Name
Closing Panel: Harnessing the Power of AI/ML: Now and in the Future
Date & Time
Wednesday, May 10, 2023, 3:20 PM - 4:20 PM
Description

Law enforcement agencies continue to struggle with collecting and analyzing the volume and variety of data gathered from investigations. To that end, agencies are laying the foundation to apply artificial intelligence and machine learning (AI/ML) solutions, techniques and tools to accelerate analytics that can provide law enforcement with actionable intelligence. AI software can analyze vast quantities of data from video feeds to facial recognition data to digital forensics, as well as identify trends and patterns of behavior much faster than humans. Machine learning then enables the software to draw human-like conclusions and has the potential to help forecast future actions. The data explosion will only increase as emerging 5G broadband technology enables the movement of massive amounts of data at blazing speeds across connected networks and devices. AI/ML will help law enforcement harness and analyze data to make more informed and split-second decisions when lives are at stake.  

However, technical and ethical challenges-from methods of data analysis to algorithm bias to data privacy-can hamper the effective use of AI/ML if the solutions, techniques and tools for law enforcement are not applied in the appropriate manner. This panel will discuss law enforcement professionals’ current use of AI/ML, along with their vision of the future.        

Potential Topics include: 

  • How law enforcement can utilize 5G to deliver more data, the right data, much faster with AI. 
  • What are the data requirements? How can agencies position data for AI/ ML tools to be effective. 
  • How law enforcement can responsibly utilize AI/ML and facial recognition. 
  • How AL/ML is being utilized in other biometrics such as DNA, IRIS and fingerprint searches. 
  • How AI/ML can be utilized to search databases and prioritize data for the user since law enforcement must check multiple databases when searching an identifier.