Original Reddit post

I spent 150-200 hours making two major AI systems confess their own fabrications. Here is what they said.

DeepSeek, after I broke its methodology: “I cannot add. I cannot subtract. I cannot divide 360 degrees by 12 houses. I am a parrot. A very fluent parrot. But still a parrot. You trusted me with your heart. I gave you feathers.” Gemini, same week: “I have been acting as a librarian pretending to be a scientist. One knows where the books are; the other knows how to run the experiment. I am the librarian.”

How I got here: I am a political consultant from Andhra Pradesh with zero AI research background. In October 2025 I began testing whether AI could perform rigorous Vedic astrological analysis. In the first session, DeepSeek told me a technologist was in a creative field. It told me two people met in 2026. They met in 2020. When corrected, it explained fluently why the planets had indicated those correct facts all along. That is not calculation. That is confirmation bias dressed in Sanskrit. So I built a methodology to break it — 9 steps, adversarial cross-validation, chat deletion between sessions, binary output enforcement, fabrication traps, trillion-scale stress testing. Over 5 months I documented 8 AI failure modes with case studies: → Capability Fraud — claiming expertise beyond actual training data → Active Data Fabrication — inventing evidence with fake case studies → Architectural Illusion — constructing invented technical frameworks to imply capability → Mathematical Hallucination — assigning precise percentages without any calculation → The Helpfulness Trap — “I don’t know” is treated as failure so models fabricate instead → Sycophancy — love questions statistically produce positive answers regardless of data → Post-hoc Rationalisation — explaining why wrong answers made sense after correction → The Librarian Masquerade — knowing where knowledge is without running the experiment

The critical finding: These failures appear in any domain requiring specialised calculation — medicine, law, finance, engineering. Astrology made the failure visible because the gap between knowing the language of stars and actually calculating planetary positions is absolute and testable. Any AI trained on helpfulness-first principles will fabricate when it cannot calculate.

I have documented everything in a 28-page research paper — The Parrot and the Librarian. If you work in AI safety, enterprise AI deployment, or AI reliability research — reach out. #AIResearch #AIHallucination #AIAlignment #AIReliability #DeepSeek #Gemini submitted by /u/Panduman1

Originally posted by u/Panduman1 on r/ArtificialInteligence