Why specialized artificial intelligence is better, yet largely ignored

The dream of creating an artificial general intelligence has captivated our imagination for generations. Alan Turing, mathematician and computer scientist, was among the first to envision what it would look like to create a sophisticated program that could pass as human a given percentage of the time.

Considering how close today’s ubiquitous digital assistants have come to understanding speech and responding to certain types of inquiries, Turing’s prediction was certainly within the ballpark.

However, Turing’s outlook was fundamentally linear: Throw more time and computing resources at the problem and eventually it will be solved. This line of thinking has persisted to this day.

This type of linear thinking has hindered the development of AI.

You have to wonder, even with all that power now at our disposal, why are Alexa, Siri, Google Assistant and Bixby still not quite right? While we are aware of their intention - to sound as human-like as possible, they, more times than not, fall short.

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Multiple cables connect to powered supercalculator Blade computer units during testing at the Bull SA headquarters in Angers, France, on Monday, June 23, 2014. Thierry Breton, chief executive officer of software maker Atos, is engineering a 620 million-euro ($846 million) bid to acquire Bull, the company he tried to revive two decades ago. Photographer: Balint Porneczi/Bloomberg

To reap the full benefits of AI, there’s an entirely different type of AI we should be exploring, that’s been largely ignored. It’s specialized (or augmented), intelligence systems.

Think of specialized intelligence as the anti-Swiss army knife. A Swiss army knife does a bunch of things okay, but none of them very well. AI will follow the same engineering maxim that all things made or born must follow: You cannot optimize every dimension. You can only have tradeoffs. You can’t have a general multi-purpose unit outperform specialized functions.

Let’s think about what it takes to put cognition into AI...if you consider what it means for a human to be intelligent, the answer is not simple. When the philosophers of the ancient world went about looking for the one property that distinguishes rational man from the irrational animals, they went with this: man is a risible animal. That is, because humans are rational, they can appreciate and tell jokes. They can be creative.

Making a good joke isn’t the end result of a linear process, as if the smarter you are, the funnier you must be. It’s a very specific ability. Some of the greatest minds in science have a reputation for being humorless, while at the same time you wouldn’t want your favorite comedian to be designing rockets!

In creating AI systems, it makes more sense to focus on specialized intelligence. Take financial services, for example. Think of it like Jarvis for your financial advisor, an AI-enabled Iron Man suit that doesn’t replace personal finance expertise, it amplifies it. The human supplies judgment and expertise, while the machine supplies a near-infinite memory capacity and the ability to perform mind-numbingly boring tasks with perfection.

With specialized AI In the medical field, instead of creating a robot medical assistant that makes human doctors obsolete by reasoning like a super intelligent human doctor, you create a system that focuses on a subset of specific tasks a doctor must do. For example, a digital assistant that transcribes the doctor’s diagnosis as he talks to the patient, relieving the paperwork burden to leave the human with more time to see additional patients.

That’s the type of artificial intelligence that’s far more useful today, right now, than chasing the dream of creating general intelligence systems that render humans obsolete. Augmented intelligence systems also have the side benefit of being real, not theoretical.

Of course, the biggest downside to artificial specialized intelligence is that once the idea is popularized, science fiction may never recover. Specialized AI is far too controllable. You know exactly what is going on, and it won’t lead us to a doomsday scenario. So when sci-fi movies create a new stock villain, you’ll know the idea has finally caught on.

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Artificial intelligence Machine learning Data management
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