Thoughts

Impact of AI on jobs today

Last week I shared a 2013 article from Mother Jones about the fears of job automation. This week I want to share an article from LinkedIn about how this is now our reality.

This September 2018 post leans on LinkedIn data and the World Economic Forum Future of Jobs report to show some trends of the entrance of AI across industries.

An interesting highlight from the article is a comparison of the occupations with the highest and lowest growth over the past five years.

Image via LinkedIn

Among the highest growing jobs are Human Resources Specialist and Recruiter, which this article suggests are inherently difficult to automate and therefore less likely to see the impacts of AI.

These roles require an understanding of human behaviors and preferences—a skill set which fundamentally can’t be automated.

Igor Perisic, “How artificial intelligence is already impacting today’s jobs,” LinkedIn

I would agree that the top jobs on this list do require an understanding of human behavior that may insulate them in some ways. However, the growth of these jobs also increases the pressure to ensure they are as efficient as possible, and that is the benefit of applying AI in these fields.

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How AI can revolutionize HR

My #AIFebruary project is focused not just on learning about artificial intelligence, but also its applications in my field, HR and recruiting. With that in mind, I enjoyed these thoughts from the Forbes Human Resources Council from July. Members were asked what a future with AI might look like in our field. Some top answers:

Enhance efficiency. Stacey Browning, President of Paycor, advocates for humans and technology working together to scale a high-touch and responsive recruiting process.

Automation and a human touch don’t have to be mutually exclusive. Strategically combining them can deliver unrivaled results. In recruiting, automation’s infinitely scalable levels of efficiency mean that, regardless of the volume of candidates, each receives a timely correspondence. For candidates, being kept in the loop with a thoughtful and sincerely worded email is what makes the difference.

Stacey Browning

Reduce bias. Sherry Martin of the Denver Public School system highlights how assessments can be analyzed for bias in language and outcomes and adjusted over time to minimize adverse impact, ideally leading to a wider variety of job candidates.

Simpler sourcing. Sourcing is a popular aim for up-and-coming AI tools, and Heather Doshay at Rainforest QA talks about the impact of improving the ability to match candidates to jobs.

Sourcing is a time-intensive pain point for most talent professionals, and providing well-matched candidates to companies would significantly speed up the top of the recruiting funnel and increase the quality of hires.

Heather Doshay

Replace administrative tasks. This comment from John Feldmann at Insperity Jobs groups together the time-consuming but critical tasks that are part of nearly every recruiting process.

AI will be valuable in automating repetitive recruiting tasks such as sourcing resumes, scheduling interviews and providing feedback. This will allow recruiters and HR managers the opportunity to focus on strategic work that AI will most likely never replace, such as connecting with top talent, providing a more personalized interview experience and establishing training and mentoring programs.

John Feldmann

Stay compliant. Compliance is a critical concern in recruiting and Char Newell thinks that AI could help automate this aspect of the workload for recruiting organizations.

Defining AI

Machine learning and deep learning are two phrases that are related to AI, and I want to be clear on them before proceeding. Here’s the quickest clip I could find on Youtube to get some clarity:

Video from Acadguild tutorial on Data Science

Artificial intelligence is any code, technique or algorithm that helps a machine mimic, develop and demonstrate human behavior.

Machine learning is the techniques and processes by which machines can learn the ways of humans.

Deep learning is drawing meaningful inferences from large data sets, requiring artificial neural networks.

Deep learning is a subset of machine learning, which is a subset of artificial intelligence. These three terms are related but not interchangeable.

Robots will take our jobs

Is artificial going to displace humans? I hear this concern a lot and this article in Mother Jones does a good job articulating the reality of robot colleagues.

Illustration by Roberto Parada

I realize now that a lot of these projections about the rapid acceleration of computer learning rely on Moore’s Law – the historically-true law that computing power (in the original case, transistors) double about every two years). However, Moore’s Law may eventually break down, and outcomes of advancement don’t always match our expectation. For instance, the rise of the computer age led many to assume that paper would soon be phased out… yet we are using more of it than ever.

The most interesting section of this article was the markers we should look for if AI really is taking our jobs:

  • A steady decline in the share of the population that’s employed
  • Fewer job openings than in the past
  • Middle-class incomes flatten in a race to the bottom
  • Corporations stockpile more cash and invest less in new products and factories
  • Labor’s share of national income decline and capital’s share rise

And… hmm. A few markers there but 2019 is looking a bit better than 2013 when this article was published.

Intro to AI via cartoons

waitbutwhy.com always delivers with the thoughtful and funny

Kicking off this month with a primer on AI from waitbutwhy.com. This is from 2015, so there have probably been leaps in AI since this was written, but it is helpful as an anchor.

There are three types of AI:

  • Artificial Narrow Intelligence: We’re here now. AI that can reliably deliver better outcomes than a human brain, such as navigating with a map on your phone and getting customized music recommendations.
  • Artificial General Intelligence: This is AI that can reason and solve problems. We’re not here yet.
  • Artificial Superintelligence: This is intelligence that greatly exceeds human intelligence across all spectrums. This could be closer than we think.

This primer on AI goes into a lot of detail on the exponential increase of computing power over time as well.

When I think about AI’s applications for recruiting and HR, I think of many areas that artificial narrow intelligence is just starting to be applied. Recommendations based on past choices can be generated with existing data. And I also see the potential for recreating bias; this comes up over and over again as a concern with AI for recruiting. I’m curious to read more about how that can be addressed.

Welcome to AI February!

Having touched companies’ recruiting processes in some capacity the entirety of my career, I’ve been fascinated with the ways recruiting has evolved in that time. As a snapshot of this change, ten years ago as a new recruiter, I sometimes called an advertising agency to help post retail openings in the local newspaper. Today in recruiting operations, we use Google Analytics and tracking pixels to see performance of online postings, and programmatic advertising can automate some placement decisions.

One of the most exciting advancements in the field is artificial intelligence. Already there are HR tech startups touting their use of AI to enhance and improve the recruiting experience. The tagline is generally something about removing human bias and increasing efficiency – great arguments to move towards technology!

As a data analyst and a former recruiter, I am both excited and skeptical. Can these tools do what they promise? Do they truly apply AI or is this advanced statistics dressed up? And finally – aren’t people a critical component of the hiring practice?

To dive into some of these questions and familiarize myself with the state of AI, I’ve decided to commit my February to learning more about it. Every day throughout February, I will learn something about artificial intelligence and share it here. I’m focused on the following areas:

  • Defining artificial intelligence. What counts as artificial intelligence? What is the difference between AI and machine learning or are they interchangeable?
  • What’s the state of artificial intelligence in recruiting? Who is already doing this and how successful is it?
  • What are the promises and pitfalls of AI?

I realize that these three areas are rich enough that I could probably devote a month (or more!) to each. My intention here is to more broadly explore, though, so I’ll touch on all of these in one short month.

I’m looking forward to this month of learning and hope you follow along! Feel free to share any interesting tidbits, resources or your own interest with me here or via email or Twitter. Here’s to learning!

June: What I’m into this month

Summer is here and I’m enjoying the long hot days! Here’s what I’m into this month:

  • College reunion. It was fun to go back to Dickinson College this month and stay in the dorms with friends. It’s funny how a trip back to school can make it feel like no time has passed at all…
  • Exploring Queens. I moved to this borough almost a year ago and made a long list of places to check out. I’m slowly making my way through and finding so many great places. I visited MoMA PS1, Brooklyn Boulders Queensbridge and Citifield (thought not for the first time). I’m taking a guitar class at Queens Guitar School and after class, I’ll meet Pete to try a new restaurant in the neighborhood (Astoria). We really like Milkflower and Snowdonia.
  • Chris Guillebeau’s Side Hustle School. I love a good project and this one from Chris Guillebeau is very compelling. He’s releasing a new podcast every day in 2017 about people and their side hustles. I really love how short each one is (most are <10 minutes) and that he includes quantitative measures of success, like revenue! I’m conflicted about the push for millennials to start a side hustle (more on that another time), but I appreciate this content.
  • The Getting Things Done method from David Allen and reaching Inbox Zero. I’ve heard about this on life hack sites for years and I’m finally reading the book. I haven’t fully committed, but there are great tips for leading a more minimal and organized life.
  • Long walks. I’m trying to get 10,000 steps a day, something that’s disturbingly difficult with an office job. Now that the weather’s nice I try to walk home across Queensboro Bridge or take a walk along the waterfront if I have time after dinner. Not always possible, but great when it happens.

April: What I’m into this month

Afterward a whirlwind of travel in March, I’m enjoying a more home-bound April.

  • Lots of family time! My cousin is getting married in Pennsylvania at the end of the month, and it’s a great reason to get together with the Laffertys. I had fun exploring Philadelphia for her bachelorette party this weekend, and brunch at Harp & Crown was a perfect wrap-up. This has led to more plans for family get-togethers in 2017, like seeing Classic East in July!
  • So much music. The month kicked off with a house concert hosted by a friend and I went to Blue Note to see jazz when Autumn was in town over Easter weekend. After a six-week hiatus, I’m back to guitar lessons. I’m learning Don’t Think Twice by Bob Dylan and Diamonds and Rust by Joan Baez.
  • Continuing with the music theme, I will finally finish my listen of the first 50 albums on the 500 Greatest Albums of All Time list from The Rolling Stone. I got James Brown’s ‘Live at the Apollo’ at the library this weekend since I couldn’t find it in full on any of my typical online music sources.
  • Starting – but not finishing – lots of books. If I complete the books I’m currently reading, I’ll exceed my reading goal for the year. I’m reading tons of founder bios lately and really enjoying them.

In the meantime, I’m also working on some longer-term projects that will hopefully come to fruition in the next 3-5 months. Good start to the year!

March: What I’m into this month

I’m breaking my posting hiatus with some of the stuff I’m following this month.

  • Lots of travel. So many of my trips strangely converged this month. Spain, Houston and Scottsdale. I checked off two bucket list items this month – visiting the Alhambra and the Johnson Space Center!
  • Outer space and life coming full circle. In 2009, I went to Scottsdale to recruit for the new Barneys New York store (unfortunately now closed). While there, Buzz Aldrin was signing his new book, Magnificent Desolation, at the Louis Vuitton store in the mall. The book was a very special Christmas gift to my dad that year. This winter, while going through my mom’s bookshelves as she prepares to sell my childhood home, I found Buzz’s book. I brought it back to Scottsdale to read poolside this month. Having also seen the Saturn V rocket at the Johnson Space Center just a week before, I felt like a real superfan.
  • So much reading. I finally finished Dubliners this month and Goodreads is moving up as one of my favorite social media accounts.
  • Getting back to writing in some small ways. More to come soon.
  • Career advice from powerful women. First Ann Shoket‘s new book The Big Life and now Sallie Krawcheck’s Own It. It’s exciting to hear how they navigated their careers and the advice they have for women like me. I saw Krawcheck speak at Work-bench last week and she was riveting. She came across as very authentic and direct, and it was great to speak with her briefly as she signed my book.

It’s been a whirlwind month and I really enjoyed it. Here’s to a happy spring!

Build a Job or Find Yourself

I am fascinated with people’s career paths and have spent much of my own career focused on why people choose jobs, both as a recruiter and as a data analyst. That’s why I loved hearing this episode about finding meaning at work on The Hidden Brain.

http://www.npr.org/player/embed/471859161/471887997

This episode is an interview with Amy Wrzesniewski, a psychologist at Yale University. She says that people can be divided into three groups when it comes their approach to their job: they see it as a “job,” a “career” or a “calling.” People equally split into these groups regardless of position. Those who see their job as a calling report the greatest satisfaction. To see which group you fall into, take the quiz here.

I find this so interesting because a lot of mainstream career advice is to follow your passion. That’s so vague, and in my opinion, so wrongheaded (see Cal Newport’s brilliant take on this). It’s difficult to identify a passion at the start of a career.

As I daydream about the coming summer, I’ve been reading and listening to a lot of stories about outdoor adventures and getting away from it all to find yourself. It’s a romantic idea, but you don’t need to leave it all behind to discover your passion or find joy in the work you do. You may just need to understand your orientation towards work. (Though unfortunately, this makes for less compelling stories of self-actualization.)