The future of AI isn’t HAL—it’s intelligence augmentation

We may earn a commission from links on this page.

In 1997, IBM’s Deep Blue computer defeated reigning world chess champion Garry Kasparov in a high-stakes, man vs. machine chess game. Commentators hailed the victory as proof that AI could match, if not surpass, human intelligence. In 2011, IBM’s Watson competed in the game show Jeopardy! against former champions Ken Jennings and Brad Rutter, and won. The predictions of AI enthusiasts appeared to be coming true: machines were learning to outthink humans.

Yet in between these two landmark cases, another gaming event occurred which may ultimately prove to be the most instructive about the future of AI and its application in our lives. In 2005, the website Playchess.com hosted a “freestyle” chess tournament in which various combinations of humans and computers could compete against each other. Even the most advanced chess computers fell easily to a human player with an average laptop.

In the end, the winner was not the best chess player using the best machine, but two chess amateurs who were particularly skilled at coaching their three computers to find ways to defeat opponents. Success, it turned out, lay not in man or machine alone, but in the hands of individuals who best knew how to optimize the abilities of technology towards a desired end.

This revelation is fast turning into the biggest takeaway for industry leaders who are gauging how AI might reshape their fields—already an area of massive interest. Venture capital investments in commercial AI products have exceeded $2 billion since 2011.

It’s becoming increasingly clear that the most promising applications are not in machines that authentically think like humans, but in AI that complements human endeavors, a field called intelligence augmentation. For context: Scientists distinguish between general AI (machines that possess a wide range of cognitive abilities, as humans do), and narrow AI (machines that can carry out circumscribed, pre-defined tasks). So far, no true application of the former exists, according to Sandy Pentland, one of the founders of the MIT Media Lab. However, there are hundreds of fascinating examples of narrow AI, including those within the field of intelligence augmentation.

Take the AI behind Deep Blue and Watson. This technology did not actually replicate the creativity of the human mind, but crunched vast sets of data in a rigorously defined environment—“intelligent the way your programmable alarm clock is intelligent,” argued Garry Kasparov.

This description is not meant to diminish the capabilities of narrow AI, but to characterize it in a way that best reveals its value to people and industry. Computers can do things that even the most skilled humans can’t and unskilled humans can easily do things (i.e. recognize or move objects) that are highly challenging for the best computers. It’s in the symbiosis between the two that researchers expect to deliver the greatest gains.

This counterbalanced AI is already threaded into our lives in countless ways. The online movie rental service Netflix employs a recommendation engine based on machine learning that predicts which movies users will most enjoy—it accounts for 75% of Netflix usage. Similarly transformative, data-centric technologies are evident in everything from apps like Waze, which helps determine the best driving routes, to programs that help doctors make the best diagnoses in critical cases. And in carrying out such tasks, computers never suffer from mental fatigue or inconsistency due to subjective concerns. By taking care of routinized, time-consuming work, AI frees up people to do the things that machines cannot: plan, improvise, strategize, and decide.

Science fiction has long been preoccupied with the prospect of advanced and threatening entities like HAL from 2001: A Space Odyssey. So far, at least, we may have overestimated the odds of encountering such AI in the near future. But when it comes to intelligence augmentation—the symbiosis of man and machine—we may have actually underestimated its potential.

Read Deloitte’s analysis on cognitive collaboration to learn more about intelligence augmentation.

This article was produced on behalf of Deloitte by Quartz Creative and not by the Quartz editorial staff.