AI FOR HUMAN RESOURCES
Many core HR skills can already be supported by AI, such as recruitment, performance reviews, disciplinary actions, interpreting laws and even showing empathy. In the future, HR AI managers will be programmable with company values in a way that human beings could never quite match. AI HR managers will truly live the company values; they will be impartial, neutral and automatically updatable with new regulations. They will also be able to pick out the top performers with uncanny precision, based on machine learning prediction powers. This will enable companies to operate as true meritocracies, without the unconscious bias that holds back women and ethnic minorities. AI HR managers, in short, will be the perfect company ambassador.
Recruitment
AI is already being used in recruitment and job selection for the US Navy. The University of Memphis LIDA (Learning Intelligent Distribution Agent) performs several HR tasks for the US Navy, as described below:
“She selects jobs to offer a sailor, taking into account the Navy’s policies, the job’s needs, the sailor’s preferences and her own deliberation about feasible dates. Then she negotiates with the sailor, in English, via iterative emails, about job selection, . . . [and] answers the only question there is for sailors, “What do I do next?”
Conducting interviews
Chatbots can conduct first-line interviews, asking candidates about their current employment status, level of satisfaction, salary, experience, skills and more.
Furhat Robotics of Sweden has created an AI robot called Tengai to con-duct interviews. The firm has spent the past four years building a humanlike computer interface that mimics the way we speak, as well as our subtle facial expressions. The idea, according to chief scientist Gabriel Skantze, is that “it feels much less scary or strange compared to a more traditional robot.”
Since October 2018, the start-up has been collaborating with one of Sweden’s largest recruitment firms, TNG. The goal is to offer candidates job interviews that are free from any of the unconscious biases.
Performance reviews
Supervised learning can be used to learn existing company performance standards and highlight some performers for attention.
Company sentiment analysis
AI for HR is also used to report on company mind-set. While this can be done qualitatively, this is an inherently subjective method. If the company uses one method of communication more or less exclusively, such as email, Skype, Slack or IRC, natural language processing tools and sentiment analysis can be employed to quantify employee mood and highlight positive or negative influencers.
Automating processes
The automation of business processes like HR ticketing can be completed through a shared-service function or the development of insights, and dashboards would be provided to the business.
AI will be valuable in automating repetitive recruiting tasks such as:
- Sourcing resumes: Manually screening resumes is still the most time-consuming part of recruiting, especially when 75 percent to 88 percent of the resume holders who apply for a position are unqualified.
- Scheduling interviews
- 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. Speeding up these parts of recruiting through automation reduces time to hire, which means you’ll be less likely to lose the best talent to faster-moving competitors.
AI for HR: Best practice model
HR is clearly a function where machines can augment human work, raising productivity and enhancing effectiveness. The future for the HR function will include the combination and manifestation of these tools into fully automated HR AI managers (HAIMS), who will do much of the work of human relations (performance assessment, regulatory and legal considerations, recruitment, empathy and more). This will free up HR professionals to be more strategic, resolve ambiguities, and build personal relationships. With the time consuming administrative work done by AI, HR professionals can focus on higher order challenges.
CASE STUDY: AI FOR HR
UNILEVER HR’S EMPLOYEE RECRUITMENT PROCESS
The consumer goods giant was looking for a way to diversify its 170,000-person workforce. HR determined that it needed to focus on entry-level hires and then fast-track the best into management. But the company’s existing processes weren’t able to evaluate potential recruits in sufficient numbers—while giving each applicant individual attention—to ensure a diverse population of exceptional talent.
Here’s how Unilever combined human and AI capabilities to scale individualized hiring. In the first round of the application process, candidates are asked to play online games that help assess traits, such as risk aversion. These games have no right or wrong answers, but they help Unilever’s AI figure out which individuals might be best suited for a particular position. In the next round, applicants are asked to submit a video in which they answer questions designed for the specific position they’re interested in. Their responses are analyzed by an AI system that considers not just what they say but also their body language and tone. The best candidates from that round, as judged by the AI, are then invited to Unilever for in-person interviews, after which humans make the final hiring decisions.
Outcomes: The time reviewers spent on applications declined 75 percent, and there was a more diverse base of new hires coming from a more diverse set of 2,600 universities, a substantial increase over the previous 840. Rather than coming just from the top universities, which we are programmed to think are the best, the AI removed this bias and evaluated candidates on overall data. This meant many candidates from other universities, who would have been excluded, were instead included. This produced a more diverse set of candidates.