Creating Synthetic Human-level Intelligence: Meet the ‘Experts’ of Tomorrow

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Everybody loves talking about artificial intelligence, but few people realize how close current analytical approaches are to recreating human-level intelligence (at least in specific situations).

Situational artificial intelligence, or expert systems, are used today to prescriptively answer queries and provide knowledge to consumers. In fact, you and I engage with expert systems every time we talk to automated support on the phone; and until word 2003, Microsoft featured Clippy.

As technology has progressed, most expert systems have remained static; however, with the ubiquity of computing power and the “race to the bottom” in the cloud market, more and more firms will be considering implementing expert systems to replace knowledge lost by their retiring personnel. Indeed, 10,000 baby boomers will hit age 65 per day over the next 19 years, according to Pew Research. The knowledge lost from the workforce will be truly massive.

How will the market compensate for this loss of human intelligence and experience from the workforce? By automating systems to recreate human-level intelligence.

WHAT THE ‘EXPERTS’ LOOK LIKE TODAY
Today, expert systems are cutting edge (when implemented properly), and can go viral regardless of real-world impact. Take, for examples, Google’s work on autonomous cars, and their expert system that was created for curating headlines and news; or Microsoft’s creation of how-old.net, an expert system for estimating age based on pictures, which went viral after being featured in Joseph Sirosh’s keynote.

There’s a host of other unique applications currently in play and traditional businesses are truly beginning to see the benefits of implementing these expert systems.

So what will the future entail? You’re going to start needing to thank companies for recording your phone conversations, because your experience will get better when you need to call support as more information is recorded, analyzed, and implemented. In fact, such support-line calls will begin to impact product roadmaps, decision-making, and potentially even corporate strategies.

Siri, Alexa, Cortana, and Watson will become increasingly functional as control interfaces for computers and other devices. More often, they will anticipate the information that you need before you turn to them to look it up.

Of course, more expert systems will be created that we can’t really imagine yet, and what does this mean for businesses?

BUSINESS IMPLICATIONS
More and more firms will begin to leverage their data to produce expert systems that will differentiate, revolutionize, and provide a competitive advantage. We will see a new surge in data mining. A few companies will specialize in the creation of these systems, and many will implement them for core business practices. But of course, some firms will refuse to change, and continue using human infrastructure.

Ultimately, this technology has great potential to enhance the power of knowledge of workers, but it can also reduce the value of human labor. If an automated car can drive as well as a cab, what does that mean for the cabbie?

In any case, one thing is clear: Companies that decide to invest now in these systems and technologies will see a long-term yield as they differentiate to extract value from their data.