63 lines
5.2 KiB
TeX
63 lines
5.2 KiB
TeX
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\chapter*{Use of Artificial Intelligence in This Thesis}
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\adjustmtc
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\addcontentsline{toc}{chapter}{Use of Artificial Intelligence in This Thesis}
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This thesis has been written during the years of 2020 - 2025. In this time, Artificial Intelligence (AI) technology
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including Large Language Models (LLMs) has entered widespread adoption. I have used such LLM systems in the preparation
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of this thesis. At the time this thesis was written, LLMs were a powerful and useful technology, but often produced
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wrong output. Thus, I used the following list of observations to guide my LLM use during the writing of this thesis.
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\begin{enumerate}
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\item Passing text through an LLM is an imprecise operation. Especially when large amounts of text are passed
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through an LLM, despite clear instructions such as ``only fix spelling errors'', the LLM output might deviate
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from the source text. Therefore, the document text should never be passed through the LLM, and the LLM should be
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prompted to point out problems, or to produce a list of suggestions for improvements instead.
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\item LLMs are really bad at summarizing text that contains novel concepts. LLM summaries of text often converge to
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a re-stating of the general consensus on the text's main topic. Where the source text deviates from conventionla
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wisdom or makes novel points, an LLM summary will likely mis-represent those conclusions. Additionally, LLMs are
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bad at capturing the point of a text. Unless extreme care is taken when prompting, it is easy to lead an LLM to
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produce an inaccurate summary of a text that agrees with the prompt, but misses the gist of the text. Therefore,
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extreme caution should be applied when using an LLM for summarization, and LLM output should be checked
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diligently in such instances.
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\item LLMs are bad at generating text from scratch. Especially on topics of academic interest that are novel and
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that do not have well-known answers that can be found in the training corpus for these models, in general they
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will not produce useful text when prompted. Therefore, LLMs should never be used to generate novel text.
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\item LLMs are really bad at giving references. Prompts that ask for academic references on a topic are likely to
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produce non-existing ``hallucinated'' references. The existing references an LLM is most likely to dig up
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usually occur on the first page of a web search on the topic, or are frequently cited in literature on the
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topic. Thus, LLMs should never be directly queried for references. When researching a new concept, a better use
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of an LLM is the generation of query strings for search engines like Google Scholar.
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\end{enumerate}
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Applying these observations, I never copied text from the LLM into this thesis. Where I edited the text of this thesis
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using suggestions from LLM output, I critically evaluated the LLM output and carefully considered each edit. Following
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are some examples of how I used LLMs in the writing of this thesis.
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\paragraph{For checking spelling and grammar,} the LLM was prompted with an instruction to review the text and output a
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list of errors. The list was then reviewed and the errors were fixed in the source document by hand. An example prompt
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for the LLM in this case might be: ``The attached file contains the LaTeX source code of a chapter of an doctoral thesis
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titled `...'. Review the text and list any mistakes in spelling or grammar.''
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\paragraph{For improving formulation patterns,} the LLM was prompted with a short excerpt of text of at most two
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paragraphs and instructions asking for an improved version of the text. In response to such a prompt, the LLM will often
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change the meaning of parts of the text. Thus, I used the output as a reference example, and manually adjusted the
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source document applying parts of the LLM response where fitting. An example prompt in this case might be: ``The
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following text are two paragraphs from a chapter on `...' in a PhD thesis on `...' . Improve the wording of these
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paragraphs to make them easier to read and understand.''.
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\paragraph{For improving the structure of the text,} the LLM was prompted with an instruction to review the text and
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output a list of recommendations. The list was then reviewed, and changes were made to the source document by hand. An
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example prompt in this case might be: ``The attached document contains the LaTeX source code of a chapter of a PhD
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thesis on `...' . Critically assess the structure and organization of the chapter and write a list of suggestions for
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improvement.''
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In accordance with the recommendations of the University and State Library Darmstadt regarding the labelling and
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documentation of AI-generated materials dated September 22, 2025\cite{RecommendationsUniversityState2025}, instances
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where I used an LLM to edit parts of the text of this thesis as described above have not been explicitly labelled in the
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text. The LLM in this use assumes a similar role a human editor might assume reviewing the text.
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Besides the use of LLMs as described above, a specialized machine translation tool was used to create the German
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translation of the abstract at the beginning of this thesis. This use is marked explicitly.
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\chapterbibliography
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