Deepfakes and AI: understanding the technology and the stakes for brands
The term “deepfake” (a portmanteau of “deep learning” and “fake”) refers to media content (videos, audio, images) generated or manipulated by artificial intelligence (AI) to make a person appear to do or say something they never did or said, often with stunning realism. The technology underlying Deepfakes and AI is advancing at breakneck speed, making these manipulations increasingly accessible and difficult to detect. While it opens some creative possibilities, it primarily poses a considerable threat regarding disinformation, identity theft, fraud, and reputation, presenting major challenges for individuals, businesses, and society at large.
Technology behind Deepfakes: GANs and diffusion models
The creation of Deepfakes and AI mainly relies on deep learning techniques, particularly Generative Adversarial Networks (GANs) and, more recently, diffusion models. GANs operate with two competing neural networks: a “generator” that creates fake images/videos and a “discriminator” that tries to distinguish fake creations from real ones. Through training, the generator becomes increasingly adept at fooling the discriminator, producing highly realistic results. Diffusion models, on the other hand, learn to reverse a process that gradually adds “noise” (randomness) to an image, allowing them to generate highly coherent and high-quality images from pure noise or guiding text/images. For video deepfakes, these techniques are often combined with facial tracking algorithms to transpose the expressions and movements of one person onto another’s face. AI voice cloning is the audio counterpart, enabling the synchronization of a fake voice with the manipulated video. Increasingly accessible tools, sometimes available online, lower the technical barrier to creating deepfakes.
Risks and threats: disinformation, fraud, and reputational damage
The dangers associated with Deepfakes and AI are multiple and severe.
- Disinformation and political manipulation: Creating fake videos of political figures making inflammatory or compromising statements to influence public opinion or destabilize elections.
- Fraud and social engineering: Using audio or video deepfakes to impersonate a company executive (CEO fraud), a loved one (romance scam), or a bank advisor to obtain confidential information or money transfers.
- Reputational damage and harassment: Creating non-consensual pornographic content (deepfake pornography), humiliating or defamatory videos targeting individuals, including public figures or company employees.
- Identity theft and security: Potentially bypassing biometric authentication systems based on facial or voice recognition.
Detection and combating Deepfakes
The fight against Deepfakes and AI is organized on several fronts but remains a constant challenge against the rapid evolution of generation technologies. Researchers are developing detection algorithms based on analyzing visual or audio micro-artifacts (inconsistencies in blinking, reflections, lip-sync, audio background noise) often left by AI generation processes. However, deepfake generators are also improving to eliminate these artifacts. Other approaches include watermarking authentic content to verify its origin or educating the public to develop critical thinking towards media content. Collaborative initiatives between tech platforms, researchers, and governments (like the Cloudflare and its AI Labyrinth which could potentially integrate analysis tools) are necessary. Specific legal frameworks for deepfakes are also beginning to emerge in some countries, but their enforcement remains complex. Bias in AI can also affect detection tools, potentially making them less effective on certain types of faces or voices.
Brandeploy: protecting the brand in the age of Deepfakes
How can a brand protect itself and react to the threat of deepfakes? Brandeploy offers tools to strengthen reputation management and crisis communication. Firstly, by centralizing all official and validated communication assets (videos, photos, statements), Brandeploy becomes the single source of truth for the company. In the event of a deepfake impersonating the brand or its executives being disseminated, the company can quickly distribute authentic content and official denials stored and approved in Brandeploy through its communication channels. Secondly, the platform manages access and rights, limiting the risk of internal assets being used to create deepfakes. Thirdly, Brandeploy can integrate monitoring and alerting workflows: if suspicious content mentioning the brand is detected, it can be escalated via Brandeploy to the relevant teams (legal, communication, security) for analysis and validation of a coordinated response. By ensuring rigorous management of official content and facilitating rapid and coherent crisis communication, Brandeploy helps brands better defend themselves against reputational damage linked to deepfakes.
The threat of deepfakes is real and growing. Protect your brand by strengthening the management of your official communications and your response capability.
Brandeploy helps you centralize your authentic assets and coordinate your crisis response.
Discover how Brandeploy can contribute to protecting your reputation: request a demo.
