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A Practitioner's Guide to the Responsible Use of Facial Recognition Technology

By Roger Rodriguez BLOG


AI is a driving force behind many law enforcement technologies, especially in video and image analysis tools. And the benefits are many: reducing repetitive tasks and workloads, recognizing patterns, sending alerts of anomalies, and streamlining investigations. You can see AI at work in technologies like object detection, license plate recognition, weapon detection, acoustic gunshot detection, and facial recognition.

Understanding what AI can do is important, and just as important is knowing what AI doesn’t do. Mischaracterizations of the technology might lead one to believe that AI and computerized automation are one and the same. Simply put, AI is NOT the same as automation.

That distinction is clear with Clearview AI’s facial recognition technology, powered by an algorithm that is made smarter and more accurate through the use of machine learning. The algorithm does not automate decision making, but rather puts the onus on a person to analyze image search results and apply best investigative practices. Law enforcement still has to do the investigative work, but you get a big head-start in the form of investigative leads that might take days, months, or even years to uncover otherwise.

Recently, our Co-Founder and CEO published a blog on the steps Clearview AI has taken to ensure the responsible use of facial recognition technology. Those steps include training protocols, advanced AI to achieve >99% accuracy across all demographics in NIST testing [1], and tools within the solution that allow for auditing and reporting at the agency level. To further support this, we developed a recommended five step investigative workflow for law enforcement using facial recognition technology.


As agencies develop policies around facial recognition technology, one key consideration involves how a user of the technology performs and analyzes the results. The following five steps can dramatically improve both the results of the facial recognition technology as well as support an agency’s policy regarding search, subsequent analysis and investigative protocol.