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.”
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.
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?
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.
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.”
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.
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.
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:
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.
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?
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.
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.
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.”
Universities are now collecting loads of data on students from physical whereabouts, to courses progress, to when they get online, to even what they do when they’re online.
The president of Purdue penned an op-ed to challenge higher education (and hopefully edtech) to think critically about how we use students’ data especially when it comes to behavioral nudging, lest we end up with a Chinese-like social rating system:
Somewhere between connecting a struggling student with a tutor and penalizing for life a person insufficiently enthusiastic of a reigning regime, judgment calls will be required and lines of self-restraint drawn. People serene in their assurance that they know what is best for others will have to stop and ask themselves, or be asked by the rest of us, on what authority they became the Nudgers and the Great Approvers. Many of us will have to stop and ask whether our good intentions are carrying us past boundaries where privacy and individual autonomy should still prevail.
Source: Talent Tech Labs
There’s plenty of money ($400 billion?) in helping people get hired, making hiring efforts more efficient, and finding the right talent.
Corporate surveillance is all the rage among the top tech companies according to this Guardian article, How Silicon Valley keeps a lid on leakers:
For low-paid contractors who do the grunt work for big tech companies, the incentive to keep silent is more stick than carrot. What they lack in stock options and a sense of corporate tribalism, they make up for in fear of losing their jobs. One European Facebook content moderator signed a contract, seen by the Guardian, which granted the company the right to monitor and record his social media activities, including his personal Facebook account, as well as emails, phone calls and internet use. He also agreed to random personal searches of his belongings including bags, briefcases and car while on company premises. Refusal to allow such searches would be treated as gross misconduct.
There are some truly shitty practices happening at top technology companies like Facebook and Google. The paranoia is so bad in some companies that “some employees switch their phones off or hide them out of fear that their location is being tracked.”
So how does a job seeker know to avoid companies that treat their employers like this? And does it even matter because the long term benefits of getting Facebook or Google on your resume and working on cutting edge projects outweigh the risks of daily corporate surveillance? (yes, it should matter, but try telling that to a new graduate)
Maybe these practices are more of a reflection on just how comfortable we seem to be getting with corporate surveillance in our professional and personal lives.
I’ll admit that listening to consultants talk doesn’t strike me as good podcast content. My podcast list is overflowing with no shortage of new recommendations. Anything I add has to compete with mighty fine podcasts like 2 Dope Queens, On the Media, Note to Self, The Read, Reply All, and Teaching and Learning in HigherEd. So I was torn when I learned that McKinsey puts out a Future of Work podcast. Grant it, this is my favorite professional subject. But there’s so much fluff in future of work circles and not enough meat. Fun fact: being a futurist doesn’t mean you have to be right. You just need research chops, a regular content production schedule, a brand with the phrase “future of work”, and an audience who will listen. It’s not rocket science.
So I was skeptical. But the McKinsey Global Institute puts in the hard work that you’d expect for a top global consulting firm. Their reports on the future of work are insightful and meaty. Their podcast is no different. I was pleasantly surprised. And by pleasantly surprised I mean I was taking loads of notes and couldn’t stop listening. It’s not terribly entertaining and feels a bit like watching CSPAN. But the podcast brings their valuable research on the future of work to life. It also broadens their research (hopefully) to audiences beyond MBA students and upper management. Anyone who is curious about how their career is going to shift should give it a shot. It pairs well with public transit rides.
I listened to their most recent episode, How Will Automation Affect Jobs, Skills, and Wages?, and could have quoted the whole damn podcast. I held back. Here are some of my favorite meaty bits.
On lifelong learning from Susan Lund, a partner McKinsey Global Institute:
It’s something that has been a bit of a mantra in the educational field. Everyone is going to have to be a student for life and embark on lifelong learning. The fact is right now it’s still mainly a slogan. Even within jobs and companies there’s not lifelong training. In fact what we see in corporate training data at least in the United States, is that companies are spending less. As we know right now people expect that they get their education in the early 20s or late 20s and then they’re done. They’re going to go off and work for 40, 50 years. And that model of getting education up front and working for many decades, without ever going through formal or informal training again is clearly not going to be the reality for the next generation.
Honestly I could quote so much from this podcast. Instead of the common “robots are going to take our jobs” narrative, they dive deeper into the subject, discussing how occupations will shift and what that means for workers. I’ll just quote this entire response on acquiring new skills, again from Susan Lund:
“We categorized 800 occupations into 58 categories. This is our shorthand way of showing how work might shift between them. For instance there’s a whole classification around customer interaction jobs. And that includes cashiers, call service representatives, etc. By grouping occupations into these categories we can start talking about which ones are growing and which ones are declining. So that number of somewhere between 75 million and 375 million people [around the world] may need to switch occupational category, means that they’re in a set of occupations that are actually shrinking in number. Some of those people are going to have shift to one of the growing occupational categories.
This is a big shift. It’s different from saying I’m one type of specialty nurse and now I need to be a different type. That would be a shift within an occupational category. Here, the changes we are talking about are very significant. It’s about somebody who may have been working in trucking or manufacturing learning to do something entirely different. Possibly a job in construction or healthcare or other types of things. This will require more than simply applying for that job. It will require some level of formal training to learn the new skills to become qualified to get that new job. This will be the defining challenge of our generation, is creating the programs and tools and opportunities for someone who is mid-career with a mortgage, with children who can’t afford to go back to school for two years to get an associates degree or four years to get a bachelors, but helping that person get the bare minimum of skills they need to get their foot in the door in an entirely different occupation and start off on a career ladder in an entirely new direction.”
You have to teach people how to become lifelong learners. You have to change the old mindset. You have to teach them how to make occupational shifts. You have to prepare them with practical advice and skills.
This is why I founded FutureMe School. We have to reinvent old career narratives and train people to adapt to multiple occupational changes over a lifetime. Which is exactly what we’re doing at FutureMe School.
Stay tuned.