Transportation equity is an interdisciplinary agenda that requires both transportation and social inputs. Traditionally, transportation equity information are sources from public libraries, conferences, televisions, social media, among other. Artificial intelligence (AI) tools including advanced language models such as ChatGPT are becoming favorite information sources. However, their credibility has not been well explored. This study explored the content and usefulness of ChatGPT-generated information related to transportation equity. It utilized 152 papers retrieved through the Web of Science (WoS) repository. The prompt was crafted for ChatGPT to provide an abstract given the title of the paper. The ChatGPT-based abstracts were then compared to human-written abstracts using statistical tools and unsupervised text mining. The results indicate that a weak similarity between ChatGPT and human-written abstracts. On average, the human-written abstracts and ChatGPT generated abstracts were about 58% similar, with a maximum and minimum of 97% and 1.4%, respectively. The keywords from the abstracts of papers with over the mean similarity score were more likely to be similar whereas those from below the average score were less likely to be similar. Themes with high similarity scores include access, public transit, and policy, among others. Further, clear differences in the key pattern of clusters for high and low similarity score abstracts was observed. Contrarily, the findings from collocated keywords were inconclusive. The study findings suggest that ChatGPT has the potential to be a source of transportation equity information. However, currently, a great amount of attention is needed before a user can utilize materials from ChatGPT

翻译：交通公平是一项跨学科议程，需要交通与社会两方面的输入。传统上，交通公平信息来源于公共图书馆、会议、电视、社交媒体等。包括先进语言模型如ChatGPT在内的人工智能工具正逐渐成为受欢迎的信息来源。然而，其可信度尚未得到充分探讨。本研究探索了ChatGPT生成的与交通公平相关信息的内容和实用性。它利用了通过Web of Science（WoS）数据库检索的152篇论文。提示词被设计为让ChatGPT根据论文标题提供摘要。随后，使用统计工具和无监督文本挖掘将ChatGPT生成的摘要与人工撰写的摘要进行比较。结果表明，ChatGPT摘要与人工摘要之间存在弱相似性。平均而言，人工撰写的摘要与ChatGPT生成的摘要约有58%的相似度，最大值和最小值分别为97%和1.4%。在相似度得分高于平均值的论文摘要中，关键词更可能相似，而低于平均值的则更不可能相似。具有高相似度得分的主题包括可达性、公共交通和政策等。此外，还观察到高和低相似度得分摘要的关键词聚类模式存在明显差异。相反，关于共现关键词的发现尚无定论。研究表明，ChatGPT有潜力成为交通公平信息的来源。然而，目前用户在利用ChatGPT材料之前仍需高度审慎。