Crossing the Rubicon? The future impact of artificial intelligence on headache medicine

It is well known that artificial intelligence (AI) is revolutionizing medicine, including headache medicine. Its potential clinical implication has been reviewed elsewhere (1). A notable breakthrough in AI is the recent emergence of an easily accessible natural languagebased AI model. Anyone with access to the Internet can benefit from AI without understanding the slightest bit about programming. ChatGPT is one such easily-accessible AI program that has gained tremendous popularity in recent weeks (2). As an AI-based language model, its original purpose was to handle language processing tasks: understand the question and provide relevant answers in all accessible languages. Human knowledge is based on language. In this sense, when such a model works properly, it provides not only adequate linguistic responses but also relevant content to the question. Hence, the application’s use is wide: language translation, text summarization or rephrasing, computer code improvement/debugging, and even answering meaningful questions. Such capabilities, available to everyone, will revolutionize scientific research, manuscript preparation, grant writing, and in the end publication in scientific journals. In lieu of the recent emergence of popularity, we used ChatGPT as an example to conduct experiments on the potential of AI in scientific publishing. The experiment began with language processing tasks. When fed with an abstract for an article, the AI easily performed the following tasks with exceptional quality: expanding/ shortening the word count, rewriting the content for a different target audience, e.g., the general population, generating a letter to the editor for submission, or reformulating sentences to avoid verbatim copying. We even asked for an abstract written in the language of Shakespeare and were rather impressed. In a more serious example, the AI program was fed with abstracts published in two different languages for translation into English. In both examples, the translated text is natural and easy to understand. Cephalalgia, like many other journals, encourages the use of English language editing services, for its purpose is to improve clarity and the communication of the science behind it. What then is the difference to asking a native speaker to help out? In this regard, AI serves as a powerful tool for language editing, for both native and non-native English speakers alike. Pure language editing does not contradict any of the existing policies in Cephalalgia. However, when the language editing tool is powerful enough, the line between language editing and AI ghostwriting becomes blurred. Scientific objectivity is based on verifiability and transparency. Therefore, content edited or generated by AI services should be clearly labeled. Cephalalgia authorship guidelines state that the use of AI is allowed, however it needs to disclosed. Notably, (other) AI services have been developed to detect AI-generated content (3). AI-ghostwriters can potentially, and will eventually, be exposed. In the next experiment, we tested whether the AI could correctly solve content-related tasks, not just language-related tasks. Real-life examples from articles submitted to Cephalalgia were used, such as whether the interpretation based on a specific analysis is correct, or based on the study design, i.e., did the authors choose the right statistical analysis to analyze the data. In our examples, these questions were correctly answered by AI. We could even describe a study design and ask the AI to suggest appropriate statistical tools for further analysis. Even non-statistical questions, such as ‘how to differentiate between different types