Demonstrates how enhancing computer literacy can bridge the prompt gap in the AI era, impacting economic systems.
Version 2 - May 11, 2026: I added subsections 3.5, 3.6, 4.5, and Appendix D (for creating prompts for Anthropic Claude 4.7 using XML tags), along with the citations supporting these new sections and a citation for Dr. Stuart Russell's academic website. I also made some minor formatting changes, and the Declaration on the Use of Artificial Intelligence was replaced with a shorter version. In this paper I argue that true computer literacy in the AI era is not coding but mastery of logical, coherent, iterative, and truth-seeking interaction with large language models and their successors. Without mass AI literacy, humanity delays the Tech Stack convergence (AI/AGI/ASI + Robotics + Fusion/Dyson swarms + Reusable Launch Vehicles) that dismantles scarcity-based governance and enables the post-scarcity Abundance Economy. Using the viral Woke Turing Test as a primary test case, I demonstrate through a five-platform 2026 experiment that accusations of AI “wokeness” stem almost entirely from poor prompting (GIGO [Garbage In, Garbage Out] amplified by transformer architecture), and that prompts that appear to elicit "woke" responses are quarantined by the AI system’s first level alignment training and are never allowed to engage the AI system’s second level reasoning capacities. I propose three scalable programs to achieve global functional literacy in 2-3 years and provide several self-study exercises and a complete self-study educational module for anyone who wishes to improve their prompt engineering skills. Version 2 includes three sections on prompt engineering for Anthropic Claude 4.7 using XML tags and an extended analogy between the four frontier AI models and legacy systems like IBM's S/390.
No takes yet. Share an insight, caveat, or question.
Lon Douglas Waford (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: