This is how the synthetic knowledge crisis unfolds. Not through outright falsehoods, but through a gradual weakening of the criteria that distinguish knowing from appearing to know.
How do we identify the folks who are just faking it until the make it with synthetic knowledge.
No specialized AI detectors can detect AI writing with high accuracy and without the risk of false positives, especially after multiple rounds of prompting. Even watermarks won’t help much.People can’t detect AI writing well. Editors at top linguistics journals couldn’t. Teachers couldn’t (though they thought they could - the Illusion again). While simple AI writing might be detectable (“delve,” anyone?), there are plenty of ways to disguise “AI writing” styles through simples prompting. In fact, well-prompted AI writing is judged more human than human writing by readers.You can’t ask an AI to detect AI writing (even though people keep trying). When asked if something written by a human was written by an AI, GPT-4 gets it wrong 95% of the time.
AI detection cannot be completed by AI detectors, the human AI or other AI tools.
Attribution is a cornerstone of the postplagiarism framework. In the postplagiarism era, where the boundaries between human and AI-generated content blur and traditional definitions of authorship are challenged, the practice of acknowledging our intellectual influences becomes more vital, not less (Kumar, 2025)
Attribution over referencing
four categories of critical AI literacy
Functional literacy: How does AI work?
Ethical literacy: How do we navigate the ethical issues of AI?
Rhetorical literacy: How do we use natural and AI-generated language to achieve our goals?
Pedagogical literacy: How do we use AI to enhance teaching and learning?
AI-aware decisions require that the educator making the decisions has sufficient understanding of AI.
Encouraging AI literacy for educators not just students. Potential idea for a CFE Repository...