Conversational AI Tools for Environmental Topics: A Comparative Analysis of Different Tools and Languages for Microplastics, Tire Wear Particles, Engineered Nanoparticles and Advanced Materials

Abstract

Artificial intelligence gained a surge in popularity through the release of conversational artificial intelligence tools, which enable individuals to use the technology without any prior knowledge or expertise in computational science. Researchers, content writers, as well as curious minds may use these tools to investigate any topics in question. Environmental topics, as one of the current public concerns, are covered by many different kinds of media, indicating a broad public interest. To assess the possibility of using these tools in environmental-related content writing or research, we tested the capabilities of conversational artificial intelligence tools on selected environmental topics. In particular, we tested different tools (ChatGPT, Microsoft Bing, Google Bard) and different languages (English, Spanish, Korean, German, Turkish and Chinese) via using selected questions and compared the answers with each other. Our results suggest that conversational artificial intelligence tools may provide satisfactory and comprehensive answers; however, we found some of the statements debatable and texts still need to be reviewed by an expert. Selected tools may offer specific advantages, such as providing references, although certain issues may need to be checked for each tool. The usage of different languages may provide additional points within the content; however, this does not necessarily imply that these new facets arise solely from utilizing different languages, since new aspects may also be attributed to the ‘randomness of the generated answers’. We suggest asking the same question several times as the tools mostly generate random answers each time, especially for ChatGPT, to obtain a more comprehensive content.