Unprecedented disagreement has emerged within the global biometrics community regarding the intricate relationship between biometrics and artificial intelligence (AI)
A new paper from the Biometrics Institute, “Members’ Viewpoints: The Relationship Between Biometrics and Artificial Intelligence (AI)” explores the conflicting perspectives gathered throughout 2024 from members and other experts across the globe
This highlights the complex connections between these two rapidly evolving technologies, revealing a landscape of contrasting views within the field.
Opinion between AI and biometrics is divided
The paper highlights significant disparities in member opinions regarding the relationship between biometrics and AI.
Some members argue that biometrics are inherently intertwined with AI, while others emphasise that many biometric applications exist independently.
“Rarely has the biometrics community disagreed on an issue at this level before,” says Isabelle Moeller, CEO of the Biometrics Institute, “This paper reflects the conflicting perspectives of our global community on an evolving topic that is critical technology for biometric success. Understanding the relationship between biometrics and AI is essential for responsible innovation and the development of ethical guidelines for their use.
While ISO definitions for both biometrics and AI exist, other important but sometimes non-aligned definitions are prevalent in the public domain. A diverse range of stakeholders, including major technology corporations, civil society organisations, also seek to define AI. The Biometrics Institute offers its own perspective to address this, and the paper resulted in a new entry for “Artificial Intelligence” in the Institute’s Explanatory Dictionary of Biometrics, providing a resource that reflects these various viewpoints for the benefit of members, policymakers, and the general public.
Bridging the gap: Defining biometrics and AI
Defining biometrics and artificial intelligence (AI) presents significant challenges. Existing definitions, such as those from ISO and some governments, are for some audiences too technical, complex, or inaccessible, affecting broader understanding. The Biometrics Institute’s Explanatory Dictionary aims to bridge this gap by capturing the nuances of these terms, considering both formal definitions and how they are perceived by the public – for example, how someone might explain biometrics or AI to a friend. However, there are no universal definitions of biometrics or AI and public perception of these technologies remains unclear, influenced by often-confusing social and traditional media portrayals that frequently fail to distinguish between different types of biometrics and AI, creating a sense of technological ambiguity.
AI’s impact: Enhancing or endangering biometrics
Determining which biometric applications “have” AI can be challenging, as there are many ways that AI interacts with biometric technologies, from aiding in processing as a threat vector to enhancing security measures and general processes. However, AI also presents potential risks, such as vulnerabilities that could be exploited. As AI becomes increasingly integrated into all aspects of technology, identifying and assessing these risks will become more crucial. Ultimately, the increasing complexity of AI integration may make it difficult to distinguish AI components from other elements within a given system.
The relationship between biometrics and AI: Complex and multifaceted
While some argue that biometrics are inherently intertwined with AI, others emphasise their potential for independent use. The inclusion of AI in a specific biometric system is often determined by the application’s requirements, rather than the type of biometric data used. Furthermore, the role of human operators within biometric systems highlights the ongoing debate surrounding human error versus machine error and the varying levels of acceptance for each. This debate is further complicated by differing legislative and liability frameworks.
Regulation and innovation: Challenges will persist
Existing regulations often conflate these two distinct technologies, particularly in the case of face recognition, where the term “AI” is frequently used interchangeably. This ambiguity can lead to overly broad regulations that may inadvertently restrict the development and deployment of beneficial biometric applications. While concerns regarding the potential impact of remote biometric surveillance on civil liberties are valid, some argue that excessive regulation could stifle innovation and hinder the ability to address pressing societal challenges through the use of cutting-edge technological solutions.
The paper’s key findings provide many more insights into the definitions of biometrics & AI, the impact and influence of AI on biometric processes, the relationship between biometrics and AI and regulatory oversight of biometrics and AI.
Above, image credited to the Biometrics Institute
