How Artificial Intelligence Augments Human Intelligence

Here's how artificial and human intelligences work together augment cognitive performances.

AI augmentation is "a human-centered partnership model of people and AI working together to enhance cognitive performance," as defined by research and advisory company Gartner. It is, most of the time, simply called intelligence augmentation (IA).

Intelligence augmentation is the largest type of AI today


While Artificial General Intelligence (AGI, when machines can perform all human cognitive tasks) is still some way into the future, AI's current stage of development is already powering many forms of IA. According to Gartner, IA is mostly creating value in the customer experience sector, reducing mistakes and fostering personalisation. IA is also at work in activities where automation is already generalised: it entails assistants in the office, collaborative robots in factories, semi-autonomous driving systems on the road, machine learning-based diagnoses in healthcare, farming robots and crop optimisation technologies in the fields, among others. In all these areas, artificial intelligence works hand in hand with human intelligence, effectively augmenting it. According to Gartner, AI augmentation will be the "largest type of AI by business value-add": by 2021, it will create $2.9 trillion of business value.

"Winning with AI"


Augmentation is not merely assistance: the artificial intelligence that works with us relieve us of boring or unsafe tasks, but they also learn from us, thus becoming increasingly personalised and making us better at the parts of our jobs that have the most added-value. In fact, talking about IA rather than AI may seem like a semantical refinement, but it has its importance:

"The excitement about AI (...) misses a crucial point," says Svetlana Sicular, research vice president at Gartner. "The goal of AI should be to empower humans to be better, smarter and happier, not to create a 'machine world' for its own sake.

This philosophy is a different way of looking at AI's purpose, which should inform the way we develop it: IA, then, is "a design approach to winning with AI."

 

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