AI Safety & Deepfake Awareness 9 Sections48 Lessons9 QuizzesLifetime
- 9 Sections
- 48 Lessons
- Lifetime
- AI, Synthetic Media, and Human Responsibility7 Items
Outcome: Explain generative AI, synthetic media, deepfakes, hallucinations, and the continuing responsibility of human users.
Case: A learner treats a fluent AI answer and a realistic video as automatically reliable because both look polished and confident.
Tools: AI capability map, Human-oversight checklist, Risk-and-benefit sorting activity
- How Deepfakes Work and Why Visual Tells Are Not Proof7 Items
Outcome: Describe at awareness level how synthetic text, images, audio, and video are produced and why appearance-based detection is unreliable.
Case: A viewer spots unusual blinking in a compressed video, declares it fake, and ignores stronger evidence about the original source and publication history.
Tools: Synthetic-media pipeline map, Signal-versus-proof worksheet, Compression-effects comparison
- 2.1Understand the media-generation pipeline
- 2.2Recognize face and identity manipulation
- 2.3Understand synthetic and cloned audio
- 2.4Understand generated images and video
- 2.5Separate detector score from conclusion
- 2.6Account for context and chain of custody
- 2.7Module 2 Assessment — How Deepfakes Work and Why Visual Tells Are Not Proof5 Minutes5 Questions
- Verify Images, Audio, Video, and Claims7 Items
Outcome: Apply a Pause-Inspect-Verify-Decide-Document method using source, context, corroboration, provenance, and official-channel checks.
Case: A dramatic clip uses a genuine broadcaster logo but appears only on an anonymous account, with no matching report on the broadcaster's official channels.
Tools: PIVDD verification lab, Source-and-context checklist, Provenance interpretation cards
- 3.1Start with the exact claim
- 3.2Check source and publication path
- 3.3Search for prior and parallel evidence
- 3.4Verify through an official channel
- 3.5Use provenance and Content Credentials
- 3.6Document a proportionate conclusion
- 3.7Module 3 Assessment — Verify Images, Audio, Video, and Claims5 Minutes5 Questions
- Deepfake Impersonation, Fraud, and Social Engineering7 Items
Outcome: Recognize voice-cloning, executive, family-emergency, romance, recruitment, investment, and identity-impersonation attacks.
Case: A finance employee joins a video call that appears to include senior leaders and is pressured to bypass the approved payment-change process.
Tools: Impersonation pattern cards, Callback protocol drill, High-risk request decision tree
- 4.1Recognize family-emergency voice scams
- 4.2Recognize executive and authority impersonation
- 4.3Recognize romance, recruitment, and investment personas
- 4.4Protect account recovery and authentication
- 4.5Use codewords and approved callbacks carefully
- 4.6Respond to an active impersonation attempt
- 4.7Module 4 Assessment — Deepfake Impersonation, Fraud, and Social Engineering5 Minutes5 Questions
- Misinformation, Manipulation, and Responsible Sharing7 Items
Outcome: Resist misinformation, emotional amplification, and unsafe sharing while communicating uncertainty and corrections responsibly.
Case: A synthetic political clip spreads through community groups with captions that become more certain and inflammatory at every repost.
Tools: Sharing-friction checklist, Claim-corroboration exercise, Correction-message practice
- 5.1Understand misinformation and disinformation
- 5.2Recognize emotional amplification
- 5.3Evaluate corroboration quality
- 5.4Share uncertainty responsibly
- 5.5Correct without increasing harm
- 5.6Prepare communities and organizations
- 5.7Module 5 Assessment — Misinformation, Manipulation, and Responsible Sharing5 Minutes5 Questions
- Privacy, Consent, Dignity, and Victim Protection7 Items
Outcome: Protect privacy, consent, dignity, identity assets, children, and victims of non-consensual or abusive synthetic media.
Case: A class group creates a humiliating synthetic image of a student, then claims it is harmless because everyone knows it is fake.
Tools: Consent decision guide, Victim-support script, Privacy and exposure audit
- 6.1Treat identity and likeness as sensitive
- 6.2Understand meaningful consent
- 6.3Recognize non-consensual intimate imagery
- 6.4Protect children and students
- 6.5Support victims without blame
- 6.6Reduce future exposure
- 6.7Module 6 Assessment — Privacy, Consent, Dignity, and Victim Protection5 Minutes5 Questions
- Safe and Responsible AI Use at School, Work, and Home7 Items
Outcome: Use AI tools more safely at school, work, and home through data minimization, output verification, disclosure, and human review.
Case: An employee pastes a confidential complaint into a public AI tool, accepts the summary without checking, and sends it as a disciplinary record.
Tools: AI-use traffic light, Prompt data-minimization lab, Output verification worksheet
- Respond, Report, Recover, and Build Resilience7 Items
Outcome: Contain, preserve, report, escalate, recover, and support affected people during a deepfake or AI-enabled incident in India.
Case: A cloned voice triggers a payment, a synthetic intimate image begins spreading, and fake posts from a compromised account target the victim's contacts.
Tools: First-30-minutes response card, India reporting decision tree, Capstone incident record
- Final Examination1 ItemFinal assessment for AI Safety & Deepfake Awareness. Passing score: 70%.
