| Full text | |
| Author(s): |
Sardinha, Tony Berber
Total Authors: 1
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| Document type: | Journal article |
| Source: | APPLIED CORPUS LINGUISTICS; v. 4, n. 1, p. 10-pg., 2024-01-04. |
| Abstract | |
The goal of this study is to assess the degree of resemblance between texts generated by artificial intelligence (GPT) and (written and spoken) texts produced by human individuals in real-world settings. A comparative analysis was conducted along the five main dimensions of variation that Biber (1988) identified. The findings revealed significant disparities between AI-generated and human-authored texts, with the AI-generated texts generally failing to exhibit resemblance to their human counterparts. Furthermore, a linear discriminant analysis, performed to measure the predictive potential of dimension scores for identifying the authorship of texts, demonstrated that AI-generated texts could be identified with relative ease based on their multidimensional profile. Collectively, the results underscore the current limitations of AI text generation in emulating natural human communication. This finding counters popular fears that AI will replace humans in textual communication. Rather, our findings suggest that, at present, AI's ability to capture the intricate patterns of natural language remains limited. (AU) | |
| FAPESP's process: | 22/05848-7 - Multi-dimensional analysis of language, discourse and society |
| Grantee: | Antonio Paulo Berber Sardinha |
| Support Opportunities: | Research Projects - Thematic Grants |