Not Just Novelty: A Longitudinal Study on Utility and Customization of AI Workflows

ArXiv Pub Date : 2024-02-15 DOI:10.48550/arXiv.2402.09894
Tao Long, Katy Ilonka Gero, Lydia B. Chilton
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Abstract

Generative AI brings novel and impressive abilities to help people in everyday tasks. There are many AI workflows that solve real and complex problems by chaining AI outputs together with human interaction. Although there is an undeniable lure of AI, it's uncertain how useful generative AI workflows are after the novelty wears off. Additionally, tools built with generative AI have the potential to be personalized and adapted quickly and easily, but do users take advantage of the potential to customize? We conducted a three-week longitudinal study with 12 users to understand the familiarization and customization of generative AI tools for science communication. Our study revealed that the familiarization phase lasts for 4.3 sessions, where users explore the capabilities of the workflow and which aspects they find useful. After familiarization, the perceived utility of the system is rated higher than before, indicating that the perceived utility of AI is not just a novelty effect. The increase in benefits mainly comes from end-users' ability to customize prompts, and thus appropriate the system to their own needs. This points to a future where generative AI systems can allow us to design for appropriation.
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不仅仅是新奇:关于人工智能工作流程的实用性和定制化的纵向研究
生成式人工智能为帮助人们完成日常任务带来了新颖而令人印象深刻的能力。有许多人工智能工作流程通过将人工智能输出与人机交互结合在一起,解决了实际而复杂的问题。虽然人工智能具有不可否认的诱惑力,但在新鲜感消失后,生成式人工智能工作流程的实用性如何还不确定。此外,使用生成式人工智能构建的工具具有快速、轻松地进行个性化调整的潜力,但用户是否会利用这种潜力进行定制呢?我们对 12 名用户进行了为期三周的纵向研究,以了解他们对用于科学传播的生成式人工智能工具的熟悉和定制情况。我们的研究表明,熟悉阶段持续了 4.3 个疗程,用户在这一阶段探索工作流程的功能以及他们认为哪些方面有用。熟悉之后,系统的感知效用评分高于熟悉之前,这表明人工智能的感知效用不仅仅是新奇效应。好处的增加主要来自最终用户定制提示的能力,从而使系统符合他们自己的需求。这预示着在未来,生成式人工智能系统可以让我们设计出适合自己的系统。
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