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:
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.
The ethical implications of AI are a serious concern. There are many, many discussions on this topic but no clear guidelines have emerged.
Regulation lags implementation. Similar to ethical concerns, it’s not yet clear how companies will be asked to stay compliant using AI tools.
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.
This article by Tracy Malingo on HR Technologist caught my attention as an interesting approach to ensure the ethical application of AI in the enterprise.
In “HR is the Ethics Model AI Needs,” Malingo makes a compelling case for placing AI under the purview of HR instead of IT. This seems like a radical notion but her arguments are solid:
HR is already tasked with steering company culture and acceptable behavior. While HR has often been the last adopters of innovation, this limits their ability to be part of creating better technology and innovative approaches to hiring, managing, developing and retaining the company’s valuable workforce.
Placing it within HR provides a system of checks and balances, since HR is incentivized to prioritize employee relations.
I’m not sure if companies will implement this, but I think it’s a proposal worth considering.
An interesting highlight from the article is a comparison of the occupations with the highest and lowest growth over the past five years.
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.
As a follow-on to my post yesterday about responsible AI, I wanted to highlight some of the risks inherent when applying AI to HR applications. Working in people analytics, I realized there are additional challenges given the sensitive data set. I imagine some of this is similar to concerns with handling analysis in healthcare given the sensitivity of people data, but some are specific to HR.
Algorithms are built on training data and learn from past behavior. Biased, discriminatory, punitive or overly hierarchical management practices could be institutionalized without additional review and management of the training data. AI systems need levers and transparency so that users know how it works and can engage it appropriately.
As with so many tools in HR, the use of people data presents a risk of data exposure.
Possible misuse of data. Management may pull development opportunities from employees predicted to leave in the next six months. A hiring manager may decide not to make an offer by someone predicted to reject an offer. AI is appealing because it can inform decisions, but false positives have real-life consequences.
Many of the companies building AI tools for HR are thinking deeply about these issues. Frida Polli, founder of pymetrics, discussed the impact on diversity and inclusion in this interview at Davos. There is great thought leadership in the space.
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:
Recruiting. I’ve looked at this extensively this February as this is professional background.
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.
Streamline training and onboarding. AI can provide coaching tips in real-time. Think Gmail message auto-complete for work performance.
Offer more robust problem-solving support. Beyond simplifying, AI can offer a wider view of potential solutions and approaches.
Drive productivity. AI can automate tedious and repetitive actions of the workplace – meeting scheduling and review, answering common questions.
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.
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.
Ethical concerns need to be at the forefront when implementing AI tools. Thankfully, people are discussing this and organizations have drafted best practices of responsible, ethical AI. Given the multitude of applications of AI, there are many issues to consider when thinking about responsibility. Focusing on HR, some clear concerns emerge:
Inherent bias in the training data. AI learns from the data it is fed. Amazon ran into this issue when exploring AI for recruiting.
Transparency in the hiring process. Companies need to be able to explain why they selected a subset of candidates for interviews, why they discarded some applications without viewing them… When AI is deployed, companies will still need to explain these decisions and will need to understand what the algorithm is targeting.
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
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.
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.
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.
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.
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.
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.