Thanks for reading our briefing about what companies are doing to navigate the continued reality of remote work, to reopen safely, and to reset their practices for the long-run. You can sign up here to receive it by email as well.
The latest virus forecast: The US has had an 8% increase from two weeks earlier, averaging about 61,000 new cases per day. About 90 million Americans have received at least one dose of a vaccine, and 3.4 million doses were recorded as administered on Friday alone.
The business impact: Weekly jobless claims fell to their lowest level in over a year, as the economic recovery gains speed. Fed Reserve officials expect 6.5% growth this year, which would be the fastest annual economic expansion since 1983. The rate of vaccination is “going to enable us to reopen the economy sooner than might have been expected,” said Fed chair Jerome Powell.
Focus on the Problem with Using Resumes
Removing bias from hiring and opening up job opportunities to people who might not traditionally have had access to them are critical parts of resetting how organizations operate.
I’ve written before about some of the practices that make a difference, such as simple tweaks to job postings so that more women apply, and apprenticeships that provide skills and credentials that lead to good jobs.
Another promising avenue is to overhaul how organizations hire people, and what they're looking for, starting with basics such as the resume. Technology can help. To understand better, I spoke with Frida Polli, CEO and co-founder of pymetrics, which uses behavioral science and artificial intelligence to reduce bias in hiring. (And yes, the company spells its name with a lowercase “p.”) Here are excerpts from our conversation, edited for space and clarity:
The most ubiquitous form of hiring is humans reviewing resumes. What's wrong with that?
There's the human part and there's the resume part; we can start with the resume part. Obviously, knowing something about someone's experience is not a bad thing in and of itself. However, there are several problems—one, it tells you nothing about what someone could do, unless it's linearly related to what they have done. So it's very limiting. It doesn't tell you anything about someone's future potential.
Secondly, and potentially more problematic, is that the resume is unfortunately rife with proxy variables. That's why Amazon got into trouble, because they had trained off of resumes that came mostly from men, and as a result of that they had flagged certain things that men do—like play baseball, not softball, and go to co-ed colleges, not all women's colleges—as being predictive. Whereas probably if you go to Barnard and play softball, you could be equally qualified. But the resume parser has learned that those are not associated with job success because they haven't hired that many women. So when you have a lot of proxy variables in your data and the resume is full of them, it can then cause problems with making predictions or decisions that are not going to then bias against particular gender, race, or socioeconomic status, if historically you haven't hired a lot of those people.
Amazon was experimenting with AI screening resumes. What are the issues with humans reviewing resumes?
The issue with humans is that it is impossible to remove unconscious bias from the human brain. There was a proceedings in the National Academy of Science, a meta analysis of 30 years of humans reading resumes. The way they audit this decision-making is they present the same exact resume, but change the names from John Williams to Jamal Washington for race, and they can change it to Emily Williams for gender. And what they found is in 30 years, ending in 2017, there has been no change in discrimination against people of color—and that for every 10 interviews John Williams gets, with the exact same resume and just changing the name, Jamal gets only seven.
The problem is simply that unconscious bias is alive and well. It's not going anywhere, unfortunately. And again, similar findings for gender. But in this time of increased interest in racial equity, it's important to highlight the stark racial differences that occur just by thinking the person is African-American not white, even with the exact same qualifications.
If humans reviewing resumes is not a fair hiring mechanism, what is a fair alternative?
Metrics and transparency are two critical things. If you don't know what you're aiming towards and you have no transparency in how different processes are leading you to different outcomes, that's a problem. And then the third one being accountability. These are super basic things, but we don't have transparency in a lot of our hiring processes. So it's hard to know where the problems lie. And a lot of times there aren't metrics that people are driving towards, and nobody knows who's accountable. Those are three things you can do immediately, essentially.
The last thing that we wrote about, specifically pymetrics and another technology platform called Applied, is how technology can be used to improve diversity. Soft skills are far more equally distributed, and so we don't have to worry about proxy variables. Why that's important is that you can then actually train on a homogenous set of people, i.e. white men, but because those variables are equally distributed, there'll be just as likely to predict a Black woman being successful in that role, even though your training set is homogenous. Whereas that would never happen with resumes, because resumes are full of proxy variables.
So one is just to have less proxy variables in your input data, that's critical. And the second thing is to audit algorithms for bias and essentially only select those algorithms that meet certain fairness criteria. We will not release an algorithm unless it is above the four-fifths rule, meaning that for every 10 of one group it's selecting no fewer than eight of another group. And if we refer back to our audit studies of humans, humans failed the four-fifths rule, because if you're selecting 10 people called John, but only seven called Jamal, you're failing. So even just by doing that, we're doing better than human decision-making.
What is an example of a soft skill versus a hard skill?
A hard skill is, can you use Excel or can you program in Java—how proficient are you in some technology or something like that. It's experience-based skill. You're not born with the ability to use Excel, at least not yet. As opposed to a soft skill, which would be something that is more innate. Your memory, your planning, your sequencing, those are all things that cognitive science has developed tools to look at. Maybe not in babies, but in young children all the way to people who are octogenarians. Things that are not experience-based, they're thought to be more innate.
Now granted, experience can change these things—it's sort of like the famous nature versus nurture debate. But for example, let's take attention to detail. People are generally predisposed to being more versus less attentive to detail. And there's nothing right or wrong about either end of the spectrum, but it's just something that people are more inclined to be or not be. That would be an example of a soft skill.
How do soft skills relate to fairness and hiring the right people for jobs?
So, a little bit of backstory: I was a cognitive scientist for 10 years at Harvard and MIT and had been essentially measuring what we now called soft skills in the lab for research purposes, looking at people's cognitive aptitudes, like memory, planning, sequencing, looking at their socio-emotional aptitudes, like are you risk-averse or risk-taking, do you perform better under conditions of intrinsic versus extrinsic reward, and so on. Basically, the fundamental things that make people human, rather than what's on your resume, which is just your experience. Cognitive scientists have developed structured, objective and well-validated tools for doing that over the last couple of decades and pymetrics has simply patented it for use in HR.
The light bulb went off when I was watching recruiting at Harvard Business School because it became clear to me that what people were trying to understand about someone was not what was on their resume. Is this person attentive to detail or not? Is this person a team player or not, what is someone's work ethic etc. They were trying to glean those soft skills from a resume; they were saying like 'he was in the chess club, that must make him or her attentive,' and trying to infer these soft skills from hard skills, when it's easier and more accurate to just directly measure them.
That was the idea for pymetrics and that's what we built. There are other ways to do it; I'm just telling you about one. But what we look at are basically cognitive, social, and emotional aptitudes. The other cool thing about soft skills the way we measure them is there is no right or wrong. So if you're attentive versus inattentive—attentive people are good at certain jobs. And inattentive people actually tend to be more novelty seeking and creative, and they'll be good at other jobs. Same with planning: you can be a thoughtful planner or a spontaneous planner. Neither one is right or wrong. It just tells you something about what jobs you will thrive in versus not. So the value to soft skills is that they're a completely different way of looking at someone than a resume. You could have the same person with the same soft skills raised in a privileged background versus an impoverished one and you'd have very different resumes, but that soft skill profile would be identical or very similar.
You can read a full transcript of our conversation, where we discuss other topics including retraining and personality and IQ tests.
Content from our partner McKinsey & Company
The boss factor. Of all the misery in the world, one source lies within an organization’s sphere of influence: the behavior of its bosses. But over half of American workers claim that their boss is toxic. Want to do better? Here's how, from the McKinsey Quarterly Five Fifty.
What Else You Need to Know
Wall Street is forced to focus on work-life balance. A group of burned-out first-year analysts at Goldman Sachs triggered action with a slide presentation posted online claiming 100-hour work weeks and fraying mental health.
- Goldman Sachs responded by saying it would more strictly enforce its policy against working Saturdays, hire more junior bankers, and automate tasks.
- Other banks announced their own measures to address burnout accentuated by the pandemic and a busy year for banking. Citigroup said staff wouldn’t have to turn on their cameras for internal meetings on Fridays and set a May 28 “reset” day off for staff.
If the banks’ responses wind up amounting to more than PR crisis management, this will be a case study in labor organization of a sort, with a small group of twentysomething-employees generating an industry response.
- It’s widely observed that a lot of the work that the junior bankers are foregoing sleep for isn’t essential, such as assembling 50-page PowerPoints when 15-pages, or nothing at all, would suffice.
- And while it might seem laughable to bankers who find it challenging to cut back to a six-day work week, some businesses have successfully gone to four-day weeks. Wanderlust Group, a New England outdoor tech firm, found that morale, productivity, and growth all improved after it started giving its 45-staff Mondays off.
Maybe computers could help lighten the workload. Morningstar last week began rolling out new mutual fund and ETF reports that are written by machines. The reports explain the rationale beyond the analyst ratings for the funds, and Morningstar says machine-generated ratings have performed as well as those from human analysts.
- Morningstar says it still needs humans to interview fund managers and understand their investment processes. But the expanded use of machines supports the idea that many knowledge workers’ jobs risk being automated over time.
Return to workplace speed round:
- Uber is opening its new San Francisco headquarters tomorrow, welcoming employees on a voluntary basis and at a maximum of 20% capacity.
- Microsoft will also begin opening its headquarters to employees on a voluntary basis tomorrow, and is encouraging a hybrid model.
- Facebook is opening its headquarters on May 10, on a voluntary basis up to 10% capacity. It won’t offer its usual free food or commuter shuttles for health reasons.
- New York City is requiring municipal employees who have been working from home to return to the office starting May 3.
- TIAA is grouping employee roles into four categories: fully remote, mostly remote, mostly on-site, and fully on-site. The financial firm will let staff know during the quarter about to start what categories are open to them—though most are allowed to work remotely through the end of the year.
- Many Wall Street firms are telling summer interns to plan on a mostly virtual experience this year.
- About 20% of executives surveyed said their companies would reduce their office space over the next 12 months.
Venture capitalists show signs of taking a tougher stand on harmful behavior. Spark Capital gave up its seat on the board of Dispo, a buzzy photo-sharing app, after sexual assault allegations against a member of its cofounder’s inner circle. The VC firm also said it would make sure that it wouldn’t profit from its investment in the startup.
- Other investors in Dispo said they would donate any profits to organizations supporting survivors of sexual assault.
It’s a model for how startup investors, who have too often enabled founders’ excesses, can use their power to draw ethical lines.
Here are some of the best tips and insights from the past week for managing yourself and your team:
- Take back lunch hour. That means recharging away from your screens in the middle of the work day and eating in peace. It’s a small step toward resisting the blurring of work and life.
- Be more realistic about your time. It’s easy to engage in magical thinking about how much you can get done in a given day or week—but the result often is you wind up behind and strung out. A better strategy is to add an extra buffer to your estimates of how much time a project might take, to accommodate the unexpected and reduce stress.
- Use experiments to figure out the best way to return to the workplace. Organizations can assign small groups of volunteers to pilot different scenarios—such as remote, hybrid, and in-office work—and then measure productivity, work satisfaction, and other outcomes. Work hours, team management approaches, and employees’ control over their arrangements can also be tested.
It’s alright to cry. About 17% of workers have cried with a colleague in the past year. That was true for 23% of health care workers and 20% of educators.
Hand sanitizer is tax deductible. The IRS issued new rules on Friday allowing taxpayers to deduct the cost of personal protective equipment, such as masks, hand sanitizer and sanitizing wipes from their taxes—though it’s subject to the relatively high thresholds for deducting medical costs.
Men in their 20s worked less because videogames got better. Researchers concluded that time spent gaming was responsible for a significant part of the 1.8-hour decrease between 2004 and 2017 in the number of weekly hours worked by American men in their 20s.
Some odd and excellent German words appeared over the past year. Among those compiled by Fast Company:
- Geisterveranstaltung— a “ghost event” such as a sports game without fans
- Klopapierhamster—a “toilet paper hamster,” or someone who hoards goods
- Coronafußgruß—a “corona foot greeting” Alltagsheld—an “everyday hero,” used to describe essential workers
The handbook for this new era of business doesn’t exist. We’re all drafting our own as we go along—and now we’d like to start doing so together. You can sign up here to receive this briefing by email.