Ethical and Legal Implications of Using AI for Predictive Policing in Child Offenses: Striking a Balance Between Safety and Surveillance

Abstract

The integration of Artificial Intelligence (AI) in predictive policing has emerged as a transformative tool for enhancing public safety, particularly in addressing crimes involving children. While the potential of AI to prevent child offenses through predictive analytics is significant, it also raises profound ethical and legal questions. This paper explores the dual-edged nature of AI in predictive policing, with a focus on striking a balance between ensuring child safety and safeguarding fundamental human rights such as privacy, autonomy, and freedom from discrimination.

Predictive patterns and stems utilize machine learning algorithms to analyse historical data, identify patterns, and forecast potential criminal activities. In cases of child offenses, these systems aim to detect early indicators of abuse, exploitation, or other harmful behaviours, enabling law enforcement agencies to intervene proactively. However, the reliance on AI introduces ethical dilemmas, including biases inherent in datasets, the risk of false positives, and potential stigmatization of individuals or communities. These concerns are particularly critical when addressing child-related offenses, where errors could lead to devastating consequences for both victims and wrongly accused individuals.[1]

From a legal standpoint, the deployment of AI in predictive policing intersects with existing frameworks governing privacy, data protection, and due process. The General Data Protection Regulation (GDPR) and similar laws emphasize the need for transparency, accountability, and proportionality in the use of AI technologies. However, the rapid evolution of AI often outpaces regulatory measures, creating gaps in oversight and enforcement. This paper examines how legal systems can adapt to address the unique challenges posed by AI-driven predictive policing, particularly in contexts involving minors.

Ethical considerations also extend to the surveillance methods employed in predictive policing. The monitoring of digital footprints, social media activity, and other personal data to predict potential offenses raises questions about consent and the right to anonymity. These practices may disproportionately affect marginalized populations, exacerbating existing inequalities and eroding trust in law enforcement. The potential misuse of such systems for over-policing or targeting specific demographics underscores the need for strict ethical guidelines and equitable implementation.[2]

This paper advocates for a balanced approach that prioritizes both child safety and the protection of civil liberties. Recommendations include the development of robust ethical frameworks, the adoption of explainable AI models to enhance transparency, and the involvement of multidisciplinary stakeholders—including ethicists, legal experts, and child advocates—in the design and deployment of predictive policing systems. Additionally, mechanisms for ongoing oversight, such as independent auditing and public accountability, are essential to ensure that AI technologies serve the greater good without infringing on individual rights.

In conclusion, while AI offers promising solutions for preventing child offenses, its application in predictive policing must be carefully regulated to address ethical and legal concerns. By fostering a culture of transparency, accountability, and inclusivity, society can harness the benefits of AI while minimizing its potential harms. Striking a balance between safety and surveillance is not only a moral imperative but also a prerequisite for the responsible use of technology in safeguarding children and upholding justice.