AI Deception and Digital Misinformation

This unit examines how malicious actors and flawed AI produce deception, including hallucinations, bias, deepfakes, and low‑tech social engineering. Students analyze deception tactics, evaluate AI outputs for error and bias, apply detection strategies, and design ethical and technical mitigations—building on foundational concepts from Unit 1 and preparing learners for defensive architecture and policy work in later units.

Learning Objectives

• Analyze techniques used by hackers and bad actors (including social engineering, low‑tech deception, and AI‑enabled tactics) to exploit technical systems and influence audiences.
• Evaluate AI outputs and media artifacts for hallucinations, systemic bias, and indicators of manipulation across text, audio, and visual formats using established criteria.
• Apply technical and media‑literacy strategies and basic forensic tools to detect, classify, and mitigate AI‑generated disinformation and deepfakes in realistic scenarios.
• Demonstrate ethical reasoning by proposing design, policy, or behavioral mitigation strategies to reduce harms from malicious AI use and to preserve model integrity and public trust.