Synthetic media generated by artificial intelligence, commonly known as deepfakes, are becoming increasingly integrated into business operations, offering benefits in areas like marketing and customer service. However, this growing adoption is shadowed by significant ethical questions about authenticity, consent, and the potential for misuse. The technology’s capacity to create realistic but fabricated video and audio content has sparked a debate that pits the drive for enterprise innovation against the fundamental rights of individuals, particularly in the entertainment industry where the likenesses of performers are being replicated without permission.
The core of the issue lies in the machine learning algorithms that power deepfake technology. These systems are trained on vast datasets of real human performances, images, and voices, often using copyrighted material without compensation or consent, to generate new, synthetic content. This has led to legal and ethical challenges from creators and performers. The controversy has been brought into sharp focus by figures like Zelda Williams, daughter of the late actor Robin Williams, who has spoken out against the creation of AI-generated videos of her father, calling the practice “personally disturbing”. Her stance highlights a growing resistance from those who find themselves unwilling subjects of digital recreations, forcing a confrontation between technological capability and personal privacy.
Corporate Adoption and Applications
Despite the ethical concerns, deepfake technology is being explored and adopted by businesses for a variety of legitimate and constructive purposes. One of the most significant applications is in corporate training and development. Companies can create cost-effective and scalable training materials in multiple languages using AI-generated avatars, eliminating the need to hire numerous actors. For example, a global franchise could produce a single training video and then use deepfake technology to dub it into dozens of languages, ensuring consistent messaging across its international workforce.
In the realm of marketing and advertising, deepfakes offer new avenues for personalized customer experiences. Brands can create interactive campaigns featuring digital spokespeople or allow customers to virtually “try on” products. The technology can also be used to create synthetic data sets for training other AI and machine learning models, which is particularly useful in scenarios where real-world data is scarce or sensitive. For instance, in healthcare, synthetic data can be used to train diagnostic AI without compromising patient privacy. Furthermore, deepfake technology can be used to improve accessibility, with applications that can narrate the world for the visually impaired.
The Entertainment Industry as a Flashpoint
The entertainment industry has become a major battleground in the deepfake debate, with actors and unions raising alarms about the unauthorized use of their likenesses. The creation of “AI actors,” such as Tilly Norwood, has been met with strong opposition from organizations like SAG-AFTRA, the union representing American actors. The union argues that such creations are not actors but computer-generated characters trained on the work of human performers without their consent. This sentiment is echoed by actors like Emily Blunt, who has publicly expressed her fear that the technology diminishes the human connection that is central to performance art.
The case of Zelda Williams and the AI-generated videos of her late father, Robin Williams, has brought a deeply personal dimension to the debate. She has described the experience of seeing these deepfakes as “maddening” and a “disgusting” misuse of her father’s legacy. Her objections underscore the emotional and ethical toll that unregulated deepfake technology can take on individuals and their families, particularly when it involves deceased individuals who cannot consent to the use of their image and voice. This has sparked a broader conversation about digital rights and the ownership of one’s persona, even after death.
Security Risks and Malicious Uses
While some enterprises are leveraging deepfakes for legitimate purposes, the technology also presents a significant and growing threat in the hands of malicious actors. Cybercriminals are increasingly using deepfakes to perpetrate sophisticated fraud and social engineering schemes. One of the most notable examples involved a UK-based energy firm where an executive was tricked into transferring a large sum of money after receiving a phone call from a deepfaked voice that convincingly mimicked the company’s CEO. This incident highlights the potential for deepfakes to bypass traditional security measures by exploiting human trust.
The risks extend beyond financial fraud. Deepfakes can be used for corporate espionage, with fabricated videos of executives being used to manipulate stock prices or deceive employees into revealing sensitive information. They can also be used to inflict significant reputational damage on a company or its leaders by creating and disseminating false and damaging content. The increasing availability of deepfake creation tools means that these attacks are no longer theoretical and can be executed by individuals with limited technical expertise, making them a serious concern for businesses of all sizes.
The Unpaved Road of Regulation
The rapid advancement of deepfake technology has far outpaced the development of legal and regulatory frameworks to govern its use. This has created a significant regulatory vacuum, leaving businesses and individuals with little guidance or protection. While some regions have begun to address the issue, there is no global standard for regulating deepfakes. The European Union’s AI Act, which came into force in 2024, includes provisions requiring the disclosure of synthetic media, but the specifics of its implementation are still being worked out. In the United States, some states have enacted personality rights legislation, but these laws are not uniform and do not cover all potential uses of deepfakes.
This lack of clear regulation creates uncertainty for businesses that want to use deepfake technology ethically. For example, there are no firm rules on whether customer service operations must disclose when a customer is interacting with an AI-generated voice. While some social media platforms have started to label AI-generated content, these policies are not consistently applied, and detection technologies often struggle to keep up with the pace of innovation in deepfake generation. This leaves the door open for misuse and makes it difficult for users to distinguish between real and synthetic content, further complicating the ethical landscape.
