Testing of detection tools for AI-generated text
HTW Berlin - University of Applied Sciences · Riga Technical University · +5 more institutions
Abstract
Abstract Recent advances in generative pre-trained transformer large language models have emphasised the potential risks of unfair use of artificial intelligence (AI) generated content in an academic environment and intensified efforts in searching for solutions to detect such content. The paper examines the general functionality of detection tools for AI-generated text and evaluates them based on accuracy and error type analysis. Specifically, the study seeks to answer research questions about whether existing detection tools can reliably differentiate between human-written text and ChatGPT-generated text, and whether machine translation and content obfuscation techniques affect the detection of AI-generated…
Citation impact
- FWCI
- 14.10
- Percentile
- 100%
- References
- 21
Authors
8Topics & keywords
- Computer science
- Plagiarism detection
- Generative grammar
- Artificial intelligence
- Set (abstract data type)
- Obfuscation
- Data science
- Field (mathematics)
- Quality Education