The AI Act in a law enforcement context: The case of automatic speech recognition for transcribing investigative interviews

Q1 Social Sciences Forensic Science International: Synergy Pub Date : 2024-01-01 DOI:10.1016/j.fsisyn.2024.100563

Radina Stoykova , Kyle Porter , Thomas Beka

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Abstract

Law enforcement agencies manually transcribe thousands of investigative interviews per year in relation to different crimes. In order to automate and improve efficiency in the transcription of such interviews, applied research explores artificial intelligence models, including Automatic Speech Recognition (ASR) and Natural Language Processing. While AI models can improve efficiency in criminal investigations, their successful implementation requires evaluation of legal and technical risks.

This paper explores the legal and technical challenges of applying ASR models to investigative interviews in the context of the European Union Artificial Intelligence Act (AIA). The AIA provisions are discussed in the view of domain specific studies for interviews in the Norwegian police, best practices, and empirical analyses in speech recognition in order to provide law enforcement with a practical code of conduct on the techno-legal requirements for the adoption of such models in their work and potential grey areas for further research.

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执法背景下的人工智能法案：用于转录调查访谈的自动语音识别案例。

执法机构每年手工记录数千份与不同犯罪有关的调查访谈。为了自动化和提高这类采访的转录效率，应用研究探索了人工智能模型，包括自动语音识别（ASR）和自然语言处理。虽然人工智能模型可以提高刑事调查的效率，但它们的成功实施需要对法律和技术风险进行评估。本文探讨了在欧盟人工智能法案（AIA）的背景下，将ASR模型应用于调查性访谈的法律和技术挑战。AIA条款在挪威警方访谈的特定领域研究、最佳实践和语音识别的实证分析中进行了讨论，以便为执法部门提供有关在其工作中采用此类模型的技术法律要求的实用行为准则，以及进一步研究的潜在灰色地带。

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