AI助力沟通辅助系统，但评估需考虑用户多重需求。
It's Complicated: On the Design and Evaluation of AI-Powered AAC Interfaces
- 从六个复杂问题场景出发，分析AI在AAC中的应用潜力。
- 提出融合交叉身份因素的评估方法，更贴近真实使用体验。
- 适合人机交互、无障碍设计及AI伦理研究者参考。
人工智能（AI）可提升使用增补替代沟通（AAC）人士的能力。然而，评估AI赋能的AAC界面颇具挑战。个体具有多重身份属性，现有评估指标难以捕捉其复杂且细微的需求。本文探讨了六个AAC问题领域的复杂性，分析了AI在其中的应用可能，并提出更稳健的评估方法，以纳入用户的交叉身份特征。同时讨论这些领域共有的深层问题，并说明如何通过所提评估方法加以应对。
原文摘要 · Abstract (English)
Artificial intelligence (AI) can enhance what people who use augmentative and alternative communication (AAC) are able to do with their systems. However, evaluating AI-powered AAC interfaces can be difficult. People are intersectional beings and current evaluation metrics can struggle to capture the multifaceted and nuanced desires people may have for their AAC. We explore the complicated nature of six AAC problem spaces, explore how AI might be used in these spaces, and suggest more robust methods of evaluation that take the intersectional nuances of people into account. We also discuss broader issues that arise across these problem spaces and how they could be addressed using our proposed evaluation methods.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。