Artificial Intelligence (AI) is revolutionizing the way we prevent and detect crime. It's helping law enforcement agencies become faster, more accurate, and more efficient in tackling criminal activities. In this, paper we will first outline why and how we are trying to raise awareness of the coming AI Tsunami that will affect every single organisation, every single job in every country. Bangladesh is no exception and will be hit just as other countries amongst the Low and Middle income countries . We will first outline the likely impacts of AI on key groups in Bangladesh and what they can do to thrive in the AI era   before showing how AI is being applied across different areas of law enforcement and sharing real-world examples to illustrate its impact in crime prevention and detection .

1. Predictive Policing

Predictive policing uses AI algorithms to forecast where and when crimes are likely to occur based on historical data. For example:

• Los Angeles: The city implemented PredPol, a tool that analyzes crime data to predict future hotspots. Within two years, it contributed to a 22% reduction in burglaries. However, this approach has raised ethical concerns about potential racial profiling.

• Durham, UK: An AI system called HART assesses suspects' risk levels to assist in decisions about pre-trial releases.

• Tacoma, Washington: Predictive policing through AI led to a significant reduction in crime rates. The system analyses patterns in crime types, locations, and timeframes to suggest proactive law enforcement strategies.

2. Real-Time Surveillance

AI-enhanced surveillance plays a crucial role in urban areas prone to criminal activities:

• Sea Point, South Africa: Deployment of AI-powered cameras developed by Hikvision resulted in a 65% drop in crime. These intelligent cameras can identify suspicious activities like unattended bags or unusual movements, analysing data directly within the camera to minimize delays.

• London Underground: AI helps detect anomalies such as potential suicide attempts by analysing real-time video feeds, allowing for faster and more efficient responses.

3. Crime Pattern Analysis

AI excels at processing large datasets to identify patterns of criminal behavior:

• IBM’s Watson: Utilized by law enforcement agencies to track repeat offenders and predict potential criminal behaviour based on past activities. It can also highlight correlations between unrelated crimes, uncovering broader criminal networks.

• New York's CompStat System: Uses AI to identify crime trends, leading to a 40% reduction in major crimes over a 10-year period. This approach enables data-driven decision-making in police resource allocation.

4. Facial Recognition

Facial recognition technology has become a prominent AI application in crime detection:

• Cloud Walk in China: Monitors individuals to predict potential criminal activity. In Zhengzhou, this technology is deployed at train stations to catch criminals attempting to flee the city.

• United States Airports and Borders: Facial recognition aids in identifying wanted individuals by comparing live feeds with criminal databases. However, concerns about privacy violations have led to legislation like the California Moratorium on Facial Recognition.

5. Cybercrime Detection

AI is pivotal in detecting and preventing cybercrime:

• Europol's Use of AI: AI tools are increasingly used for cybercrime detection, especially in spotting sophisticated phishing schemes and ransomware attacks.

• WannaCry Ransomware Attack: AI-based cybersecurity systems helped identify the spread of the malware and neutralize its impact before more systems were compromised.

6. Threat Detection in Social Media

AI monitors social media platforms for potential threats:

• France: Law enforcement agencies use AI to detect early signs of terrorist activities, significantly reducing the risk of attacks.

• Chicago: AI-driven systems monitor social media for gang-related activities, allowing police to intervene before conflicts escalate into violence. These systems analyse language, tone, and network connections to flag suspicious behaviour.

7. Digital Forensics

AI has transformed digital forensics by automating the analysis of digital devices:

• Magnet Forensics: Helps law enforcement recover deleted data and analyse communication patterns to link suspects to criminal activities.

• Drug Cartel Case in Mexico: AI-driven forensic analysis traced encrypted communications between cartel members, leading to successful prosecutions.

8. AI-Driven Hotspot Policing

AI enhances hotspot policing by predicting where future crimes might occur:

• Chicago’s Heat List: Identifies individuals most likely to be involved in violent crimes based on AI analysis, enabling targeted interventions.

• Kansas City: AI-driven hotspot policing contributed to a 12% decrease in violent crimes in targeted areas.

9. Behavioural Analysis

AI systems can predict criminal activities by analysing human behaviour in real-time:

• London CCTV Systems: Use AI to flag individuals acting suspiciously in public spaces, allowing law enforcement to intervene before crimes occur.

• Middle Eastern Airports: AI analyses travellers’ behaviours for signs of stress, anxiety, or aggression—indicators of potential criminal intent.

10. Emergency Response Support

AI supports law enforcement during emergencies by analysing data from multiple sources:

• Houston during Hurricane Harvey: AI-driven analytics were used to coordinate rescue operations, saving countless lives.

• 911 Dispatch Systems: AI helps prioritize calls based on the severity of the situation, significantly improving response times.

Conclusion

AI has significantly transformed crime prevention and detection, offering advanced tools for law enforcement. While the benefits are clear, challenges such as privacy concerns, bias, and ethical use must be addressed. With continued innovation and careful regulation, AI has the potential to make crime prevention more efficient and fair across the globe.

References

1. Emerj Artificial Intelligence Research, "AI for Crime Prevention," www.emerj.com

2. Europol, "AI in Cybercrime and Law Enforcement," www.europol.europa.eu

3. AI Policing, "AI Ethics and Predictive Policing," www.aipolicing.org