HR Tech’s Adverse Problem

While I totally loitered at the Society for Industrial and Organizational Psychology Conference (I was a presenter, just failed to register – oops), I’d thought a post on what we talked about yesterday and a bit about what’s happening at the University of Minnesota’s HR Tomorrow Conference today: adverse impact, why it’s important, and why you should care.

Adverse impact (known as “disparate impact” by the lawyers) is when groups of individuals described by a particular characteristic is negatively affected by an employer’s decision, selection tool, or policy when that decision, tool, or policy is neutral on its face or does not intend to actually have a negative impact.  For example, if an employer uses a psychological test that filters out African Americans, the test would have an adverse/disparate impact on African Americans.

The concept of disparate impact has been around for a long time.  The United States Supreme Court in Griggs v. Duke Power formally recognized the claim.  Since that time, the law has been debating many aspects of the claim, including what statistical models to use, does the doctrine apply if the rule intends to discriminate, how does impact different from treatment, and will the doctrine apply to all the HR technology out there.  While this post could go on-and-on about all of these questions, this last piece is really important for HR tech buyers, and the answer is probably.

We already know that lots of HR technology vendors, including the fancy-dancy stuff like artificial intelligence, machine learning, algorithms, etc., market their products as the only way to find the best candidates, identify problem employees, and make all your dreams come true.  When these technologies are used, their use could create a disparate impact.  How do we know?  Because we’ve already seen how these technologies discriminate outside the world of HR – see photo ID that classifies African Americans as gorillas, recidivism tools that increase prison terms for African Americans, etc., so it is highly likely that they could operate the same way when it comes to HR tech.  Arguably, HR tech has the potential to greatly impact because the decisions HR makes affect individual’s livelihood.

So what should we do about diverse impact?  While there are many, many things we need to do to limit the potential that the HR tech we use doesn’t discriminate, we should start with two things.  First, we have to know how the technology works and the data it uses to make recommendations.  This requires vendors to be open and honest with us, lose the marketing gloss, and really explain their products. Can they explain how the tech works?  Can they explain how the tech works on our organization’s data?  Could the data have bias baked in?  (The answer to this last one is probably yes, especially if we’re looking at hiring or performance data.  There’s just no escaping it.)  When vendors are transparent and honest about these issues, we can take more steps to mitigate any disparate impact the tech might have.

Second, we need to test and test and test to see if the tech creates the disparate impact.  Lawyers and data scientists talk about validation as the test.  For lawyers, validation means under the Uniform Guidelines for Employee Selection Procedures.  For data scientists, validation means how strong the correlations are statistically.  This definitional problem causes more debate and potential confusion.  So, we need to find vendors who understand, appreciate, and can articulate validation under both tests.  Because the HR tech world is a bit like the wild, wild west, it’s hard to find them. (Trust me, they’re out there.  I’ve probably met them or at least brow-beat them from a distance on this very issue.)

All that said, I want HR to understand and appreciate that these issues could exist and start playing an active part in fixing these issues.  While I’d love for everyone to trust each other, placing blind faith in a vendor is not in our organizations’ best interest.  Holding people accountable is one of the strengths in HR.  We should use it here too.

One final note, I love this stuff.  This tech is going to revolutionize how we do business.  I just want to do it in such a way that doesn’t create that much risk for our businesses.  Remember my pledge?

 

Photo by Patrick Lindenberg on Unsplash

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