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The Perils of Predictive Analytics

The opening keynoter at the inaugural Talent Acquisition Technology Conference shares his thoughts on how predictive analytics are reshaping our world.

Monday, September 19, 2016
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For centuries, people have been captivated by the idea of predicting the future. Crystal ball gazers and fortune tellers all promised to be able to do this. They played on our biases, weaknesses and gullibility and counted on us attributing chance occurrences to their predictive powers.

But the rise of predictive analytics gives us the ability to reduce uncertainty by applying statistics and determining the probabilities that future patterns will emerge in the behavior of people and systems.

The Internet provides a platform for us to communicate, share, buy, play and learn. And because people are largely creatures of habit and tend to repeat behaviors, our online activities -- when combined with today's computing power and statistical knowledge -- tell a lot about what we are likely to do.  We can give odds, based on science, about what will most likely occur. Doing this has required access to mountains of data about what we do, when we do it, how often we do it, and where we do it.

By tracking things such as our location, Facebook likes, retweets, where we check-in, what and when we buy, what we search for and so on, analysts are able to make reliable predictions about our future behavior. This data is often called "data exhaust" by analysts as, in and of itself, it has no real meaning or value. However, when aggregated, correlated and combined and then analyzed with the tools of statistics, this data becomes not only relevant but commercially valuable.

Privacy Invasion

Kevin Wheeler
We are being monitored and watched every time we log into any electronic device, whether it's a computer, a mobile phone, a tablet or a game. And everything we do is collected without us being aware. We do not give permission for it to be collected, nor do we have any control over what is collected. And, we have no way to turn off the monitoring.

For example, when we buy things, it isn't hard to predict that we might buy more of them. It's even possible to narrow this down to specific types of items, the amounts we spend and the frequency with which we buy them. Or, when you do something as simple as check in to a restaurant or hotel, you're leaving a location trail as well as an economic trail. When combined with your profession -- easily derived from your LinkedIn or Facebook profile -- this data can predict with a high degree of certainty where you are likely to be at a given time, how often you will be there, what kind of hotels you prefer, perhaps even the type of room you prefer, your income, and much more. And all of this can be sold to a hotelier or retailer without your knowledge or permission.

Commercialization that Plays on Our Predilections

Predictive analytics has had tremendous commercial benefits. Firms such as Amazon are built on predictive analytics that help them predict what we will buy, how much of it and when so that they can stock warehouses and order products before they are needed. Most retailers are investing in hiring analysts, which is a growing field. 

Much of the work in developing predictive analytics has been paid for by Madison Avenue, Wall Street and the retail world. We are heavily marketed to based on our location, age, socio-economic status and past behavior. Products are recommended to us based on a prediction about what we are likely to buy.

Shoshana Zuboff, a Harvard professor and no fan of predictive analytics, has focused her research on the study of the rise of the digital; its individual, organizational, and social consequences; and its relationship to the history and future of capitalism. She is concerned that we're applying analytics to making money and toward turning us all into "slaves" of the commercial world.

Zuboff writes, in her article titled A Digital Declaration, "Now the focus has quietly shifted to the commercial monetization of knowledge about current behavior as well as influencing and shaping emerging behavior for future revenue streams. The opportunity is to analyze, predict and shape, while profiting from each point in the value chain." 

Biases that Impede Truth

All humans have biases, many of which can impact human resource professionals and recruiters. 

The selection and hiring of people is fraught with bias and subjectivity. Psychologists have assembled long lists of these biases, which include our tendency to reject new evidence that contradicts something we believe to be true, or the tendency to search for and remember information in a way that confirms our preconceptions.

For example, if we believe that people with high GPAs are better workers, then we will seek evidence to prove that and dismiss any that contradicts it.

Recruiters also often rely too heavily on one trait or piece of information when making decisions -- often the first piece of information acquired or the information obtained from a trusted source. If someone recommends a candidate, for example, that recommendation may outweigh any facts that contradict or suggest that the person is not so good.

Many recruiters and hiring managers also suffer from what is called the "hot-hand effect," which is the fallacious belief that a person who has experienced success doing something has a greater chance of further success in additional attempts.

Analytics can help dispel many of these, but only if the results of the analysis are believed and acted upon. There are many instances in which our biases were unconsciously built into the algorithms that analyze our data.

Analytics can offer insight and help make sense of mountains of data that have been beyond our reach. Analytics can help us make choices that are based on facts. They can provide us insights and reduce uncertainty. But, as with everything, there are dangers. We need to troll the waters of data with care, ethics and human judgement.

Kevin Wheeler is a globally renowned speaker, consultant and author on talent-acquisition issues. He founded the Future of Talent Institute after a long career in HR leadership at companies including Charles Schwab Corp. and Alphatec Electronics. He will deliver the opening keynote at the inaugural Talent Acquisition Technology Conference on November 15 in Austin, Texas.






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