#AIFebruary: Month in Review

Companies spend 40-60% of revenue on payroll and some of this enormous expense is driven by management decisions about recruiting, promoting and training made on gut feel. That said, HR is an area of active innovation. The growing discipline of people analytics and improved technology are just some of the ways that the function is becoming data savvy and predictive.

My goal this month was to understand more about what AI is and how it will impact HR and the future of work. My takeaways:

  1. Robots are not going to take our jobs. At least not in the near future. The most compelling applications of AI currently enhance human work. Jobs and the skill sets needed to excel in this environment will likely change, with a focus on skills that humans already excel at, like thoughtful communication and making judgment calls with complex information.
  2. The ethical implications of AI are a serious concern. There are many, many discussions on this topic but no clear guidelines have emerged.
  3. Regulation lags implementation. Similar to ethical concerns, it’s not yet clear how companies will be asked to stay compliant using AI tools.
  4. Interacting with AI can be fun! Concerns that AI leads to poor user experience or an inhuman touch seem to be unfounded for the most part. While there are complaints about highly automated recruiting processes, many platforms provide transparency and feedback at a scale that isn’t possible for traditional recruiting organizations.

Thanks for engaging in #AIFebruary. It’s been fun to hear from people interested in the topic and always amazing to find kindred hobbyists on the internet. Please continue to reach out to me with questions and comments! I’ll continue to share my thoughts on the topic here and on Twitter.

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.

How AI will impact the future of work

All February I’ve studied how AI can influence Human Resources, but a parallel and very interesting topic is how AI will impact the future of work. Here’s a prediction from HR Technologist on some ways AI will change the workplace:

  1. Recruiting. I’ve looked at this extensively this February as this is professional background.
  2. Internal communications and interactions across languages. I recently spent a work from home day alongside a friend in technical customer service. She was responding to questions from the product team in Japan and using Google Translate as the intermediary. As she said, it wasn’t perfect but it got the job done and she was able to resolve their issue across languages. This is becoming a built-in feature for employee collaboration.
  3. Streamline training and onboarding. AI can provide coaching tips in real-time. Think Gmail message auto-complete for work performance.
  4. Offer more robust problem-solving support. Beyond simplifying, AI can offer a wider view of potential solutions and approaches.
  5. Drive productivity. AI can automate tedious and repetitive actions of the workplace – meeting scheduling and review, answering common questions.
  6. Push for new regulations. Many of the areas that AI will touch are not well regulated. This will need to change as workers engage with it regularly.

AI and the candidate experience

It’s exciting to see the ways that AI can enhance recruiting capabilities, but just as important – and potentially more so – is how it impacts the job candidate’s experience. An article from last year on CNBC highlighted one candidate’s feelings of distance when interacting with an AI recruiting tool, in this case Hirevue: “It felt weird. I was kind of talking into the void.”

Anecdotally, I’ve heard a variety of reactions, more increasingly positive. As interacting with AI tools becomes a more common experience during the recruiting process, people become more comfortable with the idea that part of the process will be automated. I also suspect some generational differences; Millennials notoriously hate phone calls, and many of these AI solutions approximate a text conversation or a video chat.

A great approach to exploring these solutions is to look at the data. Are candidates less likely to continue with the recruiting process when presented with an AI tool? Do they rate their experience lower once these solutions are put in place? Individual companies can track this for themselves with some simple data collection.

Sourcing with AI: HR tech companies in the space

And now, the convergence of my two areas of interest: recruiting and AI. The companies in this space, many of which are startups, are finding novel ways to apply AI to the recruiting process. I’ll break these out into a few categories, reflecting the stages of recruiting: sourcing, assessment and candidate experience. Today I’m highlighting sourcing.

Sourcing is a natural fit for AI because it’s an expensive activity for recruiting organizations and there is so much data available on potential candidates.

In traditional talent sourcing, a recruiter (or sourcer) looks far and wide across a population to find relevant talent for an available job. Once a qualified person has been identified, the recruiter then attempts to engage this person to see if they will consider the job. There are a few obstacles here: first, the pool of potential talent may be very large and difficult to comb through; second, it may be difficult to identify best-fit candidates, and third, it may be difficult to engage or find people willing to engage.

AI is a great fit for AI because it’s a data-rich activity. Across the web, there’s social media profiles, participation on forums, articles and white papers. Content that could flag someone as a relevant fit for a job is nearly limitless. And within companies, there is plentiful data as well. Data on existing employees can suggest what skills work well for roles, and efficient mining of previous job candidates can lead to a future hire for a different job.

Here are a few companies applying AI to sourcing activities:

  • LinkedIn: A leader in recruiting technology. LinkedIn Recruiter is a popular tool for recruiting organizations and AI is at the heart of the recommendations to recruiters when they are searching for new talent pools
  • Entelo: A startup that applies predictive analytics to identify those most receptive to a job opportunity
  • Restless Bandit: Analyzes resumes within a company applicant tracking system to match top candidates to open roles

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.

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!