人工智能法案在执法环境中:用于转录调查采访的自动语音识别案例
Radina Stoykova1, Kyle Porter2, Thomas Beka3
1University of Groningen, Broerstraat 5, 9712 CP Grongingen, Netherlands.
Forensic science international. Synergy
|December 24, 2024
概括
本研究探讨了使用人工智能 (AI),特别是自动语音识别 (ASR) 来转录警察采访的法律和技术挑战. 它提供了根据欧盟人工智能法案 (AIA) 采用人工智能的执法指南.
科学领域:
- 法律技术 法律技术
- 人工智能法 人工智能法
- 语音识别技术 语音识别技术
背景情况:
- 执法机构每年转录大量调查采访,这是一个劳动密集的过程.
- 通过人工智能的自动化,包括自动语音识别 (ASR) 和自然语言处理 (NLP),提供了潜在的效率增长.
- 成功实施人工智能需要对相关的法律和技术风险进行彻底评估.
研究的目的:
- 探索将ASR模型应用于调查面试的法律和技术挑战.
- 在欧盟人工智能法案 (AIA) 的框架内分析这些挑战.
- 为执法部门提供一个实用的行为准则,用于采用ASR模型.
主要方法:
- 在调查采访中讨论与ASR相关的AIA条款.
- 从挪威警察采访中整合了特定领域的研究.
- 考虑语音识别中的最佳实践和经验分析.
主要成果:
- 确定了在执法部门采用ASR的关键技术法律要求.
- 突出了潜在的灰色地带和挑战,在应用ASR在AIA下的调查采访.
- 为警察使用ASR.提供了一个实用的行为准则的基础.
结论:
- 在调查采访中采用ASR提出了欧盟AIA的重大法律和技术障碍.
- 对监管要求和经验表现的明确理解对于负责任的实施至关重要.
- 需要进一步的研究来解决已识别的灰色区域,并完善执法的最佳实践.
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