complicates these issues, making it difficult to understand how decisions are made, which can erode trust and hinder accountability. This session will explore the critical ethical considerations of deploying AI in cybersecurity and provide strategies to develop and implement AI systems that are fair and trustworthy. 

Key takeaways include: 

• Identifying and mitigating bias: Recognize how bias can infiltrate AI systems, and learn practical methods to identify and mitigate these biases. 
• Enhancing transparency: Understand the importance of transparency in AI models and how to implement practices that make AI decision-making processes more interpretable and accountable. 
• Balancing privacy and security: Explore the ethical balance between robust cybersecurity measures and protecting individual privacy.