If Amazon’s Tool Could Discriminate, Could Yours?

Yesterday, Reuters reported that Amazon created a recruiting engine using artificial intelligence.  This isn’t news.  Amazon is a leader in automation, so it makes sense that the retail giant would try automation in their own recruiting processes to try to quickly find the “best” candidates.  Yet, Amazon’s tool had a big problem – it didn’t like women.

As the article describes, “Everyone wanted this holy grail,” one of the people said. “They literally wanted it to be an engine where I’m going to give you 100 resumes, it will spit out the top five, and we’ll hire those.”  Who doesn’t want this?  To make hiring faster and easier?  Currently, there are hundreds of AI tools available to human resources – many of them in the recruiting space – that promise to do these things for you.  But if Amazon found problems, what about those tools?

Amazon’s tool used a 10-year look back of existing employees (largely male-dominated).  The tool then could rank applicants based on what it learned makes a good Amazonian.  Based on its own analysis, the tool learned that male candidates were preferred over female candidates in a mixture of words that appear on applications, like “women’s,” experience, job requirements, and potentially proxies for gender.  While Amazon tried to solve for this problem – making “women’s” a neutral word so the tool did not reduce the applicant’s rank – the results of the tool still had a negative impact on women.  So, in 2015, Amazon abandoned the tool.  Good for Amazon.  This is the right thing to do.  But again, there are hundreds of other AI tools out there.

At this year’s HR Tech Conference in Las Vegas, my friend Heather Bussing and I presented on this very topic.  We spoke about how AI can both amplify and reduce bias. Here are a few of the highlights:

  • We know that AI is biased because people are biased.
  • We know the sources of the bias include the data we use to teach the AI, the programming itself, the design of the tool, and people who create the tool.
  • Employers have to be vigilant with their tools.  We have to test for bias and retest and retest (and retest) for bias in our tools.
  • Employers – not the AI – are ultimately responsible for the results of the tool, because even if we follow the output of the tool, the employer is making the ultimate employment decision.

It is very possible, even probable, that the tools out there on the market have bias in them.  Employers can’t simply rely on a vendor’s salesperson’s enthusiastic declarations that the tool eliminates bias.  Instead, employers should assume bias plays a factor and look at their tool with a critical eye and try to solve for the problem ourselves.

I applaud Amazon for doing the right thing here, including testing its tool, reviewing the results, and abandoning the tool when it became clear that its bias played a part the results.  This isn’t easy for every employer.  And, not every employer is going to have the resources to do this.  This is why employers have to be vigilant and hold their vendors accountable for helping us make sure bias isn’t affecting our decisions even when using an AI tool.  Because ultimately, the employer could be liable for the discrimination that the tools aid.

 

Photo by Kevin Ku on Unsplash

What Do We Owe Each Other?

While I have been safely ensconced in #SHRM18, I haven’t been able to read the news as much as I’d like.  When I finally looked at my twitter feed devoted to news, I became angry, sad, frustrated, and a whole other host of emotions.  So as midnight approaches, here are some things I hope all of my HR friends take from this fantabulous conference to put into their worlds:

Compassion.  Oscar Munoz explained why caring comes immediately after safety at United.  Caring means holding a door open for a family who just landed a half a terminal away and who are running to catch the plane to see a sick grandma.  While a policy may say one thing, caring about the people we serve (and for those of us in HR, that includes our employees and candidates) sometimes says something different.  If our employees are empowered with compassion, they will do the right thing for our customers, clients, and the greater world.

Compassion.  While he may not have said it in quite this way, Tim Sackett talked about how CEOs want to be able to personalize our HR plans because our people are individuals who want personalization.  Personalization means we have to know, acknowledge, and understand the needs of candidates and employees.  We can’t personalize unless we are compassionate with the people we help every day.

Compassion.  In discussing inclusion, Joe Gerstandt asked us to imagine a world where employees have space to be themselves, we ask and they speak about the personal parts of their life so they don’t feel they have to hide parts of themselves.  “How are you really?”  “How is your mom?  Is she feeling better?”  Adding circle tables to a break room so people can interact.  Integrating our values into conversations about our objectives, especially when we are struggling with an issue.  We want our employees to be innovative problem-solvers, and we can do that by being compassionate with them.

Compassion.  I was unable to attend Adam Grant’s presentation.  But from what I saw on the twitters, it was amazing.  One thing he challenged me on is ending exit interviews.  The argument (via him and some super HR pros) is that we should have known about the problems before the employee leaves.  This is absolutely true.  We should have known.  When an employee is so afraid to talk to us while still working for us, we have lost.  Lost big time.  We need employees to want to talk with us, to want to share the good stuff and the bad stuff.  This takes trust.  We can foster trust by being compassionate with our folks.  Knowing their names, their struggles, their successes.  When they see that we are interested and invested in their well-being, they will come to us with their concerns.

So, what do we owe each other?  Do we owe each person around us respect?  Hells to the yeah.  Do we owe each other attention when a problem crops up or a success is achieved?  Yes.  Do we owe someone time when he is asking for help in dealing with FMLA paperwork because his wife is ill?  Yes.  All of this takes compassion.  When we see people suffering, do we owe them help?  Yes.  It breaks my heart to see people suffering.  I hope that is true for everyone in HR.  We owe ourselves, our employees, and the people around us compassion.

I’m going to try to remain hopeful and do better myself.

Photo by Matheus Ferrero on Unsplash