Developers Worried That AI May Take Their Jobs

By Darryl K. Taft  |  Posted 2016-03-13 Print this article Print
AI intelligence

Earlier this week, IBM announced that it is piloting a version of that robot to serve as a hotel concierge. Known as "Connie," the hotel concierge robot is powered by IBM Watson and Watson ecosystem partner WayBlazer, which offers a cognitive travel platform based on Watson. The robot is being tested at the Hilton McLean in Northern Virginia's Washington, D.C., suburban area. Connie draws on domain knowledge from Watson and WayBlazer to provide concierge information such as recommendations on local tourism and dining.

"As the first system of the cognitive era, Watson infuses a kind of thinking ability into digital applications, products and systems," said John Kelly, senior vice president of IBM Research and Solutions Portfolio, in a statement regarding the CES announcements. "We have already seen this capability begin to transform industries as diverse as healthcare, insurance and retail."

While Kelly listed healthcare, insurance and retail, could software development be next? Apparently some developers are a bit worried.

"I don't think developers have a lot to fear from Watson in the short term," Charles King, principal analyst with Pund-IT, told eWEEK. "The development process included numerous tasks that seem beyond the platform's current capabilities. But over time, it's likely that Watson and similar platforms will evolve to the point where they can be used effectively in some development processes, especially those that demand highly complex or repetitive hands-on tasks."

At the same time, it should be remembered that DevOps has always been an evolutionary process, and that developers use various tools to ease or simplify their jobs, King said.

"Eventually, cognitive platforms like Watson will likely fill similar roles, allowing DevOps pros to pursue more imaginative and creative tasks."

Ironically, in an Evans Data survey from October, developers involved in big data indicated that in projects that use machine learning techniques and processes, human input does not end at project deployment.

That survey of more than 529 software developers focusing on big data showed that most of the three-quarters of developers that reported working knowledge of machine learning processes said the degree to which human input is required for applications is at least some of the time. Forty-four percent indicated that their direct intervention is required in applications that use machine learning most or all of the time. And 47 percent of developers said machine learning software requires human input some of the time. Only 2.6 percent said human input was not required at all.

"Applications for artificial intelligence and machine learning may strike people as examples of completely autonomous computing, in which computers learn to process and act on data by themselves," said Michael Rasalan, director of research at Evans Data, in a statement. "In practice, development for machine learning is rather different from this fantasy. The overwhelming majority of developers involved in machine learning reveal that machine learning still requires a great deal of hands on involvement from programmers. A lot of the work in developing Machine Learning applications involves setting up big data systems and Hadoop implementations. But even after deployment, many developers will be creating and optimizing algorithms required to analyze massive amounts of data. This process is continuous and requires direct human input and control most of the time."


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