Or better yet, should we trust chatbots?
Should we build relationships with AI bots?
Should our children?
Two recent podcasts explored issues of trust and relationships with chatbots and robots.
There’s.so.much.to.say.on.this. I’m writing up a storm elsewhere this week so I’m just parking them here for the curious. You should listen and then get your friends together for a podcast dinner to discuss it. Because it’s a wild topic sure to make for engaging conversation.
Here are two brutal quotes from an Axios post reporting on executives’ attitudes towards general pay raises and employee retraining. There were made during a conference for CEOs titled “Technology-Enabled Disruption: Implications for Business, Labor Markets, and Monetary Policy.”
“Executives of big U.S. companies suggest that the days of most people getting a pay raise are over, and that they also plan to reduce their work forces further.”
Damn. And then:
The moderator asked the panel whether there would be broad-based wage gains again. “It’s just not going to happen,” Taylor said. The gains would go mostly to technically-skilled employees, he said. As for a general raise? “Absolutely not in my business,” he said.
The CFO of AT&T also said that he doesn’t have a need for so many call center employees or guys that install their cables.
The message is pretty clear: employers don’t need you.
The idea that employees should be loyal to companies is a hold over from traditional career narratives. We’re still waiting for old school career narratives to catch up the present reality of work. But in the meantime it’s a good reminder that companies aren’t looking out for your best professional interest. Waiting for your employer to give you a raise, direct you to the next step, or reward you for your hard work – that’s not going to happen. Instead, it’s going to be up to you to figure out your next move and make sure you have the skills to get a pay upgrade. Don’t expect your employer to do it.
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.”
To be fair I’ve never wanted to travel to Mars. I’m perfectly happy with the options here on Earth. And after listening to the brilliant podcast mini-series, The Habitat, I really really really don’t want to go Mars. I’d never survive the trip.
I know this for sure now after listening to all six episodes of the The Habitat, a podcast that followed 6 NASA volunteers as they lived together in a Mars-like simulation. For one year this group lived on a volcanic surface in Hawaii, an environment picked to simulate the harsh terrain on Mars. They group isn’t allowed to go outside without suits. They live together in a small, confined environment with little private space. There are toilet issues. Personalities clash and nerves fray. Their spacesuits, the only way they can go outside on missions, are noisy and gross. The food is monotonous. There’s limited contact with the outside world. And it’s all done in the name of research.
The Habitat series is captivating storytelling. It will take you on a wild ride inside these peoples’ lives as they try to complete a full year inside the dome. Alongside their stories the Habitat also shares fascinating space history tidbits. It also raises plenty of questions about team work. It might leave you wondering how the eff anyone’s going to survive the trip to Mars with their sanity in tact.
Listen to it and then send it to your friend who insists they’d totally be down with a trip to Mars.
There’s a lot of bad career advice masquerading as good advice. Much of it stems from outdated notions about careers. Advice like “stick with a job at least two years” and “don’t job hop, it’ll hurt your resume!” is meant for old school careers where companies invested in employees. It was meant for a time when people stayed with companies 5, 10, even 15 (!) years.
This advice is dead wrong.
It keeps people in miserable jobs.
And there’s no need for it in the new world of work.
This perspective was most expertly summed up in the tweet thread below:
My first job in tech, I cried every day but stayed b/c I worried leaving at 4mos would look bad on a resume.
6 years later when it happened again, I left immediately.
Both times I moved to better companies that valued & supported me. Don’t stay somewhere shitty for your resume.
— Katie Sylor-Miller (@ksylor) May 11, 2018
If you’ve got a bad manager or work in a toxic environment, leave. I don’t care if you’re two months into a new job, if you have the means to leave, gtfo. Don’t waste your time because it’ll look bad on your resume. Don’t stick with it to tough it out. It’s not worth your time or sanity, especially if you’re earlier in your career. It’s totally ok to make a mistake. (Note: not everyone has the means to escape; this is advice for those who do)
Instead, put all your energy into leaving asap. Build a story that explains the honest reasons why you left (bad work culture is a perfectly ok reason to leave). Build relationships with people inside companies that are known for having good work cultures. Learn what you like in a manager. Ask people what their managers are like during careful informational interviewing. Read Glassdoor reviews.
But don’t stay at shitty jobs just because of the fear of being perceived as a job hopper. With the number of workers who work in the gig economy, the increase of job seekers with side hustles, a tight labor market, new job types, there’s a lot more fluidity in your career. Employers can work with job hoppers. It’s not worth it to stay.
So hey, if you’re in this position, start plotting your escape.
I saw Arlan Hamilton speak during PDX startup week but I’ve been following her for just under a year after first reading her post Dear White VCs, If You’re Reading This Its Almost Too Late. She’s a VC and she speaks all the truth and lives it when it comes to investing in diverse founders (read: people of color, LGBT founders, and women).
In 2014 venture capitalists invested nearly $1.33BILLION in 976 SEED deals. I would argue that in 2015 there needs to be something around 50 DEALS in minority-led startups. There’s an entire ecosystem of newly educated minority coders and marketers and writers and financial wizards who are brilliant and nuanced and have different backgrounds and opinions and feelings…and all of that will inevitably lead to staggering innovation and profit. If you’re still doing sound bytes for TechCrunch and VentureBeat talking about how many black friends you have, or Periscoping yourself bumpin’ that new Lil’ Wayne joint in your million $ office, but aren’t writing checks to black founders — and checks the same size as your other deals at that — you’ve dropped the ball, my friend.
If you haven’t read it skip this post and just go read that. It’s worth it.
Listening to her speak is absolutely refreshing. I legit fan girled when I saw her speak because she just nails it. She calls out the industry. She gives advice that you haven’t heard over and over again. She’s reflective. And she’s fucking funny (VCs – not exactly known for their humor). Above all she’s real and she’s actually doing the hard work to invest in underrepresented founders. So yeah, I fan girl hard for her work.
Which is why the news that her company, Backstage Capital, is now featured on Gimlet Media’s podcast, Startup, made me positively giddy. My podcast list is crowded. Listening to a VC talk isn’t really my idea of good content (the convos seem to lack all sense of personality). And my podcast list is crowded.
But I made room for this one.
Because Arlan is right. She’s right about what she’s doing. And she’s working her ass off to do it.
So put this episode in your ears. Pay attention to what Arlan is doing. Support the companies that Backstage funds.
BONUS: An apprentice at Backstage, Chacho, wrote a solid article on how to get into VC. I worked a lot with aspiring VCs at Yale SOM, coaching them on how to do it. So many students just wanted to know where the jobs are posted but VC doesn’t at all work like that. Chacho’s advice sums it up so well. So if you’re working with interested students, no matter their academic background, send this their way: Advice to Aspiring Venture Capitalists
Today I tried the Google trick to read a WSJ article, Seven Jobs Robots Will Expand, whose title is clickbait for future of work people like myself. Most of WSJ is behind a paywall but normally you can access an article through a simple Google search. But it turns out WSJ closed their Google loophole some time back. In the course of researching why they did that (to get more subscribers obvi) and new methods to get around the paywall (there aren’t any) I found something far more interesting. WSJ has applied a machine learning model to predict whether or not you’ll subscribe to their paper. Based on that score they’ll decide whether or not to show you the article you requested. Visitors are a categorized into hot, warm or cold. More on this move from NiemenLab:
Non-subscribed visitors to WSJ.com now each receive a propensity score based on more than 60 signals, such as whether the reader is visiting for the first time, the operating system they’re using, the device they’re reading on, what they chose to click on, and their location (plus a whole host of other demographic info it infers from that location). Using machine learning to inform a more flexible paywall takes away guesswork around how many stories, or what kinds of stories, to let readers read for free, and whether readers will respond to hitting paywall by paying for access or simply leaving.
This is wild. I’m off to go play with new browsers to see if I can get that clickbait article (this is the only time I ever use sad Safari).