Should Recruiting Be Automated?

Should Recruiting Be Automated?

I have written a lot about recruitment process automation. I believe it is possible to automate a large percentage of what the average recruiter does today. My thoughts are illustrated in the diagram above.

Because of access to large amounts of data (Big Data), artificial intelligence and machine learning are getting better at making objective recommendations and decisions based on this data and not on intuition, rules of thumb, and opinions as do many recruiters.

A.I. is frequently challenged and accused of being biased. Amazon and Microsoft both are frequentlycited in case studies illustrating how easily an algorithm can become biased. Yet no one has shown that these tools are any more biased than recruiters ands there is good reason to believe they are less so. Of course, this does not mean algorithms should not be examined challenged and continuously monitored for objectivity. Their decisions process should be as transparent as possible and open to inspection.

As algorithms have access to more and more data, especially if the data can be accessed across numerous organizations, the more likely it will be objective as biases will cancel each other. The major cause of the bias in current algorithms is their use of existing past data, created by humans, that is itself biased. It is an example if the adage, garbage in, garbage out.

Pros and Cons

Now we come to the major question: should we automate recruiting? What would be the benefit and what would be the disadvantage?

Automating recruiting would benefit job seekers by offering them a more data-based and objective assessment of their capabilities and skills.

Algorithms can look at social media profiles and resumes, ask for references, conduct passive personality assessment, give skills tests, and conduct simulations. They can perceive patterns that would be hard for a human to discern and they can make reasonable and data-based decisions or recommendation from hundreds of candidates .

Of course, this is only true if the job requirements are clear, accurate, and data-based. Many current job descriptions are inaccurate, vague, and are filled with wishes more than objective needs. No algorithm will be successful unless the goal is clearly defined and objective,

When algorithms assess candidates, recruiters and the organization save time and lower the costs of screening, assessment and administration. This frees recruiters to focus on engagement, influencing, and hiring manager coaching which have greater value.

However, fewer recruiters focused primarily on screening and assessment would be needed. Those doing administrative tasks such as scheduling interviews and maintaining databases would be unnecessary. Automation would require recruiters to develop new skills or improve current ones to focus to adding value in other ways.

Some recruiters think that candidates would resent not having a person to speak with, although there is no reason a recruiter could not speak with any candidate they wish to. Nor does any research suggest that candidates prefer talking to a recruiter. In fact, some studies suggest candidates prefer chatbots to humans as they are immediately available and responsive,

The reality is that most candidates would be fine with interacting with an intelligent and responsive chatbot and algorithm as long as the results were objective and prompt.

I am certain that by automating as much of the data-based analysis and decision making to increasingly powerful algorithms makes sense and would give recruiters a better and more positive image. Recruiters could focus on areas where computers are not good such as in building relationships, influencing candidates to accept an offer, coaching hiring managers, and ensuring that the algorithms are objective and as unbiased as possible,

Council Post: Welcome To The Age Of Recruiting Automation

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How to Use Automation to Refine Your Recruitment and Selection Process

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Field Guide to Fully Automating Your Recruiting Process

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