2024/05/11 by Sujita Kumar Kar, Teena Bansal, Sumit Modi +1 · 3 citations
Medicine · Psychology · #Artificial Intelligence in Healthcare and Education #Electroconvulsive Therapy Studies #Mental Health via Writing
paper · pdf · doi:10.1177/02537176241247934
openalex publication_date 2024/05/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
Background: Recently, Artificial intelligence (AI) has significantly influenced academic writing. We aimed to investigate the sensitivity of the free versions of popular AI-detection software programs in detecting AI-generated text. Methods: We searched for AI-content-detection software on Google and selected the first 10 free versions that allowed a minimum of 500 words for text analysis. Then, we gave ChatGPT 3.5 version a command to generate a scientific article on the “Role of Electroconvulsive Therapy (ECT) in Treatment-resistant Depression” under 500 words. After generating the primary text, we rephrased it using three different software tools. We then used AI-detection software to analyse the original and paraphrase texts. Results: 10 AI-detector tools were tested on their ability to detect AI-generated text. The sensitivity ranged from 0% to 100%. 5 out of 10 tools detected AI-generated content with 100% accuracy. For paraphrased texts, Sapling and Undetectable AI detected all three software-generated contents with 100% accuracy. Meanwhile, Copyleaks, QuillBot , and Wordtune identified content generated by two software programs with 100% accuracy. Conclusion: The integration of AI technology in academic writing is becoming more prevalent. Nonetheless, relying solely on AI-generated content can diminish the author’s credibility, leading most academic journals to suggest limiting its use. AI-content-detection software programs have been developed to detect AI-generated or AI-assisted texts. Currently, some of the platforms are equally sensitive. However, future upgrades may enhance their ability to detect AI-generated text more accurately.