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Navigating NIST guidelines for AI and biometric technology

Navigating NIST guidelines for AI and biometric technology

By Eduardo Azanza, CEO of Veridas

From the steam-powered First Industrial Revolution to the digitalization and automation of Industry 4.0, our modern world has been continually redefined by a series of rapid advances that have demanded a recalibration of societal norms and practices.

With its breakneck pace and widespread capability for disruption, AI technology fits this pattern of technological upheaval. Its analytical process and ability to mimic human cognition means AI has near-endless potential. In the biometrics field, AI analytics is delivering unparalleled speed and accuracy for verification.

As technology weaves itself into the very fabric of our lives, it brings both profound opportunities and unique challenges that must be navigated with care.

The National Institute of Standards and Technology (NIST) has so far provided some of the best guidelines to help prevent AI technology from trampling over ethical boundaries or compromising security and privacy. The organization has a long history with AI and its intersection with biometrics, dating back to the 1960s with the evaluation of automated fingerprint identification technology.

Here, we explore how these guidelines can help steer the progress of AI and biometric technology in a way that is safe, responsible and beneficial.

Balancing technological progress with ethical considerations

As with previous technological revolutions, there is a constant balancing act where the pursuit of innovation must be balanced against the weight of ethical and safety considerations.

While some might argue that the rigidity of guidelines can hamper the free-flowing river of creativity, guidance from organizations like NIST are not designed to stifle innovation but to provide it with a safe and sustainable conduit. Like the riverbanks that prevent the waters from causing flood but allow them to flow freely, NIST guidelines aim to ensure that the tide of AI advancement doesn’t spill over into territories of misuse or ethical ambiguity.

NIST is particularly focused on the trustworthiness of AI, focusing on systems that are demonstrated to be valid and reliable, safe and secure. Further, it encourages an accountable and transparent approach to the technology, with processes being explainable and interpretable and with harmful bias being effectively managed.

Additionally, NIST also plays a key role in evaluating biometric technology, with different tests for facial, voice, fingerprint, iris and DNA biometric assessments. FRVT 1:1, for example, evaluates facial verification systems using protocols for labeling pairs of images as trustworthy (a match indicating the same person) or imposter (indicating faces of different people). Meanwhile, FRVT 1:N evaluates an identification system’s ability to search for a known person in a database.

The benefits of following NIST

Any company that specializes in biometric solutions seeking to establish itself as a trusted player in the market will significantly bolster its reputation by adhering to NIST guidelines.

By aligning its authentication processes with NIST standards, the company can enhance the security and reliability of its services, thereby strengthening customer trust and loyalty. It’s not merely about fortifying a technical infrastructure but also signaling a commitment to responsible technology application.

These evaluations and guidelines serve as a universal language in the industry, creating a harmonious standard among different players. They allow businesses to speak the same ‘dialect’ of security, fostering a collective commitment to safe and responsible technology application. This collective understanding strengthens intra-industry relations and builds a stronger rapport with the user base, ultimately driving progress on a pathway guided by innovation and ethical integrity.

NIST guidelines also offer a roadmap to organizations, helping them navigate the growing demands for data privacy and security in an increasingly interconnected world. For instance, an organization can leverage these guidelines to identify potential vulnerabilities in their systems, enabling the design of robust security strategies well in advance. This proactive approach can significantly reduce risks and foster a culture of trust and transparency.

In essence, NIST guidelines are more than mere rules to follow. They are strategic tools that allow organizations to bridge the gap between rapid technological progress and the need for ethical, responsible use of AI and biometric technology.

So, what steps must organizations take to ensure they are on the right course?

Aligning with NIST: steps for implementation

All enterprises working with biometric and AI technology should be comprehensively reviewing the NIST standards and understanding their implications for the organization’s practices.

There must be a particular focus on the trustworthiness of AI and biometric technology for its use to be successful. Transparency and accountability are key, coupled with a high degree of security and privacy assurance. There should be a clear understanding of what data and factors are being collected, and how they are being processed, stored and used.

Companies should also follow the technical standards developed by NIST for AI and biometrics, as these evaluations serve as benchmarks. This includes standards for data interchange, image quality and performance testing in the case of biometrics, and standards related to the design, development and use of AI technologies.

As we stand on the brink of an AI-driven world reminiscent of the revolutions of yore, the NIST guidelines offer us a way to harness the potential of this new era while safeguarding against its challenges. They do not curtail innovation but rather provide a safe conduit for it, ensuring technological progress does not come at the cost of ethical boundaries or security standards. And while the landscape of biometric authentication is continuously evolving, the relevance of NIST guidelines remains steadfast, offering organizations a trusted compass to navigate the exciting future of technology.

About the author

Eduardo Azanza is CEO of Veridas.

DISCLAIMER: Biometric Update’s Industry Insights are submitted content. The views expressed in this post are that of the author, and don’t necessarily reflect the views of Biometric Update.

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One Reply to “Navigating NIST guidelines for AI and biometric technology”

  1. NIST has just undergone a renaming of its programs to better clarify the difference between the identity of individuals and the analysis of individuals.

    “[2023-08-18] To align our test programs with the real-world use cases of technology, we have split the FRVT into the FRTE (Face Recognition Technology Evaluation) and FATE (Face Analysis Technology Evaluation) programs. FRTE deals with identity i.e., who is in an image, whereas FATE deals with processing to determine what is in an image. Thus, the PAD, MORPH, Quality, and Age Estimation tracks are part of the FATE activity, and the 1:1, 1:N, and twins programs fall under the FRTE. All existing participation and submission procedures remain unchanged.”

    Therefore programs to measure the accuracy of the Veridas algorithm and other algorithms are now part of FRTE, such as FRTE 1:1 (instead of FRVT 1:1).

    We’ll all get used to the new names…eventually…

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