Machine Learning Times
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CONTINUE READING: Access the complete article in USA Today, where it was originally published.  

8 years ago
Your Boss May be Spying on You (and you might welcome it)


Largely unnoticed by their targets, the human resources departments of large corporations are beginning to gather spy-agency-quality intelligence on their current and future employees. The hottest topic in human resources is “predictive analytics,” synthesizing a worker’s traits and behaviors to estimate how he or she will perform in the future.

No one knows exactly where unleashing “big data” on workers will take us. There are indications that it could get intrusive and abusive. According to analysts Raffael Devigus and Chase Rowbotham, there are also hints that it could make managerial decisions fairer, replacing “gut feel” with “unbiased data-driven decisions.” Chances are that in the early going, digital surveillance of employees will be both creepy and cool.

See Chase Rowbotham & Raffael Devigus Session at Predictive Analytics World for Workforce April 3-6, 2016. USE CODE PATIMES16 for 15% off a pass.

Predictive analytics will fundamentally alter the relationship between employee and enterprise. It will redraw the boundaries of worker privacy and managerial discretion. Either by court case or legislation, it will change the law. “Today’s workers are left with a Hobson’s choice of giving up their privacy or giving up their job, if the predictive analytics even allow them to have the job,” wrote University of Wyoming associate professor Robert Sprague in a law journal.

Few people recognize how much digital evidence they leave in their wake. A person’s profile of “Big Five” personality traits — openness, conscientiousness, extraversion, agreeableness and neuroticism — can now be discovered through analysis of her Facebook posts and likes, and machine coding of what she has written online. Her tweets can be mapped to determine how often she is “serene,” “alert,” “depressed,” “tense” or “elated.” Her LinkedIn profile can be mined for such variables as the number, executive level and geographic dispersion of her connections.

Until recently, rigorous analytical scrutiny was reserved for the most valuable and the most dangerous — those about whom making the right decision was worth the high cost. Professional sports franchises routinely used Moneyball-style predictive models to help decide which athletes to recruit or draft. For many years, casinos have used “non-obvious relationship awareness” to spot connections between, for example, people applying to be dealers and cheating gamblers seeking to plant a conspirator on the other side of the blackjack table.

Intrigued by how casinos were finding patterns beneath the surface, the CIA adopted similar methods through In-Q-Tel, a private equity firm it started to help the agency find ways of identifying terrorists. By The Wall Street Journal’s count, 33 of 101 firms funded by In-Q-Tel have since taken on commercial clients. Some of those firms now apply spy technology to scour employee emails for statistical hints of concealment, bribery or ethical ambivalence, so much the better to spot early or even anticipate an employee breaking securities laws.

As the digital trail of most employees grows, as the ability of software to harvest and make sense of that information increases, and as competitors rush into the field, the cost of predicting an employee’s potential will decrease to the point that it becomes common. Predictive analytics is the hottest buzzword in HR, holding out chances for adopters “to win that long-coveted seat at the C-table,” as a 2014 Jibe executive brief expressed it.

“If we wait to see what the competition is doing, we lose competitive advantage and market share,” state Jac Fitz-enz and John Mattox in one of the few books on the subject. “Our motto is: Manage tomorrow today.”

The more garden-variety predictive analytics offerings, with roots in traditional HR computer systems, promise to connect the dots among data that are already within the purview of the company. If a single repository holds a person’s tenure, time since last promotion, pay trend, frequency of recognition and performance levels — and if external data show what that person could be making elsewhere — the computer could quite appropriately signal it’s time the employee be given a raise or better opportunity.

CONTINUE READING: Access the complete article in USA Today, where it was originally published.

Rodd Wagner is a best-selling author and confidential adviser to senior business and government leaders. His most recent book is Widgets: The 12 New Rules for Managing Your Employees As If They’re Real People.

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