Following up on part 1 and part 2 in our series on AI regulation in identity verification (IDV), we turn our attention to the future. The rapid pace of technological advancement in AI and biometrics, coupled with growing privacy concerns, suggests that the regulatory landscape will continue to evolve.
For identity verification leaders, anticipating these changes and positioning their organizations accordingly will be crucial for long-term success.
In this final installment, we will touch on anticipated key areas of regulatory focus in AI and biometric regulation—pulling insights gained from our previous blogs—and provide strategic recommendations for C-suite executives. We will also discuss the role that identity verification providers can play in shaping future regulations.
Key areas of focus for regulators
Algorithmic bias & fairness
Regulators are increasingly concerned about the potential for AI systems to perpetuate or exacerbate existing biases:
- Testing & auditing: Expect requirements for regular testing and auditing of AI systems for bias, particularly in high-stakes applications like identity verification.
- Diverse training data: Regulations may mandate the use of diverse and representative datasets in training AI models.
- Fairness metrics: Standardized fairness metrics and thresholds may be established to ensure consistent evaluation across different AI systems.
Data protection & user consent
As biometric data becomes more prevalent in identity verification, regulators are likely to strengthen data protection and consent requirements:
- Explicit consent: More jurisdictions may require explicit, informed consent before collecting biometric data, similar to BIPA’s requirements, specifically regarding the use of AI-generated systems.
- Data minimization: Expect stricter rules on data collection, requiring companies to collect only the minimum necessary biometric data for the intended purpose.
- Right to deletion: Regulations may expand individuals’ rights to have their biometric data deleted upon request.
Transparency & explainability in AI systems
The “black box” nature of some AI systems is a growing concern for regulators:
- Algorithmic impact assessments: Companies may be required to conduct and publish assessments of their AI systems’ potential impacts.
- Explainable AI: Regulations could mandate the use of interpretable AI models in high-stakes decisions, including identity verification.
- User notifications: Requirements for clear, understandable notifications to users when AI systems are being used to make decisions about them.
Strategic recommendations for C-suite executives
Proactive compliance strategies
- Develop a compliance roadmap: Create a comprehensive plan that anticipates future regulations and sets a timeline for implementation of necessary changes.
- Cross-functional compliance teams: Establish teams that include legal, technical, and business stakeholders to ensure a holistic approach to compliance.
- Regular risk assessments: Conduct periodic assessments of your AI and biometric systems to identify potential compliance gaps or risks.
Investing in privacy-enhancing technologies
- Federated learning: Explore technologies that allow AI models to be trained on distributed datasets without centralizing sensitive biometric data.
- Homomorphic encryption: Invest in encryption technologies that allow computations on encrypted data, enhancing privacy in identity verification processes.
- Differential privacy: Implement techniques that add noise to datasets or model outputs to protect individual privacy while maintaining overall utility.
Building Trust Through Transparency
- Clear communication: Develop easily understandable privacy policies and user interfaces that clearly explain how biometric data is collected, used, and protected.
- Voluntary disclosures: Consider publishing transparency reports that go beyond regulatory requirements, demonstrating a commitment to ethical AI use.
- User control: Provide users with granular control over their biometric data, including easy-to-use options for consent, access, and deletion.\
The role of IDV in shaping future regulations
As key stakeholders in the AI and biometrics space, identity verification providers have an opportunity—and arguably a responsibility—to help shape future regulations:
- Industry collaborations: Participate in industry associations and working groups to develop best practices and standards that could inform future regulations.
- Engagement with policymakers: Proactively engage with legislators and regulators to provide expertise and perspective on the practical implications of proposed regulations.
- Public education: Contribute to public understanding of AI and biometrics in identity verification, helping to create a more informed discourse around regulation.
- Research partnerships: Collaborate with academic institutions on research into ethical AI and privacy-enhancing technologies, demonstrating industry commitment to responsible innovation.
Positioning your company for success
AI regulation in identity verification will face increased scrutiny in the coming years, with stricter requirements for privacy and fairness emerging across federal, state, and international jurisdictions. While these changes create new challenges, they also offer companies a chance to stand out and build credibility with their customers and regulators.
Companies that prepare for new regulations, invest in privacy protection, and take initiative on compliance will do more than just survive—they will lead their industries. Success will come to organizations that see regulations not as red tape, but as proof of their commitment to using AI responsibly and protecting user privacy.
The core purpose of these regulations remains clear: ensuring AI and biometric technologies serve society while safeguarding individual rights. Companies that connect their mission to these broader goals will gain lasting advantages as regulations tighten.
The road ahead isn’t simple, but those who get it right will earn significant rewards—stronger customer relationships, better standing with regulators, and sustained business growth. Tomorrow’s identity verification leaders won’t just create innovative technology; they’ll use it ethically and responsibly.
About the post:
Images and videos are generative AI-created. Prompt: Ancient oracle with weathered face and silver hair, peering intently into a glowing crystal ball, digital code and data streams swirling inside like galaxies, cybernetic patterns, floating binary numbers, holographic UI elements, volumetric lighting, intricate details, cinematic lighting, hyperrealistic. Tools: Midjourney, Luma.
About the author:
Terry Brenner is the Head of Legal, Risk, and Compliance for IDVerse Americas. He oversees the company’s foray into this market, heeding to the sensitivities around data protection, inclusivity, biometrics, and privacy. With over two decades of legal experience, Brenner has served in a variety of roles across a diverse range of sectors.
