We know that artificial intelligence (AI) has revolutionized many fields, including academia. One of the most ethically controversial issues, especially in the academic community, is the extent to which artificial intelligence can be utilized in research and whether it can be cited as a co-author in academic works. While AI has demonstrated remarkable abilities in generating texts, summarizing research and even suggesting new ideas, the general consensus is that it should not be considered an author. And why is that?
One of the strongest arguments against AI as an author is based on the ethical principle of ‘accountability’. In academia, an author is not just someone who writes a text, but also someone who takes responsibility for the content presented. Authors are expected to ensure the accuracy of their work, respond to criticism and be accountable for ethical misconduct such as plagiarism or data fabrication.
However, in addition to lacking the capacity for accountability, artificial intelligence is also known to produce and share untrue information and to claim that this information is true, a behavior that has recently been referred to as hallucination. As such, it is also known that AI systems cannot respond to peer reviews, defend their claims and be held accountable for errors. The inability of AI to assume accountability undermines the basic principles of academic integrity and responsibility, making it unsuitable for authorship.
Another critical argument against AI’s authorship is its lack of original thinking. Academic research is not only about producing texts, but also about creating new knowledge, formulating hypotheses and interpreting data in new ways. Despite the rapid development of artificial intelligence, it seems neither legally nor practically possible that it will be capable of independent thought in the future. Within certain limitations, it can process existing data and information as requested and produce outputs based on statistical probabilities, but we cannot associate these results with real insight or creativity.
Similarly, while AI systems can help determine the methodology of a study, summarize the literature, and even propose solutions based on existing data, they are not able to provide sufficient intellectual contributions such as critical thinking, ethical reasoning, or theoretical innovations. Therefore, it is unlikely to be more than an aid to improve the productivity of the researcher and the quality of the study, rather than an author.
In fact, the role of AI in academic research is not that different from other research tools. Just like office applications such as Word and Excel, statistical tools such as SPSS, and reference management tools such as Mendeley and Zotero, which increase productivity in academic studies, artificial intelligence is nothing more than a technological auxiliary tool that does not contribute intellectually to studies.
From an ethical point of view, these are not the only problems with artificial intelligence in academic studies; the principle of ‘transparency’ regarding the level and manner of use of artificial intelligence in research is also important. According to this principle, all tools and methodologies used in the research should be fully disclosed within the scope of the study. If artificial intelligence is used for literature review, summarization or data analysis, researchers are required to state to what extent they used these systems in the study.
Even if it is assumed that some of the problems outlined above can be eliminated with advanced artificial intelligence technologies in the future, it would not be wrong to say that artificial intelligence applications will ultimately maintain their status as an auxiliary tool rather than an independent researcher, given that they are systems based on human programmed algorithms and datasets.
Ultimately, despite its impressive capabilities, AI fails to meet some of the most basic ethical principles of scientific research. Therefore, rather than being a researcher who deserves authorship, it will have an important role in the future as one of the most important assistants of researchers.