人工智能时代的信息圈,数据化和决策过程
Andrea Lavazza1, Mirko Farina2,3
1Centro Universitario Internazionale, Via Antonio Garbasso 42, Arezzo, 52100 AR Italy.
概括
人工智能 (AI) 的实施需要将文物整合到我们的世界,需要广泛的数据化. 这种普遍的数据化引发了与隐私,工人自由和人类创造力有关的重大道德和社会问题.
科学领域:
- 技术的哲学技术的哲学
- 技术社会学技术的社会学.
- 人工智能的伦理学 人工智能的伦理学
背景情况:
- 人工智能 (AI) 融入社会需要了解将AI工件纳入我们的环境的条件.
- 环境越来越多地被设计为与智能机器兼容,从而为人类和机器人量身定制的微型环境.
- 人工智能的普遍使用推动了将生物领域整合到适合人工智能技术的信息圈的需求.
研究的目的:
- 综合反思人工智能实施所带来的数据化的道德和社会影响.
- 在AI的背景下考虑普遍数据化的可取性.
- 分析数据化对隐私,员工自主,人类创造力和社会价值观的影响.
主要方法:
- 对人工智能实施及其社会要求的概念分析.
- 基于当前对人工智能的解释进行的伦理和社会影响评估.
- 探索广泛的数据化可能带来的后果.
主要成果:
- 数据化对人工智能至关重要,因为数据是人工智能逻辑数学模型的基础.
- 隐私保护可能在结构上变得不可能,冒着政治和社会控制的风险.
- 工人的自由,人类的创造力和与人工智能逻辑的分歧可能会受到限制.
- 推动效率和工具性理由的推动可能会主导社会和生产结构.
结论:
- 由人工智能驱动的普遍数据化带来了重大的伦理挑战.
- 社会结构可能会转向优先考虑效率和工具理性,而不是人文价值观.
- 仔细考虑人工智能的社会融合对于减轻潜在的负面影响至关重要.
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