As organizations harness the power of AI to fortify their cybersecurity posture, a pivotal challenge emerges: striking the delicate balance between robust threat prevention and the protection of individual and organizational privacy.

This session will address the need to safeguard data privacy, along with the governance and compliance considerations necessitated by the proliferation of AI utilization. Beyond simply identifying challenges, this session will serve as a practical guide, offering actionable strategies for the ethical implementation of AI in cybersecurity operations.

Tailored for CISOs, IT professionals, data scientists, and all stakeholders intrigued by the intricate interplay of AI, ethics, and security, the discussion aims to shape a responsible and privacy-conscious approach to AI deployment. 

Key discussion points:

• Privacy-preserving AI techniques: Explore cutting-edge techniques and technologies designed to enable the use of AI without compromising individual privacy, including federated learning, homomorphic encryption, and other approaches that allow AI models to be trained without accessing raw, sensitive data.
• Consent and data governance: Examine the role of informed consent in the context of AI applications, best practices for transparently obtaining user consent, and strategies for effective data governance in compliance with evolving privacy regulations.
• Accountability and transparency in AI practices: Discuss the importance of implementing accountability measures and ensuring transparency in AI operations to build trust and enable verification. Examine frameworks for auditing AI systems, the role of explainable AI in understanding decision-making processes, and policies for addressing biases and errors that impact privacy and data security.