A Systematic Literature Review of Deepfakes in Forensic Science

Organized by: International Forensic Scientist Awards
Website: forensicscientist.org

14th Edition of Forensic Scientist Awards 26-27 September 2025 | Mumbai, India

Introduction

In recent years, deepfakes have emerged as one of the most controversial applications of Artificial Intelligence (AI) and deep learning. While these technologies can be used creatively in entertainment and media, their misuse poses significant risks—especially in the realm of forensic science. This blog post summarizes insights from a systematic literature review that explores the ethical, psychological, legal, and technological dimensions of deepfakes in forensic applications.

What Are Deepfakes?

Deepfakes are AI-generated or manipulated videos, images, and audio recordings designed to look and sound authentic. They are created using deep learning algorithms, particularly Generative Adversarial Networks (GANs). While sometimes used for harmless purposes, deepfakes can also be exploited to spread misinformation, damage reputations, or even fabricate digital evidence.

The Forensic Challenge

In forensic science, digital evidence plays a critical role in investigations and court proceedings. The rise of deepfakes undermines this trust by making it increasingly difficult to distinguish between genuine and manipulated content. This creates an “arms race”:

On one side, developers of deepfake technologies continue to refine their techniques.
On the other side, forensic scientists and AI researchers race to create advanced detection tools.

Key Findings of the Review

The systematic review examined 36 peer-reviewed articles published between 2021 and 2024 across seven academic databases. The findings can be grouped into the following areas:

Technological Progress
- Advances in deepfake detection algorithms show promising results.
- However, no universal or standardized method currently exists for reliable authentication.
Ethical Dilemmas
- The misuse of deepfakes challenges the integrity of justice systems.
- Ethical frameworks are urgently needed to guide the responsible use of forensic technologies.
Psychological and Legal Aspects
- Deepfakes not only manipulate digital content but also influence perception and trust.
- Legal systems face the challenge of adapting existing laws to address AI-driven evidence manipulation.
Future Needs
- Greater interdisciplinary collaboration is essential.
- Forensic science must integrate ethical, technological, and legal approaches to ensure the authenticity of digital evidence.

Why This Matters

The implications of deepfakes extend far beyond digital trickery. In the wrong hands, they can erode public trust, influence criminal investigations, and threaten democratic processes. For forensic science to remain effective in the digital era, it must adapt to these challenges by embracing innovation, collaboration, and ethical responsibility.

Conclusion

Deepfakes are more than just a technological curiosity—they represent a serious threat to forensic integrity. While researchers have made notable strides in detection and analysis, the fight against digital manipulation is far from over. Building robust forensic frameworks, advancing AI detection tools, and embedding ethical safeguards will be crucial steps in preserving trust in digital evidence.

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