AI Deception: Risks and Tactics

This unit examines how malicious actors and AI systems create, amplify, and exploit deceptive content online, including hallucinations, bias, disinformation, deepfakes, and low‑tech social engineering. Students study attacker mindsets and technical tactics to prepare for defensive detection and mitigation strategies in subsequent units.

Learning Objectives

• Analyze common attacker mindsets and problem‑solving approaches used in social engineering and cyber deception by dissecting case studies and simulated campaigns
• Evaluate AI‑specific risks — including hallucinations, systemic bias, and model corruption — by assessing their causes, likely impacts, and real‑world examples
• Apply evidence‑based detection techniques to identify AI‑generated disinformation and deepfakes across text, image, audio, and mixed media formats
• Demonstrate the ability to map deception tactics (high‑tech and low‑tech), prioritize associated harms, and propose at least two mitigation or policy recommendations for each identified threat