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References and Selected Resources
         I. Scientific and Professional References
         [1]  National  Institute  of  Standards  and  Technology.  (2023).  Artificial  Intelligence  Risk

         Management Framework (AI RMF 1.0). NIST AI 100-1
         [2]  National  Institute  of  Standards  and  Technology.  (2024).  Artificial  Intelligence  Risk
         Management Framework: Generative Artificial Intelligence Profile. NIST AI 600-1

         [3] National Institute of Standards and Technology. NIST Privacy Framework 1.0, and Privacy
         Framework 1.1 Initial Public Draft
         [4]  National  Institute  of  Standards  and  Technology.  (2010).  Guide  to  Protecting  the

         Confidentiality of Personally Identifiable Information (PII). SP 800-122
         [5] OWASP Gen AI Security Project. (2025). OWASP Top 10 for LLM Applications

         [6] OWASP Gen AI Security Project. LLM risk archive and current LLM risk resources
         [7] UNESCO. (2023). Guidance for Generative AI in Education and Research
         [8] Caulfield, M. SIFT: The Four Moves
         [9] Wineburg, S., & McGrew, S. (2017/2019). Lateral Reading and the Nature of Expertise.

         Stanford History Education Group; Teachers College Record
         [10]  National  Institute  of  Standards  and  Technology.  (2022).  Towards  a  Standard  for

         Identifying and Managing Bias in Artificial Intelligence. NIST SP 1270
         [11] Federal Trade Commission. (2024). Fighting Back Against Harmful Voice Cloning
         [12]  Federal  Trade  Commission.  (2023).  Scammers  Use  AI  to  Enhance  Their  Family

         Emergency Schemes
         [13]  Coalition  for  Content  Provenance  and  Authenticity.  C2PA  and  Content  Credentials
         Explainer

         [14] World Health Organization. (2021). Ethics and Governance of Artificial Intelligence for
         Health
         [15] World Health Organization. (2024). Ethics and Governance of Artificial Intelligence for

         Health: Guidance on Large Multi-Modal Models
         [16] National Institute of Standards and Technology. (2021). Four Principles of Explainable
         Artificial Intelligence. NISTIR 8312

         [17] Digital Inquiry Group, Stanford. Civic Online Reasoning and lateral reading resources
         [18] The Guardian. (2024). UK engineering firm Arup falls victim to deepfake scam
         [19] World Economic Forum. (2025). Cybercrime: lessons learned from a 25 million dollar

         deepfake attack
         [20] OWASP Gen AI Security Project. (2026). OWASP Top 10 for Agentic Applications

         [21] Coalition for Content Provenance and Authenticity. (2026). C2PA Technical Specification
         2.4
         II. Educational Video Resources

         [22] National Institute of Standards and Technology. (2023). Introduction to the NIST AI Risk
         Management         Framework        (AI    RMF       1.0):    An     Explainer     Video      [Video].




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