This article provides a comprehensive overview of the fairness issues in artificial intelligence
(AI) systems, delving into its background, definition, and development process. The article …

Predicting crime using machine learning and deep learning techniques has gained
considerable attention from researchers in recent years, focusing on identifying patterns and …

Researchers and practitioners in the fairness community have highlighted the ethical and
legal challenges of using biased datasets in data-driven systems, with algorithmic bias …

Group decision making plays a crucial role in our complex and interconnected world. The
rise of AI technologies has the potential to provide data-driven insights to facilitate group …

AI-driven decision-making can lead to discrimination against certain individuals or social
groups based on protected characteristics/attributes such as race, gender, or age. The …

Smart policing refers to the use of advanced technologies such as artificial intelligence to
enhance policing activities in terms of crime prevention or crime reduction. Artificial …

Prediction algorithms are regularly used to support and automate high-stakes policy
decisions about the allocation of scarce public resources. However, data-driven decision …

The advent and growing popularity of generative artificial intelligence (GenAI) holds the
potential to revolutionise AI applications in forensic psychiatry and criminal justice, which …

Current national and international guidelines for the ethical design and development of
artificial intelligence (AI) and robotics emphasize ethical theory. Various governing and …

Public institutions, such as law enforcement agencies or health centers, have a vast volume
of unstructured text documents, eg police reports. Currently, before this data can be shared …