{"title":"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。","authors":"Radina Stoykova , Kyle Porter , Thomas Beka","doi":"10.1016/j.fsisyn.2024.100563","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div><div>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.</div></div>","PeriodicalId":36925,"journal":{"name":"Forensic Science International: Synergy","volume":"9 ","pages":"Article 100563"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11664072/pdf/","citationCount":"0","resultStr":"{\"title\":\"The AI Act in a law enforcement context: The case of automatic speech recognition for transcribing investigative interviews\",\"authors\":\"Radina Stoykova , Kyle Porter , Thomas Beka\",\"doi\":\"10.1016/j.fsisyn.2024.100563\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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.</div><div>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.</div></div>\",\"PeriodicalId\":36925,\"journal\":{\"name\":\"Forensic Science International: Synergy\",\"volume\":\"9 \",\"pages\":\"Article 100563\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11664072/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Forensic Science International: Synergy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2589871X24001104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forensic Science International: Synergy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2589871X24001104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
The AI Act in a law enforcement context: The case of automatic speech recognition for transcribing investigative interviews
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.