A book recommendation
Simpler scientific writing with AI?
Wissenschaftliches Schreiben mit KI is the title of a book by Isabella Buck that I highly recommend! It was published in 2025, so it is as up-to-date as possible, and TUB has also licensed it as an eBook. It is written only in German.
Artificial intelligence has now found its way into almost every area of life, including scientific work. The question remains as to whether this makes sense and how AI tools can be of assistance in this field. It is not about letting AI do the thinking for us and thus also taking away our ability to act and our self-determination, at least it shouldn’t be :-). Writing yourself supports the development of your own thoughts and cannot be replaced. Scientific writing can only be learned by doing just that. Nevertheless, there are some aspects where the use of AI can make sense.
What the book is about
Isabella Buck’s book is aimed at students and doctoral candidates in all subjects; it is not an introduction to academic writing, as Buck assumes that readers already have some experience in this area. The book aims to help readers “use AI tools responsibly and competently and integrate them into the academic writing process in such a way that they really offer you added value—as helpful assistants, but not as a substitute for your own thoughts and expertise.
After an introduction to AI, the book discusses what you need to know about scientific writing with AI. It outlines usage scenarios, discusses good scientific practice, and introduces various AI tools. A separate chapter is devoted to prompting in order to exploit the full potential of AI. Finally, we explain in detail how to write with AI: from preliminary considerations and planning a scientific paper, literature review, data collection and preparation, to creating the first draft and revising the text, we show where and how AI can be used effectively.
Why I like this book so much
The book is very topical, published in 2025, and written by an author who has expertise in both scientific writing and AI. Anyone who has had anything to do with scientific work knows how difficult this can be. So it’s tempting to make the work easier for yourself. Isabella Buck shows how AI can be a tool for this and what possibilities it offers without giving up your own thinking and creativity.
Using AI tools does not mean that you no longer need to do any work yourself
Isabella Buck uses AI herself (including when writing her book), but she does so judiciously and with the necessary critical eye. She provides various arguments for why it is still necessary to do one’s own work: AI tools do not understand anything themselves and are dependent on humans; they cannot reflect or analyze critically on their own. This means that they cannot perform human thinking or replace the spirit of research. Curiosity, creativity, and intuition cannot be replaced by AI. Ultimately, AI cannot take responsibility or make decisions and then explain and defend them. These are all typical skills that are part of scientific work.
Buck uses the term AI leadership for people working in science. They can be leaders of a team of various AI tools that act as assistants. The final decision rests with the leader, who must have the necessary expertise to work with AI. This includes having a clear idea of what is expected from an AI tool before working with it.
Where AI can provide support
The above-mentioned usage scenarios for AI tools were developed by Isabella Buck and Anni-ka Limburg as part of their writing research. They are intended to show the various ways in which AI can be used to support scientific work. The spectrum of AI tools ranges from unreflective use, which involves relinquishing one’s own thinking, to relief and support, to the expansion of one’s own thinking with the help of AI.
The implementation of the last of these scenarios should be the actual goal: to use AI as an integral part of the writing process. For example, AI can serve as inspiration when interacting with AI tools in a dialogue-like manner, thereby integrating new ideas into one’s own thoughts. AI can also identify gaps in argumentation or generate different variants of an existing text passage.
In the main part of the book, Buck shows how this can be implemented using four different writing phases as examples: literature research, data collection and preparation, writing the first draft, and revising the text. The most important current tools are briefly presented and references to further current literature on the subject are provided. Beyond the book itself, QR codes repeatedly refer to more in-depth information on AI work, thus keeping the content up to date.
And a view
The book ends with an interesting outlook, fictionally addressing the possible increased use of AI in science in the future. Several theories are presented to stimulate thoughts in different directions about possible developments and raise questions about how this could, or rather must, be dealt with in the future.
There is no question that AI will continue to be a topic of discussion, but how to deal with it is something everyone must decide for themselves. Isabella Buck’s book can certainly help with this.