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Coming to Grips with Artificial Intelligence’s Many Manifestations

By   /  November 14, 2016  /  No Comments

Click here to learn more about author James Kobielus.

Artificial intelligence (AI) is all the rage these days. However, people often overlook the fact that it’s a truly ancient vogue. I can’t think of another current high-tech mania whose hype curve got going during the days when Ike was in the White House, “I Love Lucy” was on the small screen, and programming in assembly language was state of the art.

As AI’s adoption grows, we run the risk of belittling the technology’s potential if we continue to fixate on the notion that it’s “artificial.” When you think of it, all technologies are artificial, pretty much by definition. Cars are artificial transportation, houses are artificial shelters, and so on.

If something adds value to people’s lives, the fact that it’s an artificial resource, as opposed to a natural one, is of secondary concern. As AI proves its value in more cognitive applications, industry observers are searching for ways to describe what’s truly new and innovative about it. In this recent Dataversity article, analysts Steve Ardire and Adrian Bowles discuss diverse AI trends, using many “A-words” to highlight various facets of the technology’s potential.

Drawing on Ardire and Bowles’ discussion, I’d like to present my own more comprehensive “A-list” of ways in which we can characterize AI’s many facets:

  • Anthropomorphic intelligence: AI emulates natural human conversation to such a fidelity that it can drive avatars and impersonate flesh-and-blood individuals. Being able to pass the Turing test has become a trivial task for AI applications of every variety.
  • Algorithmic intelligence: AI relies on an ever-growing array of data-driven statistical algorithms, including machine learning, deep learning, reinforcement learning, supervised and unsupervised machine learning, reinforcement learning, and so on.
  • Automated intelligence: AI automates cognitive processes to such a degree that the need for manual attention, judgment, and supervision is greatly reduced or eliminated entirely. The advance of unsupervised learning techniques will continue to push this frontier.
  • Accelerated intelligence: AI accelerates cognitive processes far beyond what humans would be able to achieve unassisted. This is especially the case when the cognitive challenge involves far more data, a far more complex set of variables, and more dynamic circumstances than the human mind can possibly keep pace with.
  • Anticipatory intelligence: AI can anticipate human intentions and reactions to a greater degree through continual iteration of predictive models from fresh training data. To the extent that AI applications drive their predictions from deep historical data and continuously optimized statistical models, users will feel inclined to treat them as a natural adjunct of our organic intuitions.
  • Adaptive intelligence: AI adapts its cognitive models to fresh data, to interactions with humans, and to changing contexts in order to hone its cognitive skills to a finer degree. The technology can also adapt its own statistical models dynamically and reprogram itself to ensure that the best-fit algorithms are always applied to every new challenge it confronts.
  • Assistive intelligence: AI brings cognitive intelligence into everyday decision-support and other applications through cognitive chatbots and other virtual intelligent assistants. As smart digital assistants pop up organically in every real-world interaction, we’ll regard them as friends that have our best interests at heart rather than, as science fiction tends to portray AI, as an alien force to be wary of.
  • Augmented intelligence: AI augments humans’ organic powers of cognition, reasoning, natural language processing, predictive analysis, and pattern recognition. The incorporation of these capabilities into mobile, Internet of Things, wearable, and other mass-market devices will make these augmentations feel organic to how we get things done.

One value of a list such as this is that it allows us to view AI in the broader context of its impacts on the world around us. It allows us to see that automation—in the dreaded job-killing sense that Ardire and Bowles (and many other industry observers) obsess over—is not necessarily an inevitability. Just as important, AI’s augmented, assistive, adaptive, anticipatory, and accelerative benefits are helping people everywhere to be more productive.

If you want corroboration for this optimistic vision of AI’s value, check out my recent recap blog from World of Watson. Or simply take inventory of the growing range of AI-powered cognitive chatbots in use in myriad industries. And if you think I’m too much of an AI booster, bear in mind that none of the scary potential downsides spelled out in this blog have come to pass, or is even likely to.

Yes, of course, AI is artificial. But the value is providing here and now is starting to feel like a natural part of our lives.

About the author

James Kobielus, Wikibon, Lead Analyst Jim is Wikibon's Lead Analyst for Data Science, Deep Learning, and Application Development. Previously, Jim was IBM's data science evangelist. He managed IBM's thought leadership, social and influencer marketing programs targeted at developers of big data analytics, machine learning, and cognitive computing applications. Prior to his 5-year stint at IBM, Jim was an analyst at Forrester Research, Current Analysis, and the Burton Group. He is also a prolific blogger, a popular speaker, and a familiar face from his many appearances as an expert on theCUBE and at industry events.

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