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What Lawyers Need to Know about Deepfake Technology

February 02, 2025 (5 min read)

By: Bijan Ghom, Saxton & Stump

This article addresses existing deepfake technology and covers topics such as the available platforms to both create and detect deepfakes and the best practices for dealing with deepfakes in your case. The following is a summary of a more comprehensive practice note included in Lexis Practical Guidance.

This summary discusses the implications of deepfake technology for lawyers, emphasizing the need for legal professionals to understand and address the challenges posed by deepfakes in legal proceedings. Deepfakes are sophisticated forgeries that can convincingly mimic real people and events, making them difficult to detect and potentially impactful in court cases.

Deepfake Creation Tools

The term “deepfake” typically refers to images, videos, or audio of real people that are edited or manufactured using artificial intelligence. Examples of various platforms used to create video and image deepfakes, include Synthesia, Zao, DeepFaceLab, FaceApp, and Avatarify for video and image manipulation.  For audio deepfakes, examples include Descript, Resemble AI, and VoiceAI. These tools are often marketed as user-friendly and require minimal technical skills, posing a risk of misuse in legal contexts.

Deepfake Detection Tools

Understanding the basic mechanics underlying deepfake technology is the first step to defending against them. Like any scientific or specialized area, a basic understanding of the landscape will allow you to ask the right questions of the parties, witnesses, and experts, and then use the responsive information favorably.

Detection methods are discussed in more depth in the full practice note and include analyzing flaws in deepfakes, examining metadata, and using advanced technologies like deep learning, biometric analysis, and digital forensic techniques. Examples of detection technologies include Sensity AI, FaceForensics++, and Intel's FakeCatcher.

Best Practices for Evidence Collection and Discovery

Legal professionals to be vigilant in collecting and preserving evidence to counter deepfakes. This includes monitoring metadata, identifying visual inconsistencies, and securing corroborating evidence. Lawyers should also be prepared to work with forensic experts and use detection tools to assess questionable evidence.

The above information is a summary of a more comprehensive article included in Practical Guidance. Customers may view the complete article by following this link.

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Bijan Ghom is senior counsel at Saxton & Stump. He handles commercial litigation, business and corporate law, intellectual property, and trusts and estates litigation. A former business owner with a master’s degree in business administration, he continually works with business clients to assist with litigation and intellectual property. He brings his experience founding and selling a number of businesses to advising his clients on protecting and monetizing intellectual property assets. He is also a strategist with Palq IP, an IP strategy firm and strategic partner of Saxton & Stump.

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Sources

Scott v. Harris, 550 U.S. 372, 378–81 (2007), finding summary judgment should be granted when a video shows the plaintiff's "version of events is so utterly discredited by the [video evidence] that no reasonable jury could have believed him."

United States v. Watson, 483 F.3d 828 (D.C. 2007).

Karen Martin Campbell, Roll Tape—Admissibility of Videotape Evidence in the Courtroom, 26 U. Mem. L. Rev. 1445, 1447 (1996). Studies show that jurors are 650% more likely to retain information when they hear oral testimony coupled with video testimony than those who only hear oral testimony.

About Synthesia - Read our story here.

Download ZAO.

DeepFaceLab 2.0.

About Us · FaceApp.

Avatarify - Bring your photos to life.

About Descript.

Resemble AI - The All-in-One AI Voice Platform.

We’re Building the Future of Voice Technology - Voice.ai.

Sensity AI: Best All-In-One Deepfake Detection.

GitHub - ondyari/FaceForensics: Github of the FaceForensics dataset.

Shruti Agarwal, Hany Farid, Ohad Fried Maneesh Agrawala, Detecting Deep-Fake Videos From Phoneme-Viseme Mismatches, CVPR Workshop Paper (2020).

Intel Introduces Real-Time Deepfake Detector (Nov. 14, 2022).

David Salazar, How Intel Putting its, AI-optimized Processors to Work Detecting Deepfakes. Fast Company (Oct. 3, 2023).

Amped Authenticate - Photo and Video Analysis and Tampering Detection.

Setting the Standard for Image and Video Forensics, Amped Software.

Privacy - Pindrop.

OriginTrail.

Discover how creators can use Content Credentials to obtain proper recognition and promote transparency in the content creation process.

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