With every query to ChatGPT, Claude, or Gemini, we enter into an interaction with a mathematical model that predicts the next word in a sequence. As noted by the Honolulu Star-Advertiser, it is essential to approach the outputs of these models with a certain degree of skepticism. This phenomenon, known as hallucination, is not a bug in the code that can be easily fixed, but an inherent property of the way these models are trained.

The Mechanism of Hallucinations: Why Does AI "Lie"?

To critically assess information, we must understand what happens "under the hood." LLMs are not encyclopedias; they are sophisticated statistical tools. When a model is asked about a historical fact or a legal regulation, it does not search a database for the actual document. Instead, it generates text to match the patterns it saw during its training. If the precise information is missing from its data, the model attempts to "fill in the gaps" based on probability, leading to the creation of a plausible-sounding but completely nonsensical answer.

This problem is particularly sensitive in the context of the Czech language. While models like GPT-4o or Claude 3.5 Sonnet demonstrate a high degree of accuracy in English, their ability to work with the nuances of Czech may be lower. This means that the risk of hallucinations for Czech queries — especially regarding specific local laws or historical details — is statistically higher. Users in the Czech Republic should therefore always require a double fact-check when working with Czech texts generated by AI.

Model Comparison: Who Is the Most Accurate?

Currently (June 2026), the market is divided among several dominant players, each with a different tendency toward accuracy:

• OpenAI GPT-4o / GPT-5: The industry standard. Thanks to integration with search tools (SearchGPT), it minimizes hallucinations using RAG (Retrieval-Augmented Generation). The price for a personal subscription is around $20 (approx. 460 CZK) per month.
• Anthropic Claude (3.5/4): Often considered more "human-like" and less prone to aggressively fabricating facts than GPT. It is excellent for analyzing long documents. The price is similar to OpenAI.
• Google Gemini (Ultra/Pro): Has a huge advantage in integration with the Google ecosystem and the ability to browse up-to-date web results in real time. It is very strong in multimodal tasks (text + image + video).
• DeepSeek: A Chinese model that has surprised in recent months with extreme efficiency and low cost, but requires increased attention from Czech users due to cultural and political filters in its data.

From the perspective of benchmarks (e.g., TruthfulQA), we see that the best results are achieved by models that combine generative capabilities with external search mechanisms. A model alone without access to the live internet is almost always risky when it comes to factual accuracy.

Practical Impact: What Does This Mean for Czech Companies and Individuals?

For the Czech market, this issue has three main dimensions:

1. Legal and Regulatory Responsibility (EU AI Act)

Given the implementation of the EU AI Act, companies in the Czech Republic must be extremely careful when deploying AI into processes that affect citizens' rights. If a company uses AI for automated decision-making or generating legal advice without human oversight (Human-in-the-loop), it may face high fines. Responsibility for an error in the text lies not with the model, but with the person who published it.

2. Quality of Czech Content

Marketing agencies and editorial teams must use AI as an assistant, not as an author. Automated article generation without factual verification leads to the degradation of website quality and can negatively affect SEO (Search Engine Optimization), because search engines like Google still prioritize E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness).

3. Efficiency vs. Risk

For the average user, this means: Use AI for brainstorming, structuring texts, or explaining concepts. But if you need a date, a name, a legal citation, or a mathematical result — always verify it in a primary source.

How to Effectively Check AI: Tips for Experts

To keep your workflow safe, we recommend these techniques:

• Prompt Engineering: Instead of "Tell me about the history of Prague," try "Present facts about the history of Prague and provide a source or reference to a historical document for each claim. If you are unsure, admit it."
• Chain-of-Thought Method: Ask the model to describe its solution process step by step. This often helps the model "realize" logical errors in its own calculation.
• Cross-checking: Take the answer from ChatGPT and try having it verified by another model, such as Claude. Differences in the answers are a clear signal for further investigation.