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

Die Annual Performance Review Die

Client calls.  Asks if they can fire Jerry for performance reasons.  The first (seriously, the very first) question I ask is, “what do Jerry’s performance reviews say?”  Experience has taught me that performance-related terminations usually have a homegrown enemy – the employee’s previous annual performance reviews.  What if we could eliminate the enemy by doing it better?

No one likes performance reviews.  Employees lose sleep the night before a review meeting.  Managers hate completing all the forms and fear having uncomfortable conversations.  HR turns into nagging mother-in-law types trying to track down managers to get all the forms turned in so that performance increases can be made.  No one likes this.

Performance reviews are rarely done well.  Most typically, the reviews are so vague they are meaningless.  They focus only on recent events and not performance over the entire year.  They are chockfull of bias.  Sometimes, a manager pretends he lives in Lake Wobegon where all the employees are above average.  Because we in HR are focused on handling the next fire, we don’t have time to push back on managers who do not do performance management well.  So, a poorly completed review gets stuck in a personnel file until I ask about it when the client wants to terminate.

Even when the termination is completely warranted and lawful, it’s the performance review that hurts.  The termination is going to have to get explained.  I’m confident that I am not the only employment attorney stuck explaining why an employee was terminated for bad performance just weeks after a positive review.  (We attorneys should form a secret society complete with a secret handshake.)  Our explanation is often couched in terms of a rapid performance decline as explained by a manager who “wanted to be nice” in the review but had observed poor performance that resulted in a lost customer, order, and so on.  The explanation by both the attorney and the manager is expensive for the company.

These are just a few of the reasons I want the annual performance review to die.  I’m not advocating for the end of performance management – quite to opposite.  I want more frequent, meaningful reviews for everyone.  Here’s my wishlist:

  • Conversation coaching.  Managers need to have difficult conversations with employees about performance.  Most managers, and particularly new managers, have not learned how to have these difficult conversations.  HR pros are conversation coaches, so we need to coach our managers on how to have these conversations.  Or, we need to get our managers the training and skills necessary.
  • Frequent discussions.  I love one-on-ones when they’re done right.  Brief meetings that discuss how projects are progressing that also discuss how the employee is doing are vital to successful businesses.  With this, managers get a sense of what roadblocks they can remove, and employees get critical feedback on how to do better.
  • Transparency.  People need to know how they’re doing.  Managers need to tell them.  Use examples.  Explain how things can improve.  Show.  If employees know where they stand, they may be able to understand why you’re firing them and not believe it is for some unlawful reason.
  • Recognize.  It isn’t just poor performance that needs to see the light of day.  Good performance does too.  Managers need to know how to champion those performers with potential as well as coaching those who just haven’t meet expectation quite yet.
  • Documents.  (Insert collective reader sigh here.)  Yes, feedback discussions should be documented.  I don’t care you document provided you document and I can get it later when we need it.  You can use the functionality of your HCM or you can have managers email themselves brief synopsis of each conversation.  With the conversation coaching, coach managers how to document as well, including how to remove references to protected class status, leave use, or other items that could get an organization in trouble.

Employees deserve to know how they are doing.  More importantly, they want to know how they are doing.  That’s what a great performance management process can do – get employees what information they need to do their jobs well so we can do our business well.

 

Photo by Tim Gouw on Unsplash

 

 

FMLA Screaming (Part II)

Have you pondered the question from yesterday’s post?  Agree with me that there are things you can do and things you should do?  That should do includes approaching FMLA with come compassion and not being super strict with FMLA’s limitations, right?

Yesterday’s post covered some of my tips for the start of FMLA.  Here are a few more for during leave.

Preparation for leave is essential.  Hopefully, the employee knew he needed to go on leave and was able to prepare by giving his manager his passwords, updating her on the status of projects, and plan to turn over work.  Sometimes, this isn’t the case.  An accident, premature delivery, or quick onset of a serious illness can take the employee out of the workplace leaving a manager without the benefit of the advanced notice.  What do you do in these emergency situations?  Leave the employee alone.  The employee is already ill or injured himself, worried about a family member, or facing the crushing reality of being a parent to a new baby.  The status of the sales agreement with customer XYZ is not top of mind.

Let technology help you with not knowing what’s going on.  Get access to email and other systems to help piece together the status of projects without bothering the employee.  Need a password?  Work with the software vendor or your own IT team to recover a password if necessary.  Change permissions so the manager or another team member can see things.  Again, don’t bother the employee.

If the leave is intermittent and the employee’s need for leave could come as a surprise on any given day, plan for what that looks like.  How will the employee handle the sudden need to be off?  Come to an agreement with the employee about his work when this happens.  Does this mean the employee spends the last 10 minutes of each day sending a quick email on the status of things?  Maybe.  (Would that be a nice thing to have anyway even if he didn’t need leave?  Yep!)  Setting expectations is a manager’s job.  If the manager laments every time Juan takes an intermittent day, well then it’s the manager’s problem for not preparing for this – not Juan’s.  (I know, I know, this isn’t a great one-liner to share with the manager, but you all are good coaches, you’ll soften the message.)

Don’t surveil the employee.  Seriously.  Don’t send someone out to watch the employee’s house to see if he is cleaning his gutters or fixing a deck.  Don’t monitor his social media accounts for signs of a vacation.  Assume the employee needed the leave and is using the leave within his or his family member’s health care provider’s instructions.  If something fishy starts happening, you’ll learn about it.  Don’t waste your time and resources beforehand.

When the employee is ready to come back to work, don’t forget the ADA.  Yes, the ADA can be an even bigger headache for employers.  Yes, the Seventh Circuit recently held employers might not have to give more leave than the FMLA requires.  However, the ADA places a reasonableness standard on employers.  Employers are required to consider reasonable accommodations, including leave, for each requesting employee on a case-by-case basis.  Don’t get consumed with “well if we give it to Larry, we’ll have to give it to everyone else.”  Remember, the ADA requires case-by-case analysis.  For more return-to-work tips, check here.

Lastly, remember that communication is really important at the end of leave.  You may want to know if any restrictions are necessary.  You may want more confirmation as to what day.  For requests like these, remember K8’s rule of three.  Ask at least three times in writing before you assume the employee is abandoning his job.

I get that the FMLA is tough.  I get that it can be frustrating for HR and managers.  However, it can be a godsend for employees.  It’s supposed to give them peace of mind that their job will wait for them if they need to be out for a bit.  Use this fact as a part of your compassion and empathy game. The employee will thank you for it.

 

 

Photo by frank mckenna on Unsplash (Great, happy picture, right?  Perfect for a Friday!)

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

#UltiConnect!

This week, I was honored to be included in a loveable group of yahoos – I mean, influencers – at Ultimate Software’s Connections Conference in Las Vegas.  These people are leading the way in human resources and technology, and I’m lucky to call them friends.

The conference itself was really something.  While Robin Roberts and John O’Leary’s keynotes were fantastic, it was Ultimate Chief Executive Officer Scott Scherr who left the biggest impact on me.  Mr. Scherr’s general session did not focus on what was new or why his leadership has brought success to the company like how many other CEOs may have spent their time.  Instead, he focused on his people.  He went through a list of Ultipeeps who have made a difference.  This list was impressive, even if he was slightly embarrassing a few of them.

But what really got me was how Mr. Scherr focused on their “People First” mantra as not just a mantra but a lifestyle.  In a presentation to SHRM in 2009, Mr. Scherr said the following, “The measure of a company is how they treat their lowest paid employee.”  In this year’s session, Mr. Scherr talked about how the character of the company relies on the character of its people.  When you hire good people, you treat them well, they will take care of the 3,700 customers there at the conference and all those who were unable to attend.  This is so true.  Another (more lawyerly) way to look at this is when people are treated well, the compliance risks are significantly lower for an organization.

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If you’d like to see the sessions where I presented, please see the links for employee communication (I start at 17:25) and women in leadership.  The women in leadership session was made up of some fantastic women!  I highly recommend spending some time to learn from them.

 

Chatbots Listening

Yesterday, chatbots chatted with our employees at our own behest. HR bought, paid for, and implemented the chatbots.  Today, we’re going to chat about chatbots that listen even when they are not our chatbot but it is our business.

We’ve learned the unfortunate statistics that seven out of ten harassment instances do not get reported.  Employees fear for their jobs, they don’t want to be “that” person who upsets the apple cart, or they simply don’t know that what happened to them violates an employee handbook or who to talk to about it.  There’s one more reason though.  According to this Recode article and the overall theme of most harassment news reporting, employees don’t trust us.  However, they’re willing to trust a chatbot.

SpotSpot allows employees to go through a bunch of questions about potential harassment, develop a report, make it anonymous, and then submit the conversation report to the company (if the chatter wants to).  The chatbot helps potential reporters organize their thoughts, think about other evidence that might exist to help show something inappropriate happened, and it can show them that they can have this conversation with their organization, bolstering their confidence. These are all good things.  And, things that will be ultimately good for the organization.

But the bot also can give the employee the impression that by conversing with the bot, their job is done, they won’t have to deal with this directly.  This impression is wrong, very wrong.

Humans have to be involved.  If (and when) a report gets sent to the company, we have to do something.  Most often, we launch an investigation.  We talk with the individuals involved, including the reporter.  We look for other evidence, review policies, and then take action if necessary.   Failure to do something could mean liability.

Moreover, anonymous reporting doesn’t mean that the reporter isn’t going to have to talk to someone.  Even if a Spot user scrubs the report to make it more anonymous, we have an obligation to figure out who is reporting and how can we stop any bad behavior.  We might not know who or even what department, but HR has to ferret out the information based on what little information we have.  Failure to do so could mean liability.

For HR, we must accept complaints from employees in any and every way they come to us.  We will get anonymous reports through chatbots like Spot.  We will hear from the water cooler gossip mill.  We may see a negative post on Glassdoor or Indeed.  We will have employees come to our office.  We will get hotline calls.  In any and every instance, we have an obligation to do something.  Our first priority to make safe, respectful workplaces for our employees.  So, we listen.  Please listen.

 

Photo by Pavan Trikutam on Unsplash