Introduction
Imagine there is a criminal who has committed an offence for which video evidence has been produced by the prosecution. The picture is clear, the sound unmistakable and the sequence makes logical sense. Traditionally, such evidence was seen as being highly reliable or even close to conclusive proof. Yet suppose if it were a deepfake?
The introduction of artificial intelligence-created deepfakes has radically altered one of the most basic tenets of the law, which is the belief that visual and audio evidence is an accurate representation of reality. Courts have always worked under the assumption that evidence, once examined using methods such as cross-examination, could yield the truth. This assumption is, however, based on a further assumption about human capacity for rationality in discerning facts from fiction. Modern psychology questions that assumption. Human perception is biased and fallible due to mental shortcuts used by our cognitive system and people tend to believe the information presented by their senses. In an age when artificial intelligence can create highly realistic images and sounds, these human weaknesses become vulnerabilities.
This article argues that the emergence of deepfakes reveals a critical deficiency in the current laws regarding evidence. With its persistence in basing its rules on antiquated presumptions regarding human cognition, the judicial system may be prone to misinterpreting artificial reality as reality itself. An evaluation of existing laws with consideration for psychological insights becomes a necessity at this point.
Deepfakes and the Growing Reliance on Digital Evidence
Deepfakes are those synthetic media that are produced utilizing artificial intelligence technology and especially utilizing methods based on deep learning, to create realistic but fabricated images, videos or audio recordings. In contrast to classical manipulations, deepfakes cannot be detected just by looking at them because they look quite real.
Modern legal systems have begun to heavily depend on digital evidence, where all kinds of electronic information, CCTV footage, call logs and content from social networks are essential to conducting investigations. In the case of India, the use of such evidence has been legalized as part of the Information Technology Act of 2000 and integrated into the Indian Evidence Act of 1872 (now Bharatiya Sakshya Adhiniyam of 2023 Sections 61 & 62).
Such reliance on digital evidence presumes that digital evidence is inherently reliable and authentic. However, in the context of deepfakes, one must assume that there is no guarantee that any digital information is not deepfake.
Psychological Foundations: Why Humans Are Easily Deceived
The vulnerability of legal systems to deepfakes is rooted not merely in technological sophistication but in human psychology.
a. Visual Credibility Bias: People generally have a tendency to believe their eyes more than any other form of perception. Psychological studies suggest that humans attribute more credibility to information when they visually perceive it as compared to when they hear or read the same information. This “seeing is believing” heuristic is deeply ingrained and often operates unconsciously (Walsh, 2023).
b. Confirmation Bias: People generally understand any information or a situation based on their prior assumptions or beliefs. If a deepfake corresponds to people’s assumptions and beliefs, they are less likely to doubt its credibility.
c. Human Decision-Making Biases: Humans’ decision-making process often includes various heuristics (mental shortcuts rather than deliberate analysis) which, while being effective, significantly decrease their accuracy in many cases (Asana, 2026). In particular, heuristics reduce the accuracy of people’s evaluation of complex situations, such as deepfakes, where media content might be digitally altered.
d. Illusion of Truth Effect: Repeated exposure to an information increases the likelihood of it being perceived as true, regardless of its actual veracity. In the context of deepfakes, repeated circulation of manipulated media can reinforce false beliefs.
Crucially, these cognitive limitations are not confined to common people. Empirical research indicates that even trained professionals, including judges, are susceptible to bias and perceptual error (Olaborede & Meintjes-van der Walt, 2020). The legal system’s reliance on human judgment therefore becomes a structural weakness in the age of synthetic media.
Evidence Law and Its Rationalist Assumptions
Evidence laws in India rest upon the principle that there exists a possibility of obtaining truth through rational methods. Processes like cross-examinations, expert testimonies and document verifications aim to validate pieces of evidence. According to sections 61 and 63 of the Bharatiya Sakshya Adhiniyam 2023, evidential standards of electronic records should be certified before being accepted into evidence (Anvar P.V. v. P.K. Basheer, 2014)
Nevertheless, these standards focus more on issues related to evidentiary admissibility rather than on epistemological considerations. It is assumed that once procedural requirements are met, the court would be able to evaluate the evidence rationally. Such an approach becomes increasingly problematic as deepfakes can bypass standard procedures used in the evaluation of digital records. Even if any doubt arises, humans are simply unable to process the evidence accurately in terms of its authentication.
The Crisis: Structural Failures in the Age of Deepfakes
The interaction between deepfakes and human cognition demonstrates several problems for the legal system:
a. Authenticity Problem: If one can make fake digital evidence believable enough, it loses its value as proof. The court will find it difficult to know if the evidence is authentic or manipulated.
b. Epistemic Instability: The legal process operates under stable assumptions about truth. However, with deepfakes, the truth becomes probabilistic instead of knowable.
c. Evidentiary Burden Misalignment: The emergence of deepfakes leads to a host of questions: Who must prove whether something is real or fake? Making people prove that a piece of digital evidence was manipulated may be too much to ask.
d. Illusion of Judicial Competence: There is a high probability that judges will underestimate their incompetence when evaluating manipulated digital evidence.
Taken together, these problems indicate that the legal process lacks the necessary tools to respond to deepfakes.
Comparative Perspectives and Emerging Responses
Across the globe, legal frameworks have started to respond to the disruptive possibilities offered by deepfakes, especially when the reliability of information is key. In the United States, for example, regulatory discussions and judicial decisions have become increasingly oriented toward the consequences of deepfakes in relation to elections, criminal justice processes and defamation (HALOCK Security Labs, 2026). Problems include doctored videos with the potential to deceive the electorate, as well as fabricated audiovisual materials that might lead juries to be misled and affect judicial outcomes. In the EU, regulations have been developed to categorize and regulate artificial intelligence systems, including those with the capacity to create deepfakes as part of their operations. It appears that legal frameworks have started to realize the disruptive possibilities of deepfakes and their potential to affect legal processes.
Nonetheless, at the same time, it has to be noted that while there is some legal response to the disruptive power of deepfakes, most regulatory approaches remain fragmented and technocentric. Regulatory discussions mostly focus on questions of disclosure and liability.
Towards Reform: Bridging Law and Psychology
Overcoming the challenge posed by deepfakes will necessitate an integrated strategy that cuts across multiple levels. First, at the psychological level, there must be incorporation of knowledge of cognitive biases and perceptual shortcomings into judicial and legal training. Second, legal changes will involve improvements in authentication methods; the shift in the standard of proof in deepfake cases and formulation of evidentiary presumptions for artificial intelligence-generated material. Third, technologically speaking, it would be useful for courts to use AI technology to detect such fakes. However, this must happen in coordination, without which legal changes alone are useless.
Conclusion
Furthermore, deepfakes present a challenge not only to the authenticity of evidence, but to the entire epistemological framework of the law. The law assumes that it is possible for people to see things as they really are and determine what the truth is based on that understanding. Psychology shows that this assumption was, to begin with, overly optimistic at best and wrong at worst.
In a world where even reality can be manipulated through deepfake technology, the law needs to stop relying on human perception and the inherent belief in our ability to see and know the truth. Instead, it should focus on the fact that we now live in a world in which there is nothing obvious about truth, and that our processes for discovering it can all be compromised. This is where psychology comes into play. The future of evidence law will require the integration of knowledge gained from psychological insight.
Reference list:
- Bharatiya Sakshya Adhiniyam, 2023, §§ 61-62 (India).
- Walsh, N. (2023, October 31). Misjudgement: Why we trust what we see vs. what we hear. https://www.psychologytoday.com/us/blog/decisions-that-matter/202310/misjudgement-why-we-trust-what-we-see-vs-what-we-hear
- Asana. (2026). Heuristics: How mental shortcuts help us make decisions. https://asana.com/resources/heuristics
- Olaborede, A., & Meintjes-van der Walt, L. (2020). Cognitive bias affecting decision-making in the legal process. Obiter, 41(4), 805–820.
- Anvar P.V. v. P.K. Basheer, (2014) 10 SCC 473 (India).
- HALOCK Security Labs. (2026). What legislation protects against deepfakes and synthetic media? https://www.halock.com/what-legislation-protects-against-deepfakes-and-synthetic-media/
