AI in Evidence Analysis: Enhancing Investigative Teams

The application of artificial intelligence (AI) in investigations is revolutionizing how evidence is analyzed and managed. AI-driven tools and technologies are streamlining the process, enabling law enforcement agencies to handle evidence with greater speed, accuracy, and efficiency. From digital evidence management to forensic data analysis, AI is transforming traditional methodologies, making it possible to process vast amounts of data in record time while minimizing errors. In this blog, we'll explore the benefits of AI in digital evidence management, key AI technological capabilities, and applications in investigations.

Benefits of AI in digital evidence management

One of the most significant advantages of AI in managing digital evidence is its ability to process large volumes of data quickly and accurately. Investigations often involve reviewing an overwhelming amount of digital evidence from various sources such as social media, surveillance footage, and emails.

AI's capacity to sift through these files and surface data allows investigators to focus on the most critical elements of the case without being bogged down by manual data review processes. By utilizing machine learning algorithms and natural language processing (NLP), AI tools can rapidly extract relevant information, help teams identify patterns, and provide key insights.

In doing so, AI can add another layer of accountability to reduce human error, which can happen more often in manual evidence analysis processes. AI mitigates this risk by automating repetitive tasks and analyzing evidence with consistent precision. Machine learning models trained on large datasets can surface and identify things that may go unnoticed by human analysts. This enhances the accuracy of data analysis and speeds up the investigation process, ultimately leading to more reliable and positive outcomes.

Key AI technologies in investigations

Several AI technologies are at the forefront of automated evidence processing, including machine transcription and translation, automated redaction, person-of-interest tracking across videos, and AI-powered metadata tagging. Here's how each one plays a role in investigations:

• Machine transcription and translation: evidence comes in various formats and might of other languages outside of an investigation team's native tongue. Transcription and translationcan quickly bog down an investigation. Finding a service to transcribe and translate is a task in itself, but once you do, it can take days to get the results. Furthermore, if a large batch of evidence needs this type of processing, it can take even longer. AI can accelerate that process significantly, helping investigators surface evidence that might have otherwise been missed.

• Automated redaction: in many cases, some people might appear within evidence files that need to be redacted. Previously, this would require a time-consuming manual workflow that took valuable resources away from other important tasks. AI can largely automate the redaction process, greatly reducing the time it takes.

• Person-of-interest and vehicle tracking: facial recognition technology falls short in some situations where footage involves crowds of people. There's a time and place to use it, but at the same time, some hesitate due to concerns about protecting one's personally identifiable information (PII). Now, new AI technology that defines humans as objects can help investigators look for key aspects of a potential suspect (such as a logo on a shirt, a type of hat or backpack they are wearing, etc.) to track that person across video files at scale, greatly reducing the time it takes to analyze video evidence. Investigators can also use this same technology to track vehicles across footage.

• AI-powered metadata tagging: when processed with AI, digital evidence creates a ton of data that can be leveraged to help investigators understand what they have on hand. From surfacing only relevant files to finding moments within files with potential case-changing evidence, AI providesautomated evidence processingto provide investigators the insights to find that needle in a haystack.

These capabilities are more than just theoretical. A lot of agencies are already using AI in real-world applications.

Applications of AI in Investigations

AI in forensics and investigations is already being successfully integrated into technology stacks, transforming how cases are handled. For instance, TransPerfect Legal Services, an industry leader in multilingual legal support services,adopted AI capabilities from Veritone to help accelerate eDiscovery, transcription, and translation. In doing so, they were able to help two of their clients reduce their document review size, containing over 500K of multilingual files, by 68%.

We've also worked with state, local, and federal agencies to help improve how they hand media, whether it is evidence for investigations or simply internal files. For instance, the Oregon Police Department, as well as the Escondidoand Lake Stevens Police Departments, have adopted automated redaction capabilities from Veritone. In doing so, they've been able to cut redaction times in half by improving efficiency. In the case of the Lake Stevens Police Department, they also adopted AI transcription to make it easier to analyze what's spoken in video footage.

At the federal level, the U.S. Congress adopted AIto better store, manage, and distribute photos, audio, and video files, transforming its digital asset management. The same principle is applied to digital evidence management practices, which help investigators consolidate and process their digital evidence to better find and share only the most relevant information in a secure environment.

Ethical considerations in responsible AI deployment

As AI plays a larger role in investigations and law enforcement, ethical considerations must remain at the forefront of its deployment. Issues such as bias in AI algorithms, data privacy, and more make it critical for AI leaders to lead with standards that protect people from harm. As legislation continues to play catch up, there are things companies should be doing now. Veritone has created a set of AI for Good principlesthat guide everything we do to ensure our technology is transparent, trustworthy, secure, and compliant. It also empowers humans, such as investigators, to do their jobs even better.

Embracing AI to improve the investigative process

AI holds transformative potential for the future of evidence analysis and law enforcement technology. By enhancing accuracy, reducing human error, and streamlining the investigative process, AI empowers professionals to solve cases more efficiently and effectively. As AI technology continues to evolve, its integration into law enforcement will undoubtedly play a key role in improving public safety while maintaining ethical standards.

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