AI technology could replace countless jobs in the not-so-distant future, making an impact on workforces all over the world. According to a new analysis published in Information and Organization, researchers and policymakers alike should pay especially close attention to this development and get involved now—before it’s too late.
“We have to think about what aspects of work have meaning and value to us,” co-author Diane E. Bailey, Cornell University in Ithaca, New York, said in a prepared statement. “We might decide, ‘Maybe AI can do this better than a person, but we don't care, because we get some value out of it.’”
The authors noted it will likely take longer for AI to transform entire industries than people think—and in some cases, it may not even end up being a good fit at all. In addition, technological breakthroughs often lead to “different outcomes for different organizations,” meaning AI won’t impact every entity in the same way.
One example the researchers explored was a 2017 study about an algorithm that detects infections in a neonatal intensive care unit. It was designed to tell providers when they should intervene—but the doctors and nurses “treated the algorithm’s output wit skepticism” and “came to use it as just another tool for arriving at their own diagnosis.” In other words, the AI model expected to automate a key aspect of healthcare simply became another alert to monitor throughout the day.
As unpredictable as the implementation of AI and automation can be, the authors suggested a “unified approach” to study these technologies. The approach starts issues related to “power and ideology among stakeholders,” shifts to “issues of variation” and ends with “issues of the institutional effects of technology use.”
“We have to understand how all of these market mechanisms operate if we're going to be savvy enough to work in that world and say, ‘No, we want technology that looks like this’ [or] ‘Design something that operates this way,’” Bailey said in the same statement. “We need to work backwards from some desired future that we want, to get the technologies that will help us get there.”
Michael has more than 16 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.