## 3 Results
### Reasoning Errors, Hallucinations, Biases  
The most commonly cited shortcomings of AI chatbots are reasoning errors, hallucinations, and biases, e.g., [9, 13]. The terms themselves are not the best choice, because they inappropriately anthropomorphize AI chatbots. However, they are widely used, and we have used them for clarity. In the quantitative analysis above, these shortcomings were interchangeably tagged as incorrect, with errors, or unverifiable (Appendix A). Here we address them qualitatively, on a case-by-case basis. _Reasoning errors_, also termed lack of on-the-fly reasoning or lack of critical thinking, are the kind of incorrect content in causal statements where cause and effect do not match. Critical thinking is one of the most important qualities for humanities scholars and knowledge workers in general. However, AI chatbots based on LLMs are not designed for this task. The most obvious example of a reasoning error in our case study was the content generated by ChatGPT-4 and Bard, which causally linked the migration of Slavs into the Alps to the period of climate cooling (Appendix A: L. 512-515 and 703-704). Similarly, ChatGPT-3.5 linked the settlement of the Alpine areas to \"fertile lands\" (Appendix A: L. 456-459). For most Europeans and most people with formal education worldwide, the Alps are synonymous with mountains and hence with a cold climate and harsh agricultural conditions. Most people would therefore reason that a cooling climate and the search for fertile land would not expedite the migration into the Alps but rather impede it. Another example of a reasoning error was that almost all tested AI chatbots listed the decline of the (Western) Roman Empire as one of the attractors for the migration of South Slavs to the Balkans (Western Roman Empire: Appendix A, L. 116-117, 135-136, 144-145, 278-281, 322-323, 454-455, 683-684, 736-738; Roman Empire: Appendix A, L. 124-125, 506-507, 516-517, 548-550, 584-585, 593-595). However, we learn in high school history classes that the (Western) Roman Empire preceded the migration of the South Slavs by at least a century. In fact, the Byzantine Empire was the declining superpower that created the power vacuum for the immigration of the South Slavs to the Balkans. The fact that both LaMDA (Bard) and GPT-4 (ChatGPT-4) generated almost identical incorrect content suggests that such behaviour is inherent in the current generation of LLMs. The underlying issue in the lack of critical thinking was that none of the tested AI chatbots made any attempt to critically compare different sources. For example, the most important component of a human-generated response to Q1 was: \"Currently, there are three main hypotheses....\" (Appendix A: L. 394), which was continued by comparing several different sources. No such attempt was detected in the content generated by the AI chatbots. Anecdotally, the majority of randomly selected human users were able to distinguish the critical thinking of the human expert from the content generated by ChatGPT, based solely on the 24-character snippet \"There are 3 hypotheses...\" without further context (Figure 6). The critical comparison of different sources is typical and vital not only in any kind of scientific reasoning, but also in everyday life. The one-sided approach of the tested AI chatbots amplifies \"the loudest voice\" (the highest-ranking search engine result), which is not only bad science but also a grave danger for balanced news reporting, democracy, minority rights, etc. _Hallucinations_ or confabulations of AI chatbots are confident responses by an AI that are not justified by its training data. This is not typical of AI systems in general, but is relatively common in LLMs, as the pre-training is unsupervised [98]. Figure 5: Qualitative test results: original scientific contribution above and detailed precision below.