Europol says AI can revolutionise police work
Artificial intelligence (AI) can revolutionise law enforcement operations, Europol’s Innovation Lab says in a new report. But using AI in police work is controversial. The use of AI in predictive policing and biometric identification are mentioned as high risks in the EU’s new Artificial Intelligence Act that is a first attempt to regulate how AI can be used.
“By harnessing AI’s advanced capabilities, law enforcement agencies can process vast datasets more efficiently, enhancing their ability to detect and counter criminal activity”, the Europol lab says.
“AI tools can streamline decision-making processes at both operational and strategic levels, enabling authorities to better identify and address criminal threats at their core.”
The report also addresses the implications of the recently adopted EU Artificial Intelligence Act, which imposes regulations on law enforcement’s use of AI.
Key provisions include a ban on certain applications, such as real-time biometric identification in public spaces, and stringent oversight of high-risk AI systems.
The Interpol report underscores that AI’s advantages must be carefully weighed against potential risks to ensure fairness, transparency, and the protection of privacy.
“Artificial intelligence will profoundly reshape the law enforcement landscape, offering unprecedented tools to enhance our ability to safeguard public safety”, Europol’s Executive Director Catherine De Bolle says in a statement.
On 1 August, the EU AI Act entered into force. It was proposed by the Commission in April 2021 and agreed by the European Parliament and the Council in December 2023.
It includes a definition of risks with using AI. Unacceptable risks that violate citizens’ fundamental rights are:
- Exploitation of vulnerabilities of persons, manipulation and use of subliminal techniques;
- Social scoring for public and private purposes;
- Individual predictive policing based solely on profiling people;
- Untargeted scraping of internet or CCTV for facial images to build-up or expand databases;
- Emotion recognition in the workplace and education institutions, unless for medical or safety reasons (i.e. monitoring the tiredness levels of a pilot);
- Biometric categorisation of natural persons to deduce or infer their race, political opinions, trade union membership, religious or philosophical beliefs or sexual orientation. Labelling or filtering of datasets and categorising data in the field of law enforcement will still be possible;
- Real-time remote biometric identification in publicly accessible spaces by law enforcement, subject to narrow exceptions.
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