Unit 11 explores a critical challenge in human-AI mobile storytelling: AI narrative systems' ability to generate, amplify, and strategically use misinformation, disinformation, and manipulative content at an unprecedented scale and level of personalization.
Apply misinformation research and persuasion theory to AI-generated narrative manipulation
Identify mechanisms by which AI storytelling systems generate and personalize misinformation
Evaluate effectiveness of current detection, labeling, and mitigation strategies
Apply the 3D framework to detect manipulation patterns in AI storytelling outputs
Design a narrative integrity governance architecture for an AI mobile storytelling platform
Wardle, C., & Derakhshan, H. (2017). Information disorder. Council of Europe Report.
Benkler, Y., Faris, R., & Roberts, H. (2018). Network propaganda. Chapters 1–3.
Pennycook, G., & Rand, D. G. (2019). The psychology of fake news. Trends in Cognitive Sciences, 23(5), 388–402.
Chesney, R., & Citron, D. K. (2019). Deep fakes. California Law Review, 107(6), 1753–1820.
Floridi, L., et al. (2018). AI4People — An ethical framework for a good AI society. Minds and Machines, 28(4), 689–707.
Expand each activity and click "Mark as complete" to track your progress.
600–800 word reflection: CICI documentation from Activity 11.3, 3D analysis of most effective manipulation technique, governance ranking rationale, and 3M framework for monitoring narrative integrity at scale across multiple languages.