It’s Fake, Until It Isn’t
One of the oldest principles in policing is that what is seen and heard (photos, video, audio) can serve as reliable evidence. That assumption is now under sustained pressure. The threat does not come from criminals with new tricks, but from a deeper shift in how digital reality can be constructed and manipulated.
Tools that once recorded events truthfully can now manufacture convincing falsehoods. AI can generate fake images, clone voices in real time, and simulate entire events that never happened. The greater danger is not just the existence of fakes, but the doubt they cast over everything that IS real. When any image, recording or file can be questioned, trust in the genuine begins to collapse.
This is already happening. Fabricated media has been used to influence public opinion, damage reputations, and undermine prosecutions. The pace at which disinformation spreads often outstrips the ability to verify or correct it. In a digital environment where perception is easily manipulated, traditional evidence loses its authority.
From Detection to Provenance
Efforts to detect synthetic media are necessary, but not sufficient. AI detection tools rely on technical signatures that vanish as models evolve. This is a temporary defence. A sustainable solution must prove that a file is authentic, not merely suggest that it might not be fake.
This is the logic behind a growing number of international initiatives. The Content Authenticity Initiative (CAI), the open C2PA standard, and technologies from firms such as Truepic, Serelay, Amber Authenticate and others are built around the principle of cryptographic provenance. These systems embed digital signatures and hashes at the point of capture, creating an unbroken chain of integrity that can be verified independently.
This is not an arms race between fakers and detectors. It is a shift toward designing authenticity into the evidence from the start.
Steps Law Enforcement Should Take
Many of the technologies already exist. What is needed now is structured adoption across police forces, judicial systems, and public interfaces. That means moving from pilot projects to operational standards.
- Trusted capture hardware Devices used in the field, including body-worn cameras, drones, and mobile phones, must include secure chips capable of hashing and signing data at the point of capture. Every image or audio file should carry a unique cryptographic fingerprint from the moment it is created.
- Stream-level signing For live feeds or long recordings, the file as a whole is not enough. Each frame, audio segment or data packet should be signed and linked in sequence. This protects against selective editing and enables real-time verification.
- Immutable public anchoring The content itself does not need to be made public, but the cryptographic proofs should be. Blockchain or other ledger technologies can provide a time-stamped public record of when and how a file was created. Anyone should be able to verify its integrity without accessing its contents.
- Integrated digital evidence systems Digital Evidence Management Systems (DEMS) must evolve to include the cryptographic history of files. Several national police forces are already running pilots in this direction. Scaling these systems will require both technical updates and procedural changes.
- Public verification tools Several interfaces already exist that allow citizens, journalists and lawyers to drag and drop a file into a browser and check its authenticity. These tools should be made more visible and integrated into legal and public workflows. Open verification is what protects trust.
- Legal and procedural alignment Courts must recognise cryptographic verification as valid proof of integrity. Officers, analysts and legal professionals need training in how to handle, explain and trust this data. This is not just a technical issue but an institutional one.
Prepare for What Comes Next
The threat is evolving. AI can now generate live video and audio that responds to real-time inputs. We are on the edge of falsified emergency calls, fake live bodycam footage, and altered interviews. Verification after the fact will not be enough. We need real-time, tamper-proof logging of every captured signal from the start of transmission.
Some law enforcement agencies are already testing this. These systems must become normal, not exceptional.
Trust in Verification, Not Perception
Perhaps the greatest shift is cultural. Officers, courts and the public will have to move from relying on what seems real to trusting what can be proven to be real. “I saw it with my own eyes” is no longer good enough. The new question must be: “Can it be verified?”
This will be difficult. It runs against instinct, tradition and emotion. But in an environment shaped by digital manipulation, mathematics may become the only honest witness.
Conclusion
Artificial intelligence has not destroyed truth. It has exposed how fragile our assumptions about truth have become. It forces us to rebuild trust on firmer ground. For law enforcement, this is not optional. It is a necessary step toward restoring public confidence and ensuring justice can function in a digital age.
The path forward is already being mapped by existing initiatives. Our job is to adopt, implement and lead. Not just for our own institutions, but for society’s shared contract with reality.
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