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Police in Edmonton, Canada partner with Axon to test body cameras with AI facial recognition, and say the results will be verified by human officers (Associated Press)
https://apnews.com/article/ai-facial-recognition-axon-edmonton-21f319ce806a0…

AI-equipped police body cameras in Canada's Edmonton spark ethical concerns
Police in Edmonton, Canada, have started a pilot project using AI-equipped body cameras to detect faces on a "high risk" watch list. The move by Axon Enterprise, Inc. has raised ethical concerns, especially since the company previously paused facial recognition due to privacy issues. The pilot aims to enhance officer and public safety by identifying individuals flagged for a history of serious offenses. However, critics worry about societal risks and the lack of public debate. Axon CEO Rick Smi…

Towards a Framework for Supporting the Ethical and Regulatory Certification of AI Systems
Fabian Kovac, Sebastian Neumaier, Timea Pahi, Torsten Priebe, Rafael Rodrigues, Dimitrios Christodoulou, Maxime Cordy, Sylvain Kubler, Ali Kordia, Georgios Pitsiladis, John Soldatos, Petros Zervoudakis
https://arxiv.org/abs/2510.00084

Towards a Framework for Supporting the Ethical and Regulatory Certification of AI Systems
Artificial Intelligence has rapidly become a cornerstone technology, significantly influencing Europe's societal and economic landscapes. However, the proliferation of AI also raises critical ethical, legal, and regulatory challenges. The CERTAIN (Certification for Ethical and Regulatory Transparency in Artificial Intelligence) project addresses these issues by developing a comprehensive framework that integrates regulatory compliance, ethical standards, and transparency into AI systems. In thi…

Ethical AI prompt recommendations in large language models using collaborative filtering
Jordan Nelson, Almas Baimagambetov, Konstantinos Avgerinakis, Nikolaos Polatidis
https://arxiv.org/abs/2510.06924

Ethical AI prompt recommendations in large language models using collaborative filtering
As large language models (LLMs) shape AI development, ensuring ethical prompt recommendations is crucial. LLMs offer innovation but risk bias, fairness issues, and accountability concerns. Traditional oversight methods struggle with scalability, necessitating dynamic solutions. This paper proposes using collaborative filtering, a technique from recommendation systems, to enhance ethical prompt selection. By leveraging user interactions, it promotes ethical guidelines while reducing bias. Contri…