Posted April 28, 2017 by

Predictive analytics and interview bias

 

The following are excerpts from “Predictive Analytics, Bias and Interviewing”, written by Kevin Wheeler of Global Learning Resources Inc and The Future of Talent Institute. Published to College Recruiter blog with permission from Kevin Wheeler.

To download the full white paper, click here.

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.

By tracking things such as our location, Facebook likes, re-tweets, where we check-in, what and when we buy, what we search for and so on, analysts are able to make reliable predictions on our future behavior. When aggregated, correlated, and combined and then analyzed with the tools of statistics this data becomes not only relevant but commercially valuable.

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.

Biases that impede truth

All humans have biases and many that tend to 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. Recruiters need to do everything they can to make objective and unbiased decisions – even though perfect objectivity is never going to be possible. I offer a few suggestions below on how to reduce the impact of biases.

There are numerous common biases. For example, if we believe that people with high GPAs, for example, are better workers, then we will seek evidence to prove that and dismiss any that contradicts it. We call that confirmation bias.

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.

Analytics can help dispel many of these [biases], but only if the results of the analysis are believed and acted on.  We need to trust the data more than our gut, and although data is not always right, the percentages are on the side of the data.  There are also many instances where our biases were unconsciously built into the algorithms that analyze our data, so it is important to understand what is being measured in an algorithm and with what weighting.

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 judgment.

What you can do to reduce bias

Each of us has a responsibility to actively think about our prejudices and biases and work to manage their impact on our decisions.

  1. Know Yourself: What are your biases? Think about what you like and don’t like in people and then ask yourself why do I think this way?  You can ask yourself what you are really looking for in a candidate – is it something like GPA or age or a very specific kind of experience — and then ask yourself, what’s the evidence for this to be a decision factor? Is this really evidence that the candidate will perform well or just a self-fulfilling prophecy because of my bias?  Biases are hard to discover, hard to articulate and even harder to objectively measure.  But if you work at it, you can reduce the number of them and their impact.
  2. Prepare Neutral Questions: When you prepare for an interview, make sure that your questions are not aimed at bringing out a bias of some sort. Keep them job-specific and relevant to the work you want the candidate to do. Never ask about age, politics, or anything that is not job relevant.

Read more concrete advice for reducing your bias by downloading the full white paper here.

 

Kevin Wheeler of Global Learning Resources and Future of Talent InstituteAbout Kevin Wheeler: Kevin is the founder of Global Learning Resources and The Future of Talent Institute. He is a consultant, sought-after public speaker, writer, and university lecturer.   Kevin is the author of hundreds of articles on talent management, career development, recruiting, human capital, leadership, and on corporate universities, strategic planning, workforce planning, and learning strategies. Global Learning Resources and The Future of Talent Institute work to help organizations discover emerging trends that impact the talent marketplace and help organizations implement creative talent strategies to meet the challenges of the future.

 

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