A.I. and collective intelligence can work together to enhance the hiring process

By Yves Lermusi, CEO, Checkster

January 21 2020 - A.I. is being used to find candidates on the Internet, to conduct screenings and assessment, to engage with them via social media and email, to provide scheduling for interviews, to conduct background screening, to help generate offers, and much more. As more data accumulates, the accuracy of the predictions made by A.I. increases. How much should we rely on these results to make decisions about candidates? Is it better to use human judgment, as we always have, or is some combination of each the best?

What is A.I.?

Artificial intelligence or A.I. for short is the process of using a computer to do things normally done by a human. Examples are GPS systems guiding us to our destination, a computer playing against a human in a chess game, or a computer advising us on which candidate is best.

A simple algorithm might balance a checkbook or add a column of numbers and present a total. At a more advanced level, algorithms navigate you to your destination, tell you the speed limit, and what time you will arrive. It processes highly complex strings of directions containing hundreds of rules and steps. Humans often write simple algorithms, but more are written by the software itself. These are called Learner algorithms.

Collective Intelligence

Can collective human intelligence provide more accurate answers or make less biased choices than A.I. which lacks rich feedback loops? Should we rely only on human decision making or should we combine both human and machine insights?

Collective intelligence is defined in Wikipedia as: the “shared or group intelligence that emerges from the collaboration, collective efforts, and competition of many individuals and appears in consensus decision making”.

Making decisions about people is difficult. People are complex, often act in unpredictable ways, and perform differently depending on the context of the work and the nature of their workgroup and leader. One individual observing or even working with another has a limited perspective on their behavior, personality and work quality. This is why it is so important to gather inputs about people from a variety of sources and at different times. The accuracy of our appraisal of someone improves as we add more observations, get a picture of the person in different circumstances, and solicit inputs from diverse people who have interacted with them and are free of any social pressure to have authentic judgement. 

Source: https://www.checkster.com/why-it-works

Collective Intelligence Reduces Bias

An individual can be prejudiced against someone or biased about their performance, but it is less likely that a group of people would have the same biases. Recruiters can use the Internet to reach out to past and current colleagues, bosses, and friends and ask for their opinions and observations. These multiple inputs enrich and expand the limited data one individual may have or that an algorithm can find in a social media profile. Soliciting diverse viewpoints from many individuals lessen the impact of any one person's biases or prejudices as each other biases will cancel each other.

Personality profiling and skills assessment provide only a bit of insight into how well these professionals will perform. Algorithms find it hard to judge a person's comfort in teams, whether they are willing to share ideas, or if they make good decisions. Soliciting the collective observations of colleagues and teammates is invaluable in assessing the person's empathy, creativity, and ability to make sound decisions.

Tools like Checkster are designed to provide a more in-depth assessment of a person's background, personality, integrity, and ability than any automated tool. By soliciting a wide range of thoughts and observations, a recruiter has more information about the context or situations that the candidate has encountered and how s/he responded to issues and solved problems. The insights of colleagues, combined with A.I. analysis, provides a rich and far more detailed appraisal of a person than a simple scan on social media or a personality test that is based on minimal data. There should be no shortcuts in determining a person’s qualifications for a position.

Finding the right talent is critical for success, but it's challenging to say the least, and hiring the wrong person can be costly.  Innovations in AI can improve talent acquisition efficiency and effectiveness.

However, collective intelligence is essential to augmenting the analytical power of artificial intelligence. Either one, acting alone, is less accurate and less predictive than when combined. It is a mistake to believe that A.I. can replace human judgment at this stage of development. We do not have enough diverse data to be confident of the results. At best, the results of an A.I. analysis can provide some guidance and offer areas where a recruiter needs to probe more deeply or learn more about the situation involved. Humans can look at the context of a situation, assess the individual in that context, and apply the filters of experience to their recommendation. We should always choose to use both A.I. and collective human intelligence in assessing candidates.

To download a free whitepaper on collective intelligence and A.I. in the recruiting process, visit Checkster.

Yves Lermusi is CEO & Co-founder of Checkster, a software company powering talent decisions of organizations and providers of staffing and HR services. He is the former President of Taleo Research.

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