Mitigating Deepfake Risks

This unit examines how deepfakes exploit trust and the role of technology, corporations, and policy in both enabling and curbing their harm. Students will investigate the social, legal, and technical dimensions of deepfake threats and design practical prevention and response strategies to prepare businesses for emerging AI-enabled cybercrime.

Learning Objectives

• Analyze at least four ways deepfakes exploit human trust and cognitive bias in business and social settings, citing examples from case studies in the unit
• Evaluate the responsibilities and incentives of Big Tech, corporations, and regulators by producing a written critique with a minimum of three recommended policy or governance interventions
• Apply cybersecurity and risk-management principles to create a 5–8 page prevention and incident-response plan that incorporates detection, access controls, and a real-time ‘kill switch’ concept
• Demonstrate an ethical operational framework for organizations by presenting a 7–10 minute proposal that balances access, innovation, and verification procedures and includes measurable monitoring metrics