Being Human

This week, I had the enormous privilege of attending #workhuman.  If you’ve never heard of Workhuman, where have you been?  Remove yourself from under that comfy rock, and let me share all my learnin’, y’all.  (Workhuman was in Nashville this year, and now, my drawl game is strong.)

Workhuman, formerly Globoforce, is a social recognition and continuous performance management platform that can integrate with lots of different HCMs to improve how your people see and interact with each other.   Workhuman does a ton of research on the impact of social recognition on inclusion, gender, race, wellness, and performance issues that will make your jaw drop.  They’ve come up with ways to inform, but not criticize, how we use language from a gendered and racial perspective when giving recognition or feedback based on the data they have collected from millions of interactions.  It is this research informs how they do business.  They’ve learned that being human makes workplaces better.

#workhuman is their signature conference, bringing together thousands of concerned humans for the sole purpose of trying to figure out how to make the workplace more human.  The conference is all about how do we see, treat, encourage, develop, recognize, thank, and love – yes, I said love, but not in the romantic sense – the people we work with so we can all do better.  This is more than just an HR conference, it is a business conference.

Here are a few of my takeaways:

We have to revel in being uncomfortable.  Whether it was Brene Brown, Kat Cole, Candi Castleberry Singleton, David Lapin, or any of the other speakers, this was a powerful take away.  As a society, we are at a tipping point.  Our workplaces are also at this tipping point.  We can’t simply put our heads down, our safety googles on, and focus on productivity goals if we’re going to be successful.  If we’re going to have people in our workplaces, we need to accept and welcome them as they are.  We’re going to have to talk to them about the heavy society concerns from gun safety, policy brutality, offensive tweets, gender and racial inequality, and the fear that prevents us from being our whole selves.  Allianz does this, Kat Cole does this, we should all do this.

Recognition makes a difference.  Data is the best.  Data that shows we can make a dent in the problems that plague our workplaces is even better.  The data Workhuman shared on how recognition can improve our connections at work, our engagement at work, and help plug the holes in our leaky buckets is so impressive.  I want to know more.  Luckily, there’s a resource page devoted to this!

Pobody’s nerfect, but we can all be resilient.  If we’re going to have difficult, uncomfortable conversations at work, we’re going to make mistakes.  We’re going to hear antiquated language that is now offensive.  We will have to tackle our fear with a battering ram.  We’re going to have to be brave and vulnerable.  We’re going to have to rely on our integrity, strength, and humanity to deal with the mistakes, use them as teachable moments, and move on.  I’m not saying that every mistake is just a mistake – some mistakes warrant termination – but as we encourage these conversations, forgiveness and resilience will be powerful to keep us moving forward.

Being human is hard.  As a crier, I was moved to tears a couple of times – not gonna lie.  It is hard to be vulnerable, willing to fail, learning from our mistakes, and sharing our failures so others can learn from them too.  No one promised this life, in general or in business, was going to be easy.  So, grab your friends, family, co-workers, and meet these obstacles head on.

I cannot oversell #workhuman.  Every attendee self-reflects, does some mental gymnastics, and learned from this conference.  Next year, Workhuman is in Denver.  I hope to be there.  I hope you all are too.

 

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Me & You Metrics

I wear an Apple Watch.  I have since they debuted in April 2015.  I love it even though I rarely use all of its functionality.  I track my calories burned, whether I work out, get all the notifications from Twitter to reminders to actually breathe.  (Little nugget – I have only missed my stand goal twice in nearly four years.)  I’ve metric-ed myself to death with Ive (my watch’s name).

Yet, I would never share all of this information with an employer.  You can tell where I’ve been, whether I went up a flight of stairs, or my heart rate at a particular time. You’d be able to figure out so much about me, my habits (good and bad), and could even use the information to determine if I’m a good employee.  (She sits too much when she should be chatting with customers or getting parts.)

My personal beliefs of biometrics are part of the reason I’m less-than-enthusiastic about recommending employers use them.  I love the idea of determining if there’s a better way to lay out a manufacturing floor, whether we could reduce real estate costs by encouraging hot-desking, and I’m even for handing out Apple Watches to employees for wellness purposes.  But I just can’t get endorse an employer gathering this data and then making employment decisions based on the data.

My biggest concerns surround privacy and the potential for misuse of personal health information.  Employers don’t get to know what I do off work provided it doesn’t affect the workplace.  If an employer knows, could I get terminated for spending too much time at a movie theater rather than reading business books?  What about not spending the night at my house but at a friend’s? Biometrics can allow data gatherers to be the Big Brother technology has often been portrayed as.

As for health information, biometrics are implicated by the Americans with Disabilities Act, Genetic Information Nondisclosure Act, and many state laws.  Imagine being an employee in a wheelchair where steps taken are not going to be tracked.  Does that mean that that employee is not going to be considered when the health data is aggregated into an analytic tool that determines who should be promoted?  Or imagine being an employee who struggles with his weight who has trouble meeting his step goals.  When his fitness goals are not met, does that mean he could be terminated, maybe even in an effort to reduce overall health costs. (This would likely be unlawful under ERISA, but that might not stop an overly cost-conscious employers.)

To this end, I recently went on XpertHR’s HR Podcast to discuss a new decision out of Illinois on biometric data collection and the possible impact on employers from coast-to-coast.  I encourage you to listen.  You can listen here.

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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.

 

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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.

 

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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?

 

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Happy Birthday, tHRive!

Today is a big day!  Today, tHRive Law & Consulting turns one.  In just the past year:

Human resources and employment law are ever-changing and exciting.  Our work touches nearly everyone, making it incredibly meaningful and challenging.  This is why I love it.  I can’t think of another area of business or law I’d rather be in.

tHRive Law & Consulting made it through one of the most significant milestones of any start-up – the first year.  I could not have done it without the support of so many and the confidence of my HR tribe.  For that, I am eternally grateful.  Thank you!

Now, onto the challenges of year two!

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