Could machine learning replace career coaches?

Buried at the bottom of an an HBR post titled 8 Ways Machine Learning is Improving Company Processes, is a little nugget about the ways machine learning might soon affect career planning. Machine learning could help employees in navigate their career development by providing:

Recommendations (that) could help employees choose career paths that lead to high performance, satisfaction, and retention. If a person with an engineering degree wishes to run the division someday, what additional education and work experience should they obtain, and in what order?

Could this be a career coach in the future of work? It’s a fascinating idea and I’d love to see it in practice. We’ve already seen machine learning technology take over some parts of a career advisors job. There’s even a chatbot in development that’s trying to be a career coach (let’s hope they’re better than LinkedIn’s mediocre job recommendation algorithm.) IBM uses AI to guide job seekers through their search.

A good career coach will listen to you, help you work out ideas, guide you through an ambiguous process, support you emotionally, and reflect your own words back to you. Machine learning technology can’t do this yet, in answer to my clickbait title.

But there aren’t enough good career coaches to go around. And few people can even afford a good career coach. Moreover, not every organization offers career coaching that helps employees navigate their next steps. Tools that help people navigate a world full of increasingly ambiguous career paths are mighty helpful.

Like many jobs, career coaches won’t be fully replaced by robots or artificial intelligence anytime soon. There will always be people who prefer working with people over machines. But the role of career coaches will change as new tools and technology emerge. Career coaches need to be aware of these changes. The workplace and available roles are shifting rapidly. Career coaches need to be able to coach their clients through these changes. They need to rethink outdated career advice, especially given that our job search is becoming less human. University career departments in particular need to upskill.

Today’s post is brought to you by my half way mark to 50K words for #NaNoWritMo. I’m deep into a chapter on the future of work for my book and still finding a ton of good content to write about. The challenge of course is to write about it and not just read about it. Reading is not writing, I have to remind myself a bajillion times a day.

If you’re into this type of stuff, subscribe and I’ll send you things about careers, future of work, and probably a bunch of gifs.

Where’s the discussion about employee privacy in the future of work?

In the age of big data, a measure-everything mindset is emerging. Julia Ticona, a sociologist and researcher with the Data and Society think tank in New York, says that the same types of apps that track and keep tabs on restaurant workers or delivery people 24/7 are now migrating to white-collar jobs.

But while service and manufacturing industry workers are more used to overt productivity measurements, such systems are often sold to office workers as opportunities to maximize their own productivity, she explains. “For lower wage folks, it’s about scheduling and hours,” says Ticona. “For the white collar folks, it’s about being the ‘best you.’” The inevitable future of Slack is your boss using it to spy on you

There’s so much in this article about all the ways your employer uses new technology and invasive data collection techniques to spy on you at work.  There’s even an example of a company that tracks their employees outside of work hours. Your workplace is creeping ever closer to the Circle.

So much of the future of work is focused on robots taking our jobs. But that discussion overlooks much of what’s happening outside of robots, mainly the erosion of employee privacy. The idea that companies should have the rights to all data an employee produces in the course of their workday is absurd. Employee surveillance shouldn’t be normalized. Moreover, we need more discussion about the people making decisions about what constitutes worker productivity. Who are they and how are they qualified to make these decisions? You can bet the executives and upper management aren’t being tracked like this.

I disagree that this is all inevitable. We have the power to say no to it. We have the power to teach emerging leaders how to not to use this technology or point out the potential for abuse. Employee privacy shouldn’t be a trade off for a paycheck. Employees have the power to ask questions: How are you using my personal data? What data are you monitoring? What assumptions are you making about my work when you build productivity measuring algorithms?” 

Future employees have the power to ask the right questions during their job interviews. Let’s start teaching people the right questions to ask in an interview for a white collar role. How do you measure success in this role? How do you track worker productivity? How much data do you collect on your employees and what do you use it for?

We’re in the middle of a massive transition to a quantified workplace where leadership wants to measure everything in the pursuit of pure productivity. The people who are impacted most under this system must participate in shaping this transformation and pushing back.

employee privacy

The algorithm will manage you now

“Workers increasingly see assignments and wages doled out by artificial systems rather than human managers, and have to rely on AI, not HR, when things go wrong. According to tech experts, the rise of algorithms is changing not only how we earn a living, but who gets access to jobs and other opportunities — if their data checks out — or not.” – Forbes, Algorithms And ‘Uberland’ Are Driving Us Into Technocratic Serfdom

I rarely link to Forbes pieces because their ad game is excessive (even with my ad blocker) but the quote above captures the workplace transformation quite succinctly. From spying on workers, to replacing managers with AI, to using questionable data and AI insights to determine who gets hired, the world of work is changing in ways that need examining fast.

The Forbes article was referencing the book UBERLAND: How Algorithms Are Rewriting The Rules Of Work, which has just rocketed to the top of my reading list. Until then, I’m definitely looking out for the author on the podcast circuit.

 

Employee data collection and monitoring: Creepy or nah?

How much employee data collection is too much? Because it seems our employers – or at least the big corporate ones – want every single piece of your personal data. Is there any option for pushing back on your employer’s personal data grab?

From Axios:

The Kaiser Family Foundation’s annual review of employer-based insurance shows that 21% of large employers collect health information from employees’ mobile apps or wearable devices, as part of their wellness programs — up from 14% last year.

Talking to a human is going to be a luxury in the future

Alexa might be checking you into your next hotel room:

David Autor, an economist at M.I.T., says it is plausible to foresee a future in which — as airlines have done — hotels deploy humans to tend to elite guests and automated systems for everybody else. Workers generate costs well beyond their hourly wage, Professor Autor argued. They get sick and take vacations and require managers. “People are messy,” he noted. “Machines are straightforward.”

 

These are the jobs of the future and they’re already here

What are the jobs of the future and when will they get here? The answer is now.  Mya Systems makes a chatbot that conducts interviews. They work at the cutting edge of Natural Language Processing and are making waves in HR Tech spaces. (full disclosure: I contract with them to design chatbots). They’re also hiring for cutting edge jobs like this one: Language Annotator. It’s a contract role for a current student, ideally someone in the liberal arts!  They’re looking for a student with literature or philosophy background with strong communication skills and an understanding of machine learning. Bonus if they’ve got foreign language skills. This post touches my machine-learning-obsessed-and-liberal-arts-loving soul.

The job:

The jobs of the future are hybrid jobs. Hybrid jobs combine soft skills with digital skills. You’ll find hybrid jobs through out the job listings; popular hybrid jobs right now are product managers and data translators.

These are the jobs we need to train students and alumni for in order to prepare them for an automated workforce. The future of work is already here.

jobs of the future

Your employer is probably spying on you

FAQ from Teramind, a software that records, logs, and monitors employees.

Corporate America enjoys spying on its workers. According to Wired, “94 percent of organizations currently monitor workers in some way.” Even worse, you likely can’t escape it. From The Creative Ways Your Boss is Spying on You:

Try to hide from this all-seeing eye of corporate America—and you might make matters worse. Even the cleverest spoofing hacks can backfire. “The more workers try to be invisible, the more managers have a hard time figuring out what’s happening, and that justifies more surveillance,” says Michel Anteby, an associate professor of organizational behavior at Boston University. He calls it the “cycle of coercive surveillance.” Translation: lose/lose.

Last year I wrote a post called, AI is going to make your asshole manager even worse. Nothing I’ve read since then has convinced me otherwise.

Is it appropriate now to inquire during the interview stage ask what technology the company uses to spy on workers? If not now, when will it be appropriate?

Also, who monitors the executives? Who monitors the monitors?

Employees who are already living the future of work

Curious about how AI technology might change your job? The NYT offers a glimpse at how algorithms are changing traditional roles. In retail, fashion buyers who are normally tasked with making purchasing decisions, are increasingly using algorithms to do the task. These algorithms make fashion decisions and predict the next big trend, a task normally associated creative geniuses. With so much consumer data, predicting trends and stock levels is left to the machines, no intuition needed.

“Retailers adept at using algorithms and big data tend to employ fewer buyers and assign each a wider range of categories, partly because they rely less on intuition.

At Le Tote, an online rental and retail service for women’s clothing that does hundreds of millions of dollars in business each year, a six-person team handles buying for all branded apparel — dresses, tops, pants, jackets.”

The result is two-fold: the industry is using fewer buyers in the decision-making process and retailers are increasingly hiring people who can “stand between machines and customers.” The article notes that there are plenty of areas where automation can’t do the job. Negotiating with suppliers, assessing fabric transparency, and styling all need a human touch.

Instead of replacing all the humans, algorithms are changing how we work.  As a result, future roles (and managers) will demand employees who understand understand how to use algorithms to make decisions that improve the final product, while also understanding the limitations of the technology.

In the future of work (which is already here and we need a better phrase), we’re going to need a lot more of these employees.

The potential strike in Vegas is about robots taking hospitality jobs

From Gizmodo:

“I voted yes to go on strike to ensure my job isn’t outsourced to a robot,” said Chad Neanover, a prep cook at the Margaritaville, said.“We know technology is coming, but workers shouldn’t be pushed out or left behind. Casino companies should ensure that technology is harnessed to improve the quality and safety in the workplace, not as a way to completely eliminate our jobs.”

The article also cites a survey from Cognizant that reported “three-fourths of hotel operators said AI-based systems would become mainstream by 2025.”

 

Your job search is becoming less human. Here’s how to adapt.

Imagine you’re a job seeker looking for work. You submit your resume to a company’s website.

Your resume is scanned by AI that evaluates your resume against the job description. Then it compares your qualifications to a database of current employees’ qualifications. The algorithm also pulls in some publicly available data about you, like your social media profiles. It scores you based on that data and your resume. Your score puts you above the competition. Your resume isn’t reviewed by a recruiter.

Next you get a text on your phone. It’s the company and they’re asking if you have time to answer a few questions. You answer a few basic questions about your professional experience and interest in the role. You realize it’s a chatbot half way through but you’re just happy to avoid the awkward phone interview.

You make the cut again. You receive an automated email with a link to an online video interview platform and instructions. You record your answer to the interview questions. It’s awkward to stare at yourself on the screen. There are no visual or verbal cues to see how your answers land. Your responses are recorded. An algorithm analyzes the video, reviewing your micro expressions and looking at 25,000 possible data points to evaluate your personality and fit within the company. Your video response is scored by the algorithm.

Then you get an email from the recruiter. You’ve passed all the steps. They’d like to invite your for a day in the life experience at their company.

The visit is the first and last opportunity you’ll have to interact with a person in your entire job search.

Back to reality. The scenario above isn’t totally hypothetical. It’s reflective of the current hiring process evolution. Companies are increasingly adopting HR tech that uses AI to automate the hiring process and make it more efficient. For example, here’s what hiring looks like at Unilever:

Candidates learn about the jobs online through outlets like Facebook or LinkedIn and submit their LinkedIn profiles — no résumé required. They then spend about 20 minutes playing 12 neuroscience-based games on the Pymetrics platform. If their results match the required profile of a certain position, they move on to an interview via HireVue, where they record responses to preset interview questions. The technology analyzes things like keywords, intonation, and body language, and makes notes on them for the hiring manager. All of this can be completed on a smartphone or tablet.

If the candidate makes it through these two steps, they are invited to a Unilever office to go through a day-in-the-life scenario. By the end of the day, a manager will decide whether they are the right fit for the job.

A fundamental shift in hiring is under way and it’s powered by machine learning. From resume screening by AI to interview chatbots to predictive analytics that determine who’s most likely to leave a job, the list of startups transforming the hiring process is long. Over half of HR tech investments in 2017 went to companies offering products and services powered by AI. Companies like Entelo, an AI recruiting platform, use machine learning to determine whether you’re a fit for an organization. Entelo’s knowledge base provides a few hints on how the AI will evaluate you:

The shift to automation is making the hiring process less human. As a job seeker it’s not always obvious when AI is used as part of the hiring process. You might not know if your professional qualifications are being evaluated by a human or an algorithm. To stay competitive as the hiring process evolves job seekers need to stay informed and adapt as new HR technology enters the market.

Here’s how to start.

Get curious about HR Tech

Explore the range of new HR technology that’s being used in the hiring process. Get curious about how these tools are used. Then experiment with new HR technology that also helps job seekers. Tools like Jobscan and VMOCK are valuable resources that use machine learning to help your improve your resume. There’s even a promise of a chatbot to help you navigate your career.

Next, research which companies are using machine learning for hiring so you can prepare accordingly. Right now big companies with large resume volumes are the ideal automation customers. Smaller businesses and startups aren’t using them as much yet. Some HR tech products list which companies use their services. Before you apply to a job, email a recruiter or ask a current employee about their hiring process so you know up front whether you’ll be engaging with a machine or a human.

600+ companies in 140 countries use HireVue.

Be prepared to go beyond resumes

The resume isn’t going away any time soon but the application process is evolving to evaluate you on more than your resume. Instead of submitting a resume, candidates are taking part in hiring assessments like Pymetrics, a collection of that neuroscience games that “collect millions of data points, objectively measuring cognitive and personality traits.” Tools like Entelo assess your social media data as part of the application process:

AI Recruiting on Entelo

Creating professional content so the HR bots can find and evaluate you could make you a more competitive candidate than a resume alone. Start by producing small bits of content online. Create a personal website, show off a portfolio online, write short blog posts, or share articles on Twitter related to your professional interests to be seen by the bots.

Ask hard questions about AI and HR technology 

There are plenty of ethical questions we need to ask about AI and reinforcing bias in recruiting. Job seekers can contribute by asking hard questions too. Sometimes it’s as simple as asking how.

How do algorithms score candidates? How are candidates screened out of the process? How do candidates rank if they don’t have online profiles or publicly available data for algorithms to find? How would a candidate beat the AI system? How much do hiring managers trust their AI recommendations and scoring? How do these platforms reinforce existing bias?

Then ask yourself the hard questions: Are you getting all the information you need in the hiring process – company culture, opportunity for growth, management styles – to make an informed decision? Does an automated candidate experience make you more or less likely to want to work for a new company?

Become an actor

One question they get frequently, said Lindsey Zuloaga, director of data science at HireVue, is if an applicant is able to trick the A.I. Her answer: “If you can game being excited about and interested in the job, yes, you could game that with a person as well,” she said. “You’re not going to game it without being a very good actor.”

Employers seek candidates with strong soft skills. As more employers delegate emotional intelligence screening to automated tools you need to ensure you’re expressing that emotional intelligence. Start by recording yourself so you know how you look, talk, and express yourself on screen. Pay attention to your tone, body language, and facial expressions. Learn how to build your soft skills to improve your emotional intelligence. Spend more time interacting with people to improve your communication skills outside of digital environments. You might even want to take some acting or improv lessons to get comfortable showing those necessary emotions.

Cultivate those professional relationships

Will recruiters eschew a recommendation from a human in favor of their AI scoring system? Do AI hiring platforms incorporate internal recommendations into their scoring model? We don’t know. So for now we can assume that internal referrals via professional relationships might be a way to beat the algorithms (or at least, get around it). More importantly those professional relationships take on greater importance the more automated the hiring process becomes. Conversations with people inside of companies give you valuable insights. Discussions with current employers also give you a feel for company culture and management style, making up for the insights you lose in an automated process.

Sharpen your persuasion skills 

We’re not in a fully automated hiring process (yet). Job seekers still have a chance to engage with humans during their search. But the hiring process is evolving and making some career advice outdated. When you finally get in front of an employer it might not be what you expected (i.e. those behavioral interview questions you memorized might not be as relevant in the future). But one thing won’t change: once you engage with a human you still have to persuade them that you’re the best person for the job. Your job search has always been an act of persuasion. That much hasn’t changed. After you learn the new automated systems focus on building your persuasion skills. Reflect on what the companies needs and how you meet that need. Learn how to tell an engaging professional story that connects your interests to your future team’s needs. Show employers your intellectual curiosity and passion as you ask questions about the role. Seek out new conversational opportunities so you get better at engaging with people from different backgrounds.

We all need to pay attention to the way hiring is changing. With millennials looking at a lifetime of job hopping, we’re going to have adapt fast to new hiring processes. The traditional way of doing things won’t always work. As this article so cleverly points out:

“those first impressions so carefully emphasized by career coaches are now being outsourced to artificial intelligence.”