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While we may be far from a world where
machines will replace working humans, 45 percent of work activities could be automated using existing technology, according to the
Four Fundamentals of Workplace Automation, a new report by McKinsey & Co.
Researchers pointed out that more than blue-collar jobs are at risk of metamorphosis or extinction. But sources stress that people will still be part of the equation: Automation will help people work smarter, they say, and will give rise to new kinds of workers.
“Automation comes in funny ways and is often so blindingly obvious we don’t even notice it as we adapt,” pointed out Jeremy Carey-Dressler, an automation engineer and owner of Eternal Blue Software in Meridian, Idaho.
Consider ATMs, which have replaced bank tellers, or apps that provide airline boarding passes. Today’s computer programs now perform data analysis and can generate entire newspaper articles in minutes. For example,
IBM Watson works as a cognitive assistant, using “natural language processing and machine learning to reveal insights from large amounts of unstructured data,” according to IBM.
McKinsey reports that “a significant percentage of the activities performed by even those in the highest-paid occupations (… financial planners, physicians, and senior executives) can be automated by adapting current technology. For example, we estimate that activities consuming more than 20 percent of a CEO’s working time could be automated using current technologies. These include analyzing reports and data to inform operational decisions, preparing staff assignments, and reviewing status reports.”
MarketsandMarkets, a market research firm based in India, estimates that the artificial intelligence (AI), or cognitive computing, marketplace will generate $12.5 billion in revenue by 2019. Research firm KPMG states that by 2025, 100 million global knowledge workers could be affected by robotic process automation.
What Happens to the World of Work?
“I have a strong view that systems such as those described should not be thought of as replacing humans but, rather, enhancing the way humans do their jobs,” Sheri Feinzig, director of strategy for IBM’s Smarter Workforce Institute, told
“For example, advanced analytics tools can do a phenomenal job of ingesting and analyzing vast amounts of information and identifying relationships in the data,” she said. “The reality is, though, that not all of those relationships will be meaningful, actionable or causative in nature. By surfacing these observed relationships quickly and efficiently, the human decision-maker is then able to discern what makes sense, what is useful and what can be acted upon. You still need the human as part of the decision-making process.”
Other sources concurred, telling
SHRM Online that in light of the revolutionary changes slowly being made by supercomputing programs, HR will need to make sure humans aren’t left out of the equation.
KPMG reports that with
massive investments in AI from companies like Facebook, Dropbox and Google, and with the launch of high-profile businesses like IBM Watson and IPSoft’s Amelia, AI is on the rise.
According to San Francisco-based data analytics firm Quid, “from 2010 to 2014, private investment in AI has grown from $1.7 billion to $14.9 billion and is on track to grow nearly 50 percent year-on-year in 2015 alone,” KPMG reports.
Cliff Justice, a principal at KPMG, told
SHRM Online that “process automation can free up employees from rules-based tasks by computerizing stable, predictable activities. But to truly replace human employees, process automation and cognitive technologies such as IBM Watson must converge. This combination of advancements is creating cognitive automation—or smart robotics—that can potentially automate new classes of knowledge work.”
People Will Still Matter
“Automating tasks from a business perspective makes things more efficient,” Sybll Romley, a member of the Society for Human Resource Management’s Technology & HR Management Special Expertise Panel, told
SHRM Online. “But we have to make sure we’re not making things efficient at the expense of the customer experience.”
She said it was like looking at any situation from an HR perspective: “It might be more efficient from a production experience, but if you’re doing it at the expense of your culture and business, there’s a risk in that, too.”
Added Carey-Dressler: “Machines can eventually learn by experiencing something repeatedly, but the problem is machines don’t handle unexpected circumstances well.” For example, he said, an automated car may not know what to do when its path is obstructed.
“We see our machines getting more intelligent, but in reality they are just statistical engines with massive amounts of data. When you are building a one-off solution, you don’t have nearly as much data. Until we can develop a funnel to take all the tacit knowledge of a business and make it explicit without millions of data points, AI automation is going to be limited,” he explained. “However, an executive might not need as many lower-level workers or middle managers. Data analysis might come faster and with more clarity from an automated system than from a human.”
But “Knowing what the data actually means still takes a human,” he noted.
Aliah D. Wright is an online editor/manager for SHRM. Reach her @1SHRMScribe.
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