The future of AI

The future of AI is here—and everywhere

There is a genuine, evidence-based phase shift from artificial intelligence as “cherry-on-top” curiosity to “key ingredient” at leading organizations. Sixty-one percent of respondents to a recent Deloitte Insights report say AI will substantially transform their industry in the next 3-5 years. Furthermore, adoption is significant on a per-organization basis, with 53% of those polled spending more than $20 million during the past year on AI tech and talent. AI’s increasing centrality to business processes, and even strategy, is no longer up for debate.

As with any exponentially accelerating emerging technology, the abundance of news has, however, given way to an even greater abundance of noise. How can you see the forest for the trees?

The key, it would seem, is to peer beneath AI-as-platitude and above the à la carte jargon. To shoot the curl toward the “Goldilocks zone,” where clusters of coherent, high-growth, impactful submovements are both easier and more useful to understand. In this way, we can not only better sense what’s happening, but also make sense of where these movements are likely headed.

Teaching Machines (Not Telling)

Engineers and computer scientists spent decades perfecting computers’ abilities to solve classical math and logic problems. But as it would turn out, a huge set of real-world decision-making isn’t readily framed as a tidy math problem.

Machine learning (ML) earns its paycheck in these kinds of situations: When we’re unable to logically or cost-effectively use math to tell a computer what to do, we can use ML to teach a computer what to do by showing it examples of how it’s been done.

This current AI/ML “Cambrian explosion” is resulting in a radical rethink of what computers can realistically learn. Startups and incumbents alike are teaching machines to emulate an ever-increasing share of capabilities once thought of as “uniquely human.”

Other frontiers of AI advancement include sensation and discernment (the five “senses”); creativity (reading, writing, and the arts); and congeniality (emotional intelligence).

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The Age of With (not against)

AI research suggests that as machine intelligence ascends exponentially, humans succumb to the tendency to think of machines as “the stranger” to be feared and even shunned.
A more useful rubric for thinking about our future with artificial intelligence might instead be to think about machines less as a stranger to compete against and more as a partner to be teamed with—less “other,” more “brother.” We have crossed the threshold to the Age of With, wherein humans can team with machines to deliver outcomes that marry mechanized speed and precision with human intuition and curiosity.

The future of AI gets inarguably more interesting, though, as these intelligent agents continue to proliferate, specialize, and proact.

But what of physical work? While robots have been around for some time, today’s robots are different in at least two material ways: They’re much more configurable and much more situationally aware.

As a result, the future of robots in the workplace is increasingly turning toward “cobots”: Collaborative robotic teammates that work with us, rather than instead of us. So while histrionic headlines have long fixated on robots coming for our jobs, research trends suggest that they are more likely to be our colleagues, as opposed to our replacements. The cobot market is expected to be worth $7.5B by 2027, or around 29% of the global industrial robot market. The market is further expected to grow at an annual rate of more than 60% for the next two years and more than 35% CAGR until 2027.

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Our shared AI future

While all science fiction explores our relationship with technology, a particularly vivid sci-fi trope speaks to the taboo of ourselves becoming technology-based beings. The research suggests that our shared AI future is, in part, about our becoming cyborgs. It’s a slow, symbiotic coevolution of our own choosing, and it’s already begun.

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