Digital tools are actively reshaping how police conduct investigations, offering faster results, improved collaboration efforts, and greater access to more data than ever before. From video analysis and transcription software to predictive models and facial recognition, artificial intelligence is playing a larger role in modern policing. But as departments increasingly rely on AI, concerns about manipulation, bias, and authenticity are gaining ground.

Law enforcement leaders are facing growing skepticism around whether AI-generated evidence can be trusted in court or even within their own agencies. In response, departments across the country are adopting new practices and technologies to prevent tampering, add transparency, and strengthen confidence in digital evidence.

AI Tools Gaining Ground in Investigations

Law enforcement agencies have increasingly turned to AI to support investigations ranging from fraud and violent crime to missing persons cases and organized networks. 

Technologies that are driven by AI, including real-time crime analysis, enhanced video processing, predictive policing, and facial recognition, are speeding up the investigative process and helping departments make connections that would be difficult for analysts working alone. 

Automatic transcription tools can process hours of audio in minutes, while video analysis software identifies patterns, anomalies, and people far faster than human reviewers. These capabilities are improving response times, uncovering new leads, and providing investigators with a more detailed understanding of cases in less time.

Digital interview and transcription platforms are a prime example. These systems automatically transcribe video interviews with support for dozens of languages, allow for real-time translation, and create searchable, time-coded records. 

Investigators can bookmark and annotate interviews, invite silent observers, and share interviews securely across departments. Built-in audit trails, encryption, and blockchain-based authenticity verification add another layer of integrity. 

These features are making interviews easier to conduct, faster to analyze, and harder to manipulate. As a result, they’re rapidly being adopted by agencies to reduce operational costs, cut investigation times, and improve evidentiary outcomes.

Growing Doubts About Authenticity and Bias

While AI opens the door to faster and more comprehensive investigations, it also introduces a new set of concerns. Among the most prominent, is how it can be misused to distort information or systems. 

Investigators and prosecutors worry about deepfakes, adversarial attacks on AI systems, and algorithmic bias leading to false positives or unreliable conclusions. These concerns have a direct impact on courtroom proceedings, where evidence generated or supported by AI is increasingly under scrutiny.

Deepfakes, in particular, present a distinct challenge for law enforcement. AI-generated video or audio content that mimics real individuals can be used to spread disinformation, damage reputations, or mislead investigators. 

Machine learning is fueling a new wave of smarter, harder-to-detect scams, covering everything from phishing emails to fake audio. In some cases, departments have had to verify whether an audio or video recording used in an investigation was manipulated before it could be introduced as evidence.

Bias in AI algorithms is another concern, especially in tools used for predictive policing or facial recognition. Historical crime data can reflect systemic issues, and feeding biased data into AI systems may lead to unjust profiling or over-policing in certain communities. 

Facial recognition technology has also faced accuracy concerns, particularly in cases involving non-white individuals. Public backlash around the use of these tools has led to reduced trust in law enforcement, with some cities choosing to pause or ban facial recognition programs altogether.

Building Trust Through Transparency and Security

Agencies are responding to the aforementioned concerns with a mix of technology, policy, and community engagement. Newer digital evidence management platforms incorporate tamper-evident seals that leverage blockchain technology. 

If any edits are made to a file, the system immediately flags the change; every change and access point is logged in an audit trail, creating far greater accountability. These features provide documentation to support the authenticity of evidence, offering reassurance during both internal reviews and court proceedings.

Explainable AI is becoming a priority for departments deploying machine learning tools. Unlike black-box algorithms that provide results without context, explainable systems reveal how decisions were made, what data influenced them, and what weight was given to each factor.

Training is another focus area to keep in mind, as law enforcement personnel are being trained on the capabilities and limitations of AI tools, helping prevent overreliance or misuse. 

Investigators are learning how to evaluate AI-assisted findings, cross-check conclusions, and document how AI influenced a case. Engaging in ongoing education helps agencies stay ahead of emerging risks while building internal confidence in the tools they use.

Proactive Steps to Prevent AI Misuse

To protect against AI tampering, many departments are adopting more rigorous vetting processes when selecting vendors. 

Technology providers must disclose how their algorithms are developed, what datasets are used for training, and whether their models have been tested for bias. Agencies are seeking tools that support full documentation of algorithmic decisions, scalability for high-volume environments, and secure integration with existing systems.

Departments across the country are also investing in counter-AI capabilities. Just as criminals are leveraging AI to create deepfakes or evade detection, law enforcement is working with developers to build detection tools that flag synthetic media and manipulated files. 

These countermeasures are essential for verifying the legitimacy of evidence and identifying when bad actors are attempting to mislead investigators. As agencies embrace more digital tools in their investigative workflows, they’re under increasing pressure to prove that these tools produce accurate, authentic, and legally admissible results. 

Maintaining clear chain-of-custody records, using technologies that automatically log every action taken on a file, and keeping a distinct separation between human and AI decision-making at all times are all part of a broader effort to protect the integrity of modern investigations.

Preventing AI Tampering For Reliable Investigations

At CPI OpenFox, we’ve spent decades building technology solutions that law enforcement professionals can rely on. 

Our CPI OpenFox suite was built specifically for the criminal justice community, combining advanced capabilities, including automatic transcription, tamper-evident file protection, real-time translation, and seamless collaboration, into one cost-effective platform. We understand what’s at stake and design our systems to support the integrity of your investigations from the first interview through to court-ready evidence.

If your agency is evaluating how to move forward with AI-driven tools or digital case management, we’re ready to help. Let’s connect and discuss how your department can better protect evidence, accelerate active investigations, and strengthen public trust. Call us at 1-(630)-547-3679, email sales@openfox.com, leverage our online contact form, or schedule a consultation online today.