Overcoming the Top Challenges of Digital Evidence Management
- The teams of public safety agencies face significant challenges in managing the complexity of their digital evidence practice.
- These challenges include increased diverse evidence file types, CJIS compliance, and disjointed evidence workflows, reducing efficiency and sapping resources.
- Artificial intelligence can now provide superhuman powers to the teams of public safety agencies to do more with their evidence in a single, secure hub with multiple capabilities.
The digital age has reshaped the public safety landscape in numerous ways, including managing digital evidence. Public safety agencies are awash in data, thanks to the ubiquity of smartphones, body cams, and omnipresent video surveillance. Add to this the pressing demands for the timely release of evidence due to new legislation, and the result is a perfect storm that overwhelms agencies with outdated processes, especially in the face of tightening budgets. In this blog, we’ll look at the three most pressing challenges these teams face with their digital evidence management practice and how emerging artificial intelligence (AI) technologies are pivotal in streamlining many of these processes.
Challenge #1: Managing Record Volume and Diverse File Types
In the era of constant connectivity, smartphones, surveillance systems, and social media platforms are deluging public safety agencies with an unprecedented volume of digital evidence. Files come in many formats, each requiring specific handling, from videos and images to documents and text messages. These files also exist in disparate locations, some on-premise or cloud-based, meaning they are not in a single location where they can easily be accessed and analyzed. Moreover, traditional manual processing is cumbersome and riddled with inefficiencies. And hybrid processes that use a combination of technology and manual processes create gaps that can compromise the success of investigations.
AI is changing that now by automating transcription, facilitating translation, carrying out redaction, finding objects, license plates, people, and key evidence investigators are searching for and tagging files with descriptive metadata. This not only streamlines the sorting and retrieval process but also significantly reduces the burden on investigators who previously had to review and process diverse types of evidence manually. They can now find that “needle in the haystack” within large compilations of evidence, accelerating their ability to surface actionable intelligence that can impact an investigation.
Challenge #2: Maintaining CJIS Compliance
Protecting sensitive data is a paramount concern for public safety agencies, particularly when this data comprises evidence integral to criminal investigations. As custodians of such information, these agencies are attractive targets for cyber threats. Securing evidence management infrastructure is a delicate balance – it must be robust against such threats while facilitating the necessary access for inter-agency investigations.
CJIS Compliance provides a framework to ensure security without sacrificing functionality. Solutions like Veritone’s AI-driven technologies are designed with these compliance requirements, aligning with our AI for Good principles to ensure that safety, security, and compliance are never compromised in developing new AI solutions.
Challenge #3: Disjointed Workflows in Evidence Processing
Evidence processing involves numerous steps, from identifying relevant evidence to redacting sensitive information and tagging for easy retrieval. Traditionally, these tasks might be handled by different software solutions, resulting in a fragmented and inefficient workflow.
By automating the myriad tasks involved in evidence processing, AI-powered systems enable investigators to rapidly pinpoint relevant evidence, transcribe conversations, translate languages, and redact confidential information. All this can now be accomplished within a single, unified platform, drastically reducing the time and resources spent managing evidence.
Using AI to Evolve Digital Evidence Management Practices
Many public safety agencies still need to rely on a patchwork of manual processes and disparate solutions for logging and analyzing digital evidence. This places immense strain on personnel, potentially leading to burnout and errors, and risks missing critical evidence due to inefficiency. Integrating AI into evidence management is revolutionizing how agencies approach their processes.
Veritone Evidence is a cutting-edge AI-powered solution that merges our robust media management technology with our other public safety solutions, creating a CJIS-compliant environment for processing and analyzing evidence. It simplifies access to essential tasks like transcription, translation, redaction, object detection, license detection, facial recognition, and more, all within the same ecosystem.
This isn’t just about technological advancement; it’s about empowering the people behind the scenes. By alleviating the grunt work through AI, you can empower your teams to accomplish more and magnify their impact—it’s AI for the people, by the people. For public safety agencies looking to save time, reduce resource drain, and close more investigations faster, AI can help transform how your teams work, freeing them to focus on more mission-critical tasks rather than becoming buried in repetitive taskwork.