AI-Based Approaches for Detection and Prevention of Domestic Violence

Abstract

This study examines the role of artificial intelligence in identifying and predicting the risk factors associated with domestic violence across different cultural contexts. Domestic violence is a serious global problem that affects individuals physically, mentally, and socially, with women being the most vulnerable, although men are also impacted. Existing methods for detection and prevention are often reactive and limited in effectiveness, highlighting the need for more advanced approaches. With recent progress in AI technologies such as machine learning, deep learning, and natural language processing, it has become possible to analyze patterns of abuse and predict potential risks more accurately. These techniques can support early intervention and help provide timely assistance to victims. However, the use of AI in this area also raises important concerns related to privacy, data bias, and ethical responsibility. Additionally, cultural values, legal frameworks, and social conditions play a major role in both the occurrence of domestic violence and the effectiveness of AIbased solutions. This study stresses the importance of developing fair, transparent, and culturally sensitive systems, along with improving data diversity and integrating AI with social and public health services.