人工智能测试,评估,验证和验证可访问性:一个全面的框架
1Cognitive and Neurodiversity AI Lab, Center for Responsible AI, Virginia State University, Baltimore, VA, United States.
Frontiers in digital health
|March 16, 2026
概括
本研究引入了一个AI测试,评估,验证和验证 (TEVV) 框架,以确保人工智能 (AI) 系统可访问. 评估AI的可访问性障碍和偏见可以增强所有用户的包容性.
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 人工智能伦理学
背景情况:
- 人工智能 (AI) 系统越来越多地融入社会.
- 确保残疾人能够使用人工智能对于公平的技术采用至关重要.
研究的目的:
- 为人工智能测试,评估,验证和验证 (TEVV) 提供一个全面的框架,特别关注可访问性.
- 提高人工智能技术对不同用户群体的包容性和有效性.
主要方法:
- 开发了一个TEVV框架,包括红色团队,模型测试和现场测试.
- 强调了针对可访问性的可用性测试.
- 进行了详细的案例研究来验证框架.
主要成果:
- 使用该框架进行的系统评估确定了人工智能系统中的可访问性障碍和偏见.
- 该框架展示了AI包容性和对不同用户有效性的改进.
- 案例研究提供了框架实用性的经验证据.
结论:
- 专注于可访问性的TEVV框架为开发公平的人工智能提供了一个结构化的方法.
- 实施这个框架会导致普遍可用的AI系统.
- 这种方法支持创建有利于社会所有成员的AI.
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