If you’re working in a cozy office, it’s easy to ignore the plight of Amazon warehouse workers and scroll right past their stories in your feed.
So I encourage you to watch this short clip from Frontline, not just so you understand what happens behind the scenes when you click on that purchase button. I want you to see how Amazon is shaping our workplaces.
This focus on data-driven management and efficiency over people won’t be limited to Amazon in the future. Amazon is a leader in everything they do. When they experiment with data-driven management and efficiency and it works, others will follow. From the video:
“Amazon is the cutting edge. Other warehouses are starting to adopt these technologies. Other companies are starting to do what Amazon is doing. Data collection can become the standard for all workers. You’re never good enough. You’re never able to keep up.”
Data-driven management mixed with workplace surveillance creates a brutal work environment. This shouldn’t be what we’re building for the future of work.
I don’t know what the solution is. Listen to these stories. Support unions. Don’t order Prime (or order it less). If you’re in tech, don’t use your talents to work for Amazon.
These workers don’t deserve this. This isn’t the future of work we deserve. We have the power to change it.
I spend a lot of time writing and speaking about how new technology reshapes job functions and industries. Specifically, I focus on automation tools, how they alter traditional roles, and how employees can adapt. So I’m always on the look out for new features and tools that automate something a human normally does.
This week, I noticed that LinkedIn offers a new feature: LinkedIn will write your summary for you.
My wife was on LinkedIn the other day, a place she rarely visits. She works in healthcare, isn’t job searching, and has zero reason to update her profile. As such, her profile is a barren place. But she checked in and saw this in place of her empty summary:
When she clicked to expand, she saw this:
Her first reaction was surprise followed by laughter. Though she doesn’t like writing a summary, she told me she’d never write something like that. It’s not her style.
The summary is slightly inaccurate and reads like an outdated objective statement from a resume in the 90’s. It sounds like a corporate website devoid of personality.
But that’s probably the point. A lot of professionally written LinkedIn profiles read like corporate websites. I used to work for an outplacement company that has an entire team dedicated to writing resumes (those resumes which always included an outdated objective statement, much to my disappointment (side note: objective statements are a polarizing topic in resume writing circles. I land firmly on the side of hating them with a passion)). No matter how the resume was written before the review process, they all sounded like the statement above after the resume team worked on it. Standardization is easier than personalization.
Corporate speak written by humans is very popular on LinkedIn and within the resume/LinkedIn writing community. Since this feature was likely trained on data from LinkedIn profiles, it’s not surprising to see this type of summary.
That’s not a bad thing either. Style aside, this feature is actually really helpful. If you can’t afford a professional LinkedIn writer to redo your profile, you’re in a rush, or you’re just not one for words, LinkedIn’s automated summary will most definitely do the trick for you. At the very least, it’ll get you started on writing a summary.
Writing LinkedIn summaries is hard. Writing them with flair and personality is harder. It takes practice and skill for a human to do it well. It’s impressive to see this coming from a machine yet still a good reminder machines still generally suck at creative flair and personality.
I’ve got a sweet spot for automation tools that are creeping into my former industry: career coaching. In my talks, I tell a story about how a machine came for my job when I was a global career coach at Yale School of Management. I use it to show audiences how automation tools aren’t limited to warehouses and accountants, and that we all need to adapt, even career coaches.
Career coaches do many things. They give direction. They review resumes, write cover letters and LinkedIn profiles. They listen to your stories and give you feedback. Career coaching at its heart is a people profession. It’s about relationships and communication.
It’s always a treat to guest on a podcast but I think the treat is even sweeter when the podcast is hosted by someone with a British accent. I had was thrilled to chat with Jane Barrett, Founder of Career Farm, all about our new world of work.
More than two-thirds of workers, specifically 64 percent, trust robots more than their managers…
Notably, 45 percent of workers—less than half—said managers are better than robots at understanding their feelings. Thirty-three percent believe managers are better at coaching while 29 percent said they’re better at creating work culture. However, 26 percent believe robots are better at providing unbiased information and 29 percent said they were better at problem-solving.
I don’t even know what to write about this survey and really I just feel like typing WTF over and over again. I didn’t dive into the report to see the methodology or question phrasing, so I’m taking everything surface value here. But I’m still floored.
What the hell is happening with management? I mean I’ve worked for some absolutely terrible managers. In a previous job I had a manager who stole my work and passed it off as hers, bad mouthed me to make herself look good, made my coworkers cry on the regular, and threatened to take away all the best parts of a job unless I did her pet project. She caused me all kinds of stress. And even then I didn’t wish to be managed by algorithm. I’m also firmly in the camp that AI will make managers worse.
It’s common knowledge that people leave their jobs because of bad bosses. Bad management is everywhere. But algorithms aren’t much better as bosses. Just ask the Uber and DoorDash workers how they feel about algorithms as managers. So why do so many workers think that algorithms > managers? That’s hella depressing news for managers in general.
I’m also curious who is working for robots that understand feelings. Is there some kind of virtual reality manager that’s more compassionate than a human?
I don’t have an answer to that. But workers in low wage jobs are seeing an increase in management by algorithm. From Axios:
Even the most vigilant supervisor can only watch over a few workers at one time. But now, increasingly cheap AI systems can monitor every employee in a store, at a call center or on a factory floor, flagging their failures in real time and learning from their triumphs to optimize an entire workforce.
First, the phrase “optimize an entire workforce” should strike fear into employees across workplaces. Workers are human, they aren’t designed to be optimized. They need breaks, moments to reflect, engage, connect, and encouragement from humans. They need to be human. Optimizing strips human needs from humans. The term “optimizing” masks the brutality of it.
We’ve seen what’s happened to those working in the world’s most optimized workforce, Amazon, especially people working in warehouses and as delivery drivers. We don’t need more of it.
And yet leadership is proceeding ahead as if optimization is the holy grail of the workplace. Again from Axios:
How often is an employee going out to smoke a cigarette? How long a lunch are they taking? How long are they sitting in the lunchroom?” These are the questions clients want answered with AI software, says Kim Hartman, CEO of Surveillance Secure, a D.C.-area company that installs security systems.
Hartman says his company has put in video analytics for several area retailers and restaurants that wanted to monitor their employees’ productivity.
Employee surveillance isn’t just used to keep tabs on employees – it can also be used to discipline employees. This all happens first with low-wage workers because they have less power, and less ability to push back. It’s harder to fight the system when you can’t miss a paycheck. Once these automated systems are tested, integrated, tweaked and finessed – and they’ve collected enough data – leadership will move onto automating middle-wage jobs.
I wonder what’s going to happen to all the middle managers who oversee these workforces. Where will they go? Will they be laid off? Retrained to use AI software to manage their workforce? What is a middle manager to do at this point?
At every discussion of automating workers, I wonder why we never talk automating leadership. Here’s my proposal to push back: Automate the c-suite.
The premise of using affect as a job-performance metric would be problematic enough if the process were accurate. But the machinic systems that claim to objectively analyze emotion rely on data sets rife with systemic prejudice, which affects search engine results, law enforcement profiling, and hiring, among many other areas. For vocal tone analysis systems, the biased data set is customers’ voices themselves. How pleasant or desirable a particular voice is found to be is influenced by listener prejudices; call-center agents perceived as nonwhite, women or feminine, queer or trans, or “non- American” are at an entrenched disadvantage, which the datafication process will only serve to reproduce while lending it a pretense of objectivity.
All of us are used to hearing the familiar phrase “This call is being monitored for quality assurance” when we contact customer service.
Most of us don’t give a second thought to what happens to the recording after our problem is solved.
The article above takes us in the new world of call center work, where your voice is monitored, scored by AI, and used to discipline workers.
“Reps from companies claim their systems allow agents to be more empathetic, but in practice, they offer emotional surveillance suitable for disciplining workers and manipulating customers. Your awkward pauses, over-talking, and unnatural pace will be used against them.
The more I read about workplace surveillance, the more dystopian the future of work looks. Is this really what we want? Is this what managers and leadership want?
What if we used the voice analysis on leadership. Why aren’t we monitoring and analyzing how leadership speaks to their subordinates or peers in meetings? Grant it, I don’t think that’d actually produce a healthy work environment but it only seems like a fair deal for leadership who implement and use these algorithms in their organizations.
On a related note, there’s a collection of papers out from Data & Society that seek to “understand how automated, algorithmic, AI, or otherwise data-driven technologies are being integrated into organizational contexts and processes.” The collection, titled Algorithms on the shop floor: Data driven technologies in organizational contexts, shows off the range of contexts in which new technology is fundamentally reshaping our workforce.
With companies racing to implement automated platforms and AI technology in the workplace, we need so much more of this research.
Whether you are a grocer, doctor, factory worker, or journalist. All of our jobs will soon be reshaped by automation. Some will benefit from the new work that will emerge. And others will watch their jobs disappear with no clear path to another livelihood. Managing this transition will be the defining challenge for us in the decades ahead. And we need to be ready for it.
Employee surveillance is all the rage in 2019. Advancements in facial recognition technology, wearables and sensor data, data analysis and machine learning, have created a rich product landscape that makes it easy for your employers to track you at work and outside of it.
The market for Employee (Automated) Monitoring Solutions is around $1.1 billion but analysts expect it to grow to about $3 billion by 2023. That’s a whole lot of worker spying headed our way.
Amazon is the most enthusiastic and well-known employer to embrace employee surveillance technology. They routinely subject their warehouse employees to a brutal work environment in which everyone is tracked, measured, and pushed to meet ever-increasing metrics. The mindset seems to be that any moment spent not producing – whether its going to the bathroom, saying hello to a coworker, or taking a moment to think – is money stolen from the company. The result is a hellish place, in which workers suffer from depression and injuries, creating a corporate culture of distrust.
Employee surveillance tech is hot hot hot
If you don’t work in an Amazon warehouse it’s easy to think that surveillance technology is a world a way from your workplace. But you’d be wrong. Gig economy workers are already managed by algorithm, with plenty of tracking and nudges to get workers to obey the algorithm and keep working.
In fact, companies use of employee surveillance technology is only growing:
Last year, the research firm Gartner found that more than 50% of the 239 large corporations it surveyed are using “nontraditional” monitoring techniques, including scrutinizing who is meeting with whom; analyzing the text of emails and social-media messages; scouring automated telephone transcripts; gleaning genetic data; and taking other such steps. That’s up from just 30% in 2015. And Gartner expects those ranks to reach 80% by next year. – Workplace tracking is growing fast.
Employee surveillance technology is going to make your worst manager even worse. Employers are collecting increasing amounts of data about you, both at work and outside of work. The data is fed into algorithms designed to categorize and analyze you. The result is delivered on a dashboard, accessible by your boss and leadership. The data your produce, and the decisions made based on that data, are rarely shared with with you, the employee. Sometimes your data is shared with third party companies.
Choose a company that trusts their employees and respects your private data
Now that employers are highly invested in monitoring their employees habits it’s important to know just what kind of culture you’re headed into as you search for new employment. It’s unlikely employers will play up their use of employee surveillance tech on the about page (algorithms aren’t so photogenic after all). Ensure you don’t end up working for a company culture that breeds distrust or puts your personal data into the hands of a bad manager or third parties by asking the right questions.
We all know that asking questions as the end of the interview is a smart move. It makes you look informed and engaged. Use this time to ask the hard questions about employee monitoring.
Employee surveillance interview questions
Here are the top interview questions to guide you in your search for a company that both trusts their employees and cares about your data privacy.
What is the company’s position on employee monitoring?
The future of work is not set in stone. We don’t have to trade our personal data and privacy for a job. Asking questions about data privacy and surveillance monitoring helps us push back on invasive tech and data privacy violations in the workplace. You deserve to work in a place where you aren’t monitored continuously. Find those companies and champion them.
If this article is your jam you’ll definitely like my book. It’s jam packed with upgraded career advice to navigate a new world of work. Sign up to get on the list to get notified when it’s published.
“I want people to know how powerless you feel when your income comes from a faceless app and when you open it up one morning, things are just different and you’re earning less money and there’s no boss you can talk to, you weren’t told about it, you just see your income is lower today and you just have to deal with it.”
Management by algorithm and faceless bosses, this is the future of work. Consider last week’s report from Business Insider:
“A new report indicates that the company doesn’t just track worker productivity at its warehouses — it also has a system that can automatically generate the paperwork to fire them if they’re not meeting targets.”
Companies like Uber and Amazon are leading the way for workforces managed by algorithm. They’re experimenting with the most vulnerable workers first – contractors. But you can expect them to apply what they learn to the white collar workforce next.