The role of Artificial Intelligence (AI) in fact-checking is often misinterpreted. While AI can assist in the process, it is not a replacement for human oversight. The use of Large Language Models (LLMs) can lead to inconsistent and unverifiable results due to the instability of their scoring and the lack of transparency in their decision-making.

A more effective approach involves using LLMs to extract structured factual information from sources, which is then evaluated using a deterministic scoring system. This method provides a transparent and auditable process, where the criteria and weights used to determine the verdict are clearly documented and consistent.

Although this approach may have limitations, such as being less adaptable and requiring deliberate engineering to modify the scoring weights, it prioritizes transparency and accountability. As AI continues to be used in high-stakes domains, it is essential to recognize the importance of human oversight in ensuring the accuracy and reliability of fact-checking.

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