SMART Access & identity 2024

ARTIFICIAL INTELLIGENCE

AI in 21st century identity technologies

An IDEMIA white paper

This is a condensed version of an IDEMIA white paper that discusses the significance of AI in contemporary identity and security technologies.

A rtificial intelligence (AI) the associated challenges. AI technology use cases have become more mainstream as deep learning algorithms help us to solve increasingly complex problems. Applied to the fields of identity and security, these technologies have driven massive progress over the last decade – progress that would not have been possible without human supervision. What AI is… and what it is not AI technologies: separating myths from reality Let us be clear about one important distinction. AI allows a machine to learn on its own, but it cannot train a machine to think on its own. So, what exactly do we mean by has a very real impact on contemporary society, and we have only just begun to reap the benefits; and tackle

intelligence? If we go back to its Latin root, intelligence is the ability to understand, an ability that is unique to humans and inseparable from their capacity to think. As unsettling as the performance of certain recent AI applications may be, we should be careful not to jump to the conclusion that human intelligence and artificial intelligence are one and the same. The term ‘artificial intelligence’ dates back to the 1950s, when experts were captivated by the rapid progress of computers. For decades, what passed for ‘intelligent machines’ were, in fact, elaborate computer programs that enabled computers to perform pre programmed tasks, such as playing chess. Although it was groundbreaking at the time, these computers were still far from being sources of true intelligence – or understanding. Today, AI technologies learn by trawling through reams of data and drawing

conclusions based on recurring patterns. In this way, they provide humans with insights, but they still lack the ability to think – and understand – their own conclusions. In order to learn and draw conclusions, machines use an algorithm (i.e., a step by-step guide) to complete a precise task, within a predefined framework, and to meet a specific need. To be a genuine source of understanding (and intelligence), this learning can only be achieved in partnership with humans – never by machines alone. Ultimately, the true source of intelligence remains human. Human intelligence first understands the problem to be solved and then designs the framework to do this. It is also human intelligence that is subsequently able to draw lessons from the learning process and the findings generated by the machine. In actual fact, artificial intelligence is really an

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