Team Rangar
Artificial intelligence (AI) excels at creating the "what" (the main face), but it consistently makes mistakes in the "how" and the "where" (the environment, physics, and fine details). Focus on these three "fingerprints" that AI leaves behind.
Implementation of laws that define and severely punish the malicious use of Deepfakes (fraud, extortion, PNCP), establishing clear criminal liability for creators and distributors.
Regulatory proposals that require all content generated or significantly modified by AI to be clearly labeled as "Synthetic" or "AI-generated" to prevent deception.
Creation of agile legal mechanisms that allow victims of identity theft (especially PNCP) to request the immediate removal of content from all platforms.
Development of Artificial Intelligence algorithms specialized in identifying the microscopic "fingerprints" and anomalous patterns that GAN (Generative Adversarial Network) models leave in content. These detectors operate at a pixel scale that the human eye cannot see.
The industry is driving the creation of standards to prove that content is genuine. Systems (such as the C2PA initiative) attach an immutable record to the file certifying who recorded it, when, and with what device. Similarly, invisible digital watermarks guarantee that the content has not been modified or, if it has, indicate which parts are synthetic.
Automated tools implemented by social media platforms to identify and remove harmful deepfake content in a matter of minutes, neutralizing its ability to spread rapidly.
Integrating teaching about Deepfakes and disinformation into formal education to teach people to question the source and think critically about what they see and hear.
Active promotion of the use of fact-checkers and reverse image search tools to assess authenticity before consuming or sharing.
Campaigns that emphasize the ethical impact of sharing a deepfake (even if done without malicious intent), making it clear that the act of sharing is what amplifies the lie.
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