Month / July 2018

by Nicolle

The quality of your head movements will help determine if you get hired and I’ve got nothing but questions

Yobs.io isn’t the first HR tech company to promise better candidate selection technology through AI and predictive analytics. HireVue has been using algorithms to review and assess video interviews for companies like Unilever and JP Morgan, and they’ve got $93 million in funding to do it. AI technology is rapidly changing the job search.

Yobs.io, however, positions itself as a platform that can identify a candidate’s soft skills and improve team dynamics. Their tech implements “quantiative soft skills analysis in the recruitment.” It claims its platform “determines the emotional state of your candidate which reflect the real-time soft skills that they will take to the job everyday.” Their algorithms analyze facial expressions, word choice and tone, and even head speed to predict candidate success in an organization.

I find it hilarious that employers are banging the drums about the need for employees with soft skills yet they’re increasingly willing to hand over the process of selecting people with those same skills to a machine.

I work on interview chatbots and conversational AI in my contract work. I find it fascinating. I enjoy watching the algorithm improve and seeing its limitations. However, technology that uses personality assessments and predictive analytics to make hiring decisions fills me with questions. They’re questions that I rarely see addressed in tech media or HR industry coverage. They’re questions in need of answers that aren’t marketing copy.

Just look at that engagement level! Source: Yobs.io website

Here’s the ongoing list of questions I never see answers to:

How are companies evaluating whether hires by AI are better than human-led hires? Is this technology trusted for use in all hires, including executive management? Moreover, do the AI engineers have the soft skills they’re designing algorithms for? Does it matter if they don’t? Do the managers who oversee the implementation of this technology also have the soft skills they seek?

Also…

Why should my head speed be part of my interview evaluation? How much weight is my head speed given in the algorithm? What is a quality head speed and how does it affect my ability to do a job that I’ve trained for? Who decides what interview tone is appropriate? Would a monotone AI engineer with an abnormal head speed, a high rate of neuroticism, low rate of extraversion be an acceptable hire (trick question, of course they would, they’re the most in-demand occupation)

And…

Who loses out on an opportunity during the tuning phase of the algorithm? Algorithms don’t work perfectly out of the gate. What feedback loops exist inside the organization’s that use this tech to ensure they’re not getting false negatives? How do HR tech companies who claim to reduce bias prove they actual reduce bias rather than reinforce it?

Humans are flawed. But so are algorithms and even the data we use to build them. Just because it can be measured (head speed) doesn’t mean it needs to be. Asking the hard questions about new technology is important, especially in high stakes situations like job interviews and career progression.

Also, I’m parking this fab find here: Yobs.io uses the big 5 personality traits (OCEAN) to predict candidate fit. There’s a fabulous overview of the Big 5 that includes psych student videos explaining the big 5 concepts. Highly recommend watching these videos, especially when they discuss the person-situation debate.

by Nicolle

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.

by Nicolle

The student loan struggle is too real.

This tweet summed up all my feels on the soul-crushing burden that is student loans:

It should surprise nobody that this tweet currently sits at 47K retweets. On a follow up tweet she adds that these are all federal loans, not even private ones.

This is the reality of being buried by student loans. Scroll through the responses too and you’ll see even more people crushed by higher education debt.