人工智能期望管理:理解利益相关者对人工智能系统的信任和接受的框架
Marjorie Kinney1, Maria Anastasiadou1, Mijail Naranjo-Zolotov1
1NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, Campus de Campolide, 1070-312, Lisboa, Portugal.
Heliyon
|April 5, 2024
概括
管理期望是可信的人工智能 (AI) 的关键. 本研究提出了一个框架,以捕捉最终用户的期望,确保人工智能系统满足用户需求,并减轻医疗保健和教育等领域的风险.
科学领域:
- 计算机科学 计算机科学
- 人与计算机的交互
- 人工智能伦理学
背景情况:
- 可信度对于人工智能 (AI) 的采用至关重要.
- 错误的利益相关者期望可能会阻碍人工智能系统的成功.
- 需要采取积极的方法来管理用户的预期.
研究的目的:
- 引入一个框架来管理最终用户对可靠人工智能系统的期望.
- 通过实证研究来验证框架的相关性和稳定性.
主要方法:
- 为值得信赖的AI开发了一个全面的期望管理框架.
- 进行了半结构化采访,与14个不同的终端用户在医疗保健和教育.
- 对面试成绩单进行定性分析,以确定关键主题和用户观点.
主要成果:
- 确定了关键主题和对最终用户对人工智能期望的不同观点.
- 验证了框架在捕捉基本用户预期方面的实用性.
- 强调了系统属性和潜在挑战的重要性.
结论:
- 开发的框架有助于深入讨论用户对可靠人工智能的期望.
- 它阐明了关键系统属性和潜在风险.
- 该框架是协调利益相关者的预期和确保AI有效性的重要工具.
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