In this position paper, we argue that careless reliance on AI to answer our questions and to judge our output is a violation of Grice's Maxim of Quality as well as a violation of Lemoine's legal Maxim of Innocence, performing an (unwarranted) authority fallacy, and while lacking assessment signals, committing Type II errors that result from fallacies of the inverse. What is missing in the focus on output and results of AI-generated and AI-evaluated content is, apart from paying proper tribute, the demand to follow a person's thought process (or a machine's decision processes). In deliberately avoiding Neural Networks that cannot explain how they come to their conclusions, we introduce logic-symbolic inference to handle any possible epistemics any human or artificial information processor may have. Our system can deal with various belief systems and shows how decisions may differ for what is true, false, realistic, unrealistic, literal, or anomalous. As is, stota AI such as ChatGPT is a sorcerer's apprentice.

翻译：在这篇立场论文中，我们主张，在回答问题和评判输出时轻率依赖人工智能，不仅违反了格赖斯（Grice）的质量准则，也违反了勒莫因（Lemoine）的无罪推定法律准则，构成了一种（无根据的）权威谬误，并且在缺乏评估信号的情况下，因逆谬误而犯下第二类错误。当前对人工智能生成和评估内容的关注点集中在输出和结果上，除了未能给予应有的尊重外，还缺失了对人的思维过程（或机器的决策过程）追踪的要求。通过刻意规避无法解释其结论来源的神经网络，我们引入了逻辑符号推理机制，以处理任何人类或人工信息处理器可能拥有的认知体系。我们的系统能够应对多种信念系统，并展示对真、假、现实、非现实、字面义或异常等不同判断可能产生的不同决策。目前，像ChatGPT这样的大语言模型（stota AI）仍是一个巫师的学徒。