[How to detect scientific texts generated with artificial intelligence?]
View abstract on PubMed
Summary
This summary is machine-generated.Large language models (LLMs) aid scientific writing but pose ethical risks. Human judgment, not just AI detection, is crucial for maintaining academic integrity in the age of AI-generated content.
Area Of Science
- Scientific communication
- Artificial intelligence
- Academic integrity
Background
- Large language models (LLMs) are increasingly used in scientific writing, offering benefits like drafting assistance and promoting linguistic equity.
- However, their use introduces significant ethical and epistemological challenges, including lack of transparency and potential information manipulation.
- These issues threaten the core principles of academic integrity.
Purpose Of The Study
- To analyze the dual impact of LLMs on scientific writing, highlighting both advancements and risks.
- To evaluate the effectiveness of current AI detection tools in identifying AI-generated content.
- To emphasize the indispensable role of human critical evaluation in preserving scientific integrity.
Main Methods
- Literature review of LLM applications in scientific writing.
- Analysis of the capabilities and limitations of AI detection software (e.g., Originality.ai, ZeroGPT, Turnitin).
- Qualitative assessment of AI-generated text characteristics (e.g., formal coherence, predictability, stylistic uniformity).
Main Results
- LLMs enhance text drafting and revision, fostering linguistic equity.
- AI detectors exhibit variable effectiveness and struggle against sophisticated "text humanizers."
- AI-generated texts often display formal coherence but lack originality and stylistic diversity.
Conclusions
- Detection of AI-generated content requires more than automated tools; it necessitates human ethical and critical evaluation.
- True scientific integrity relies on human intellectual judgment, not solely on technological automation.
- A balanced approach integrating AI tools with human oversight is essential for responsible scientific communication.
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