Abstract

The intersection of philosophical research and artificial intelligence (AI) is, at first glance, fertile ground for research, but only at first glance. After all, it is not an easy task to thoroughly delve into the fundamental philosophical principles on which AI developments are based and to realize all the consequences of this relationship fully. The article is devoted to the search for those fundamental principles that may determine the value, effectiveness, and different risks that AI may generate alongside new ideas and experiences. The article exemplifies the role of AI in teaching the course "Research Methods and Analysis in Philosophical Studies" as a study. The author also analyzes the ethical and cognitive problems of AI, using two student research works as illustrations of how the course achievements are applied to consider, in particular, the bias of AI and its limited ability to "judge" compared to humans. Deliberately bypassing the history of AI development, the author describes the closest stage to us when there is a transition to creative processes, especially writing. ChatGPT is used for searching, classifying research objects, generating data, and rewriting with editing, as well as overcoming writer's block, all of which can be accomplished in a matter of minutes. There are also more specialized versions of artificial intelligence for academic work, such as searching and processing literature. True, one also has to deal with the consequences of such "encyclopedism" of AI. The fact is that AI finds information using the work of hundreds of thousands of academics (scientists, teachers), as well as writers. Everyone decides for themselves whether to use such a labor-intensive means of creating texts. However, the mechanism of AI borrowing literary sources requires immediate regulation and constant monitoring of copyright compliance. The article discusses the latest approaches to assessing the role of philosophy, which lays the principles of creating artificial intelligence and is, therefore, a fundamental part of effective AI. A field of AI philosophy is emerging that deepens and illuminates important topics, combining theoretical foundations with practical applications in technology. Furthermore, considering various concepts, such as explainable AI, highlights the need for users to understand, at least in general terms, the meaning of complex models, including information models. The conclusions emphasize the importance of moral responsibility in the development and use of AI, both personal and collective.