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A significant trust gap exists, with 87% of Americans holding businesses responsible for digital privacy but only 34% trusting them to use AI effectively against fraud. Even though 51% of enterprises use AI for cybersecurity and fraud management, only 43% of global customers believe companies are doing it right. Companies need to bridge this trust gap, ensuring their AI-driven security builds confidence. Deepfakes are making this gap wider.
The trust gap affects everything from long-standing customer-business relationships to major elections. Telesign’s 2024 Trust Index sheds light on this growing issue.
Deepfakes and misinformation are fostering distrust among companies, customers, and citizens involved in elections. Once someone is deceived by a deepfake, their trust in online content diminishes, threatening democracy. Social media platforms are flooded with deepfakes, often driven by automated fake accounts, making it hard to distinguish between real and fake content. An example from September 2020 involved Facebook blocking a Chinese network of accounts that posted on geopolitical issues.
Nation-states invest heavily in misinformation to influence elections, aiming to destabilize democracy or create social unrest. The 2024 Annual Threat Assessment of the U.S. Intelligence Community highlights Russia’s use of AI to create deepfakes, even fooling experts. Voters globally are impacted, with 72% fearing AI-generated content undermining elections. In the U.S., 81% of Americans are particularly worried, noting a noticeable presence of AI-generated political ads.
Interestingly, despite their fears, 71% of Americans would trust election outcomes more if AI and machine learning were used to prevent cyberattacks and fraud.
Generative Adversarial Networks (GANs) are at the core of deepfakes’ rising popularity. From rogue attackers to nation-states like Russia, many are using GANs to create highly realistic videos and voice clones. The more authentic the deepfake, the more it impacts trust among customers and voters. GANs are used in phishing, identity theft, and social engineering. For instance, The New York Times offers a quiz to test if readers can distinguish between real and AI-generated images, highlighting how advanced GANs have become.
GANs operate with two neural networks: a generator creating synthetic data and a discriminator evaluating its authenticity. This competition enhances the quality of fake content, making it nearly indistinguishable from the real thing and spreading misinformation quickly via social media and fake accounts.
Protecting trust in an era of deepfakes is critical. Christophe Van de Weyer, CEO of Telesign, emphasizes the importance of AI in safeguarding data integrity and preventing AI-enabled fraud. Telesign uses AI to prevent over 30 million fraudulent messages monthly and protect more than a billion accounts annually. Their Verify API leverages AI for secure transactions and reduced fraud risks.
Telesign’s research shows the importance of robust cyber hygiene, noting that 99% of successful digital intrusions happen when multifactor authentication (MFA) is not enabled. MFA combines what you know, what you have, and biometric factors to enhance security. Companies like Microsoft and GitHub are enforcing MFA to improve security.
Identity-based breaches significantly erode trust. Without a solid identity and access management (IAM) plan, dormant accounts can remain active and vulnerable. Ivanti’s research found that 45% of enterprises believe former employees may still have access to company systems. This is a major oversight that needs addressing.
Telesign’s Trust Index highlights the urgency of getting IAM and MFA right. Customers depend on CISOs and CIOs to make informed decisions about AI/ML for protecting identities and data. As neural networks advance, improving GANs’ ability to create realistic content, focusing on security becomes crucial for any business to prevent breaches and maintain trust in the digital world.