Natural Language Generation tools, such as chatbots that can generate human-like conversational text, are becoming more common both for personal and professional use. However, there are concerns about their trustworthiness and ethical implications. The paper addresses the problem of understanding how different users (e.g., linguists, engineers) perceive and adopt these tools and their perception of machine-generated text quality. It also discusses the perceived advantages and limitations of Natural Language Generation tools, as well as users' beliefs on governance strategies. The main findings of this study include the impact of users' field and level of expertise on the perceived trust and adoption of Natural Language Generation tools, the users' assessment of the accuracy, fluency, and potential biases of machine-generated text in comparison to human-written text, and an analysis of the advantages and ethical risks associated with these tools as identified by the participants. Moreover, this paper discusses the potential implications of these findings for enhancing the AI development process. The paper sheds light on how different user characteristics shape their beliefs on the quality and overall trustworthiness of machine-generated text. Furthermore, it examines the benefits and risks of these tools from the perspectives of different users.

翻译：自然语言生成工具，例如能够生成类人对话文本的聊天机器人，在个人和专业用途中日益普及。然而，对其可信度和伦理影响存在担忧。本文探讨了不同用户（如语言学家、工程师）如何感知和采用这些工具，以及他们对机器生成文本质量的看法。文章还讨论了自然语言生成工具的感知优势与局限，以及用户对治理策略的信念。本研究的主要发现包括：用户专业领域和专业知识水平对自然语言生成工具感知可信度及采用的影响；用户对机器生成文本在准确性、流畅性和潜在偏见方面与人类撰写文本的比较评估；以及参与者所识别的与这些工具相关的优势与伦理风险分析。此外，本文讨论了这些发现对改进人工智能开发过程的潜在启示。文章阐明了不同用户特征如何塑造其对机器生成文本质量和整体可信度的信念，并从不同用户视角审视了这些工具的益处与风险。