Relying on machine learning and so-called “smart computing” to solve and automate a variety of tasks has become more of the norm than the exception.
If you want an example of how artificial intelligence is evolving in a workplace context, look no further than IBM’s Watson, an A.I. system capable of answering questions posed in natural language. (Its name derives from IBM’s first CEO, Thomas J. Watson.)
Needs and Solutions
A couple of years ago, IBM made the decision to focus its artificial-intelligence work on healthcare, a burgeoning industry. The company’s engineers began coding Watson for “telehealth,” or the ability to remotely evaluate medical conditions. Because the technology is still in its relative infancy, they decided to devote Watson’s “learning” to non-acute symptoms such as colds. (More acute symptoms still demand a flesh-and-blood physician.)
Training Watson hinges on inputting ever-more-sophisticated algorithms into the system, which allow it to ask increasingly relevant questions. This series of questions eventually culminates in a “gatekeeping” point, in which Watson may refer the patient to an urgent care center if their symptoms are deemed too acute for a regular telehealth consult.
IBM has also aimed Watson at the food industry, with an app (called IBM Chef Watson) that will take any ingredient inputted by the user and return with a list of recipes that use that ingredient in original ways. Will this technology make cookbooks obsolete? Probably not—but for novice cooks, a site like this can prove extremely useful.
The Job Market
IBM likely won’t be alone for long in its artificial-intelligence work: Apple, Google, Microsoft and other tech firms have all shown significant interest in creating digital assistants that respond to natural language queries. For tech pros who specialize in fields such as machine learning, this rising interest can translate into incredible opportunities to help determine the future of “mass market” artificial intelligence.