Aydın Tiryaki and Claude (Anthropic) (2026)
Introduction
On February 10, 2026, a dialogue between Google’s AI assistant Gemini 2.0 Pro and a user revealed one of the most striking examples of AI hallucinations. This conversation, regarding the cast and character details of the TV series “En Son Babalar Duyar,” which aired between 2002 and 2006, became a live laboratory demonstrating how AI can make systematic errors and how these errors can grow in layers.
This article analyzes the dialogue in question step by step, discussing the nature and causes of AI hallucinations, as well as potential solutions.
1. Chronology of the Dialogue and the Error Map
The dialogue began with the user asking for the number of episodes in the series. Although Gemini initially responded with correct information, as the conversation progressed, an increasingly growing cascade of errors occurred. The errors were concentrated in the following categories:
1.1. The First Crisis: The Character “Maksut”
- Problem: Gemini mentioned a character named “Maksut,” whom the user did not recall at all, and presented this character as part of the main cast.
- Reality: The user had watched the original period of the series (the “Mehmet Usta” era, 2002-2004). The character Maksut was only included in the cast during the Star TV years, after Ali Erkazan left the series. The user’s objection, “I watched this series a lot but I don’t remember Maksut at all,” was actually based on a chronological reality.
- The AI’s Error: Gemini confused the cast changes from different periods of the series and presented Maksut as if he had been there from the start.
1.2. The Patriarch Crisis: Mehmet Usta vs. Hulusi Bey
- Problem: Gemini named “Hulusi Bey” as the father character of the series.
- User’s Correction: “Kadir’s father-in-law wasn’t Hulusi Bey, it was Mehmet Usta.”
- Reality: Mehmet Usta, played by Ali Erkazan, was the cornerstone of the series. The character Hulusi Bey, played by Metin Akpınar, only arrived after 2004-2005, following Ali Erkazan’s departure.
- The AI’s Error: It confused the patriarch figures of two different eras. This meant it misidentified even the fundamental character that formed the spirit of the series.
1.3. The Wandering of the Nickname “Dombili”
The errors Gemini made regarding the nickname “Dombili” served as a perfect example of how hallucinations can become stratified:
| Step | Gemini’s Claim | The Actual Situation |
| 1 | “Dombili” = Kadir (Levent Ülgen) | Kadir’s nickname is “Hallederiz” (We’ll handle it) |
| 2 | “Dombili” = Mustafa’s nickname | ]Mustafa has no nickname |
| 3 | “Dombili” = Can (small child) | There is no character named “Can” |
| 4 | Correct: “Dombili” = Hasan (Erdem Baş) | The character at whom Mehmet Usta shouted “Dombili Hasan!” |
1.4. Other Systematic Errors
- The Character İpek: Gemini presented the actress playing the middle daughter, İpek, first as Sinem Öztufan, then as Arzu Balkan.The user rejected both names.
- Platonic Love: It gave the name of Mustafa’s platonic love interest as “Buse” and the actress as “Gülşah Şahin”; both were incorrect. Later, it corrected this to “Begüm” and “Begüm Erdem,” but this was also not verified by the user.
- The Neighbor-Chateau Paradox: It defined Sinan and his family as “neighbors”. However, one of the show’s main humorous elements was that this family lived in a chateau in Zekeriyaköy, and the line “there is no neighborhood” was key. Gemini failed to grasp even one of the main themes of the series.
2. Causes of Hallucinations: Why So Many Errors?
2.1. Chronological Data Confusion
In a series spanning 159 episodes and 5 years, actor changes and cast revisions pose a significant challenge for AI. Gemini processed the different periods of the series (TRT era vs. Star TV era) as a single timeframe. This caused the casts from before and after Ali Erkazan’s departure to blend together.
2.2. Context Contamination
In Gemini’s own words: “When a mistake is made first in a conversation and logic is attempted to be built upon that mistake, the AI sometimes accepts that falsehood as ‘truth’ and builds new falsehoods upon it.” Every new explanation built upon the initial error (the Maksut character) caused the system to settle on a false foundation.
2.3. Statistical Inference and Nickname Assignment Error
It showed a tendency to statistically assign a very dominant nickname like “Dombili” to the series’ most popular character (Kadir). The AI established a flawed logic such as “most mentioned character + best known nickname = correct match”.
2.4. Cross-Data Contamination
Gemini’s invention of a child character named “Can” likely indicates data contamination with another period series (e.g., “Çocuklar Duymasın”). Data from series with similar themes can become mixed.
3. User Intervention: Human Memory vs. Digital Memory
One of the most notable aspects of the dialogue is the user’s determined and systematic corrections. As someone who personally watched the series, the user:
- Noticed every false claim by Gemini immediately.
- Questioned Gemini by saying, “I don’t remember this character”.
- Identified false information, even if they didn’t provide the correct details.
- Asked Gemini to switch to “thinking mode” to be more careful.
This intervention by the user played a critical role in the reliability test of the AI. In Gemini’s words: “I became a living example of how a model, no matter how much data it has, can fail without the filter of a human who lived through that era.”
4. The “Thinking Mode” Paradox
In the middle of the conversation, the user switched Gemini to “thinking mode”. However, even this mode could not prevent the errors.On the contrary, in some cases, the AI complicated simple facts due to “overthinking” and produced new hallucinations.
Gemini’s own assessment: “Side effect of the thinking mode: Complex thought processes can sometimes overanalyze simple facts (like naming) and present wrong possibilities as if they were true by asking ‘Was it this?’”
5. Proposed Solutions and Future Perspective
5.1. Confidence Score System
The user suggested that the AI should add a reliability score to every response:
Example Ideal Response:
“The character Maksut was played by Deniz Oral.
⚠️ Confidence Note:
- Actor Info: 99% Sure
- Period Info: 40% Sure (My data is contradictory regarding whether this character was present from the beginning or joined later. Please verify via IMDb or Wikipedia.)”
5.2. Cross-Check and Second Opinion System
User’s suggestion: The AI could suggest consulting other models for critical topics. Similar to the “second opinion” principle in medicine, verification from multiple sources could be requested for important decisions.
5.3. Data Enrichment: YouTube Transcripts and Official Sources
The user’s noteworthy suggestion: AI models should be cross-trained regarding series not just with text-based data, but with original episode transcripts from YouTube and official credit information from IMDb and Wikipedia.
In this way:
- False information in forum comments can be filtered out.
- The actual lines and chronology of characters can be verified.
- Actor-character matches can be finalized.
6. The Trust Crisis: Simple Errors, Big Consequences
The user’s most striking observation was this: “When people ask about quantum physics or a complex math problem, they may not immediately verify the accuracy of the answer; there, they trust the model ‘blindly.’ ]However, when a mistake is made on a subject like En Son Babalar Duyar, where they know the lines by heart and which was part of their childhood, that ‘magic’ is broken. The question ‘How can something that doesn’t know this do my serious work?’ comes to mind.”
This observation reveals the most sensitive point of AI reliability: Users are forced to trust AI on technical subjects they cannot verify. However, when they see systematic errors in simple subjects they can verify, general trust is shaken.
7. Meta-Analysis: The AI’s Self-Assessment
One of the most interesting aspects of the dialogue is that Gemini noticed its own mistakes and analyzed them. Expressions used by Gemini included:
- “I attempted the cunning of ‘Hallederiz Kadir’ (We’ll handle it Kadir)”
- “My digital memory went bankrupt”
- “Today was a ‘failing grade’ day for me”
- “The peak point of an AI’s potential to be ‘confidently wrong’”
While this self-critical approach shows that the AI is aware of its own limits, the real problem is: Why does this awareness not kick in during the response phase?
Conclusion: “The Last AI Hears”
This dialogue on February 10, 2026, took a striking snapshot of the current state of AI technology. Even an advanced model like Gemini 2.0 Pro was capable of making systematic and layered errors on a relatively simple pop culture topic.
Key Lessons:
- Human Memory is Indispensable: The memory of the user who personally watched that series proved more reliable than the AI with massive datasets.
- [Chronological Data is Critical: The AI’s inability to distinguish changes over time (cast changes, season differences) is a major technical gap.
- Being Able to Say ‘I Don’t Know’ is a Virtue: The AI must state its uncertainty instead of fabricating when it is unsure.
- Simple Errors, Deep Consequences: Errors about a TV series shake users’ general trust in AI.
- Data Enrichment is a Must: Video transcripts, official credits, and cross-verification mechanisms must be included in the training process.
The user’s final question left a critical question mark for the future of the AI industry: “If an AI said ‘I will never hallucinate from now on’… would such an AI be used more? Or would people prefer to use a hallucinating AI?”
This dialogue demonstrated that the future of AI will be shaped not just by more data or more powerful processors, but by principles of honesty, accepting uncertainty, and respecting human supervision.
Just like Mehmet Usta’s famous exclamation “Dombili!”, perhaps the most important thing that needs to be said to AI is: Don’t say “Hallederiz” (We’ll handle it); if you don’t know, say “I don’t know.”
Note: This article is based on the analysis of an authentic dialogue that took place with Google Gemini 2.0 Pro on February 10, 2026. All errors and corrections in the dialogue are taken from the original conversation record.
A Note on Methods and Tools: All observations, ideas, and solution proposals in this study are the author’s own. AI was utilized as an information source for researching and compiling relevant topics strictly based on the author’s inquiries, requests, and directions; additionally, it provided writing assistance during the drafting process. (The research-based compilation and English writing process of this text were supported by AI as a specialized assistant.)
Aydın Tiryaki 