从像素到原则:十年的进步和景观在可靠的计算机视觉
Kexin Huang1,2, Yan Teng3, Yang Chen2
1Shanghai Artificial Intelligence Laboratory, Shanghai, 200232, China.
Science and engineering ethics
|June 10, 2024
概括
本研究通过分析研究趋势来解决计算机视觉 (CV) 的伦理挑战. 它提出了一个生命周期框架,以指导可靠的人工智能系统的开发.
科学领域:
- 计算机视觉 计算机视觉
- 人工智能伦理学 人工智能伦理学
- 值得信赖的AI 值得信赖的AI
背景情况:
- 计算机视觉 (CV) 技术提出了独特的社会和伦理挑战,与更广泛的人工智能 (AI) 或自然语言处理 (NLP) 截然不同.
- 现有的研究往往缺乏专注于CV的伦理维度和系统解决方案.
- 在文学中存在一个缺口,专门针对计算机视觉领域内可信赖的AI.
研究的目的:
- 量化分析过去十年计算机视觉研究中可靠方面的趋势和注意力分布.
- 识别伦理考虑与视觉模型开发的各个阶段之间的联系.
- 为实现可靠的计算机视觉提出一个生命周期框架.
主要方法:
- 使用了文献计量和文本挖掘技术.
- 分析的重点是计算机视觉领域著名学术会议的论文.
- 一个十年的研究经过了定量评估.
主要成果:
- 揭示了计算机视觉中可靠方面的发展趋势和注意力分布.
- 确定了伦理维度和视觉模型开发阶段之间的固有联系.
- 展示了一个生命周期框架,将可信的问题,AI模型管道和技术解决方案相互连接起来.
结论:
- 拟议的框架为研究人员和政策制定者提供指导,以实现可靠的计算机视觉.
- 讨论了可信实践的动机以及原则和技术属性的相互作用.
- 这项工作为专门研究计算机视觉中的伦理问题和解决方案提供了基础.
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