Biometrics: We Optimized for Convenience. We Forgot About Privacy.

Facial biometrics have become one of the most widely used and recognized biometric modalities, second only to fingerprint verification. Today, face scanning is part of everyday life for most people — unlocking your phone with Face ID, entering your condo building, moving through TSA, CLEAR, or Global Entry. It has become so normalized that we rarely think about it.

What people often forget is how recently facial biometrics became mainstream. While the technology has existed for decades, it was not until the mid-2010s that it entered everyday consumer use. Apple acquired the underlying technology in 2014, and by 2017 we had moved from Touch ID to Face ID. Shortly after, facial biometrics began rolling out more visibly in consumer-facing environments like airports and access control.

The reason facial biometrics took off is simple: they are easy, fast, touchless, and convenient. For a long time, that convenience outweighed everything else.

The Privacy Problem

But over the past decade, we have become more aware and more informed. Facial biometrics are also the most invasive modality. Your face is public by default — constantly exposed, widely shared online, and easy to capture without consent. Facial data is one of the most widely monetized forms of biometric information in existence. Once it is compromised, there is no way to change it.

As a result, there is growing user fatigue. Being repeatedly forced to authenticate with the most exposed part of your identity is something people are starting to question.

The rise of generative AI and deepfakes has only accelerated this concern. Facial biometrics are now easier to weaponize and harder to trust in isolation. When security weakens and privacy erodes at the same time, the model starts to break.

Why We’re Stuck

So why do we continue to prioritize facial biometrics? The short answer is momentum and money. Tens of billions of dollars have been invested into facial recognition. The market today sits roughly in the $8–10 billion range and is projected to grow north of $30 billion over the next decade. Changing embedded systems is slow, expensive, and threatening to existing business models.

But user interests are not aligned with that inertia. People care about convenience, privacy, and not having their identity constantly extracted and monetized.

Palm Verification Changes the Equation

Palm biometrics make it possible to prove liveness and uniqueness without relying on the most public identifier a person has. Unlike faces, palms are not passively exposed online. They are not widely scraped, shared, or monetized — which immediately reduces the attack surface.

The advantage becomes obvious in the numbers:

• Using a single palm, VeryAI operates at a false acceptance rate of roughly 1 in 10 million (1 × 10⁻⁷), using only a standard camera
• For context, Apple Face ID sits closer to 1 × 10⁻⁶ and depends on dedicated infrared depth hardware
• With dual-palm enrollment and multiple scans per palm, VeryAI reaches a false acceptance rate of approximately 2.5 × 10⁻¹⁴ — sufficient for global-scale identity

To reliably guarantee uniqueness across a global population of roughly 8.1 billion people, a biometric system must operate below a false acceptance rate of approximately 1.2 × 10⁻¹⁰. Most biometric systems never reach that threshold without sacrificing usability.

Resilient by Design

Generative AI has made faces and voices trivial to replicate. High-quality source material already exists everywhere online. Palms do not share that exposure. The lack of publicly available palm data makes synthetic attacks far more difficult, especially when combined with liveness signals derived from motion, depth, and photometric cues.

VeryAI’s hardware-free palm scanning delivers this level of performance on any device with a camera. No specialized sensors. No added friction. Just a more private and resilient way to confirm that a real human is present.

The Future of Identity

As digital environments become increasingly synthetic, authentication systems cannot rely on exposed identity signals. Palm verification offers a path forward that scales globally, resists AI-driven spoofing, and preserves privacy by design rather than as an afterthought.

The systems we build next will quietly define how people move through the world — whether they feel watched or respected, whether participation feels seamless or extractive, whether proving you are real feels natural or invasive.

Biometrics are not going away, but the defaults we choose matter. The goal is not to collect more data, but to ask for less, while still getting stronger guarantees.

The future of identity will belong to systems that people do not have to think about — systems that work at global scale and earn trust by design rather than demand it.