Thought leadership? The most progressive recruiters will aspire to ‘thought readership’!

Does ‘thought readership’ have a place in recruitment?

In recruitment, in the battle for audience engagement, just like any other industry, thought leadership is often seen as the holy grail.

It’s the goal of every progressive recruitment business to be seen as providing expertise in its chosen area of specialisation. Sharing insights and opinions that are relevant and valuable is an essential component in the content mix that attracts clients and candidates.

But what if there was a way to further exploit the concept of ‘thought’ and use it as an integrated part of the recruitment process? What if you could use AI thought analytics to help identify candidates who are the best matches for specific roles?

One of the most innovative – and some might say controversial, areas of AI research and development is understanding the activity of the human brain to see if it is possible for computers to read emotions and minds. One leading centre for this research was the subject of a recent current affairs news program.

Taking search and selection to a new level of sophistication

To take this technology to its ultimate conclusion, in the future, recruiters may be able to provide the capability of mind reading by generating computer interpretations of candidates’ thoughts. This is because artificial intelligence (AI) is becoming increasingly sophisticated, and it is now possible to develop AI algorithms that can interpret human language and behaviour.

‘Thought readership’ could have a major impact on the recruitment process. It could be used to bring data from different sources together to help build a multi-dimensional view of a candidate. One way to consider this is as profiling and psychometric testing ‘on steroids’. For example, AI could be used to:

• Identify candidates’ hidden talents and skills – AI could be used to analyse candidates’ social media posts, blogs and other online activity to identify any hidden talents, interests or skills. This information could then be used to match candidates with job roles that are a good fit for their skills and interests.
• Understand candidate motivations – AI could be used to understand candidates’ motivations for wanting a particular job. This information could then be used to match candidates with jobs that are aligned with their goals and values.
• Predict candidate performance – AI could be used to predict how well candidates would perform in a particular job role. This information could then be used to match candidates with jobs that are a good fit for their abilities.

The drawbacks of recruiters reading candidate thoughts

In the wider world, such a capability would likely have the ability to be used as an AI lie detector. This would be a superior form of the device known as the polygraph, which is used by law enforcement and criminal justice systems around the world. This works by detecting dishonesty by measuring changes in heart rate, blood pressure, respiratory rate and sweating.

However, there are also some challenges associated with thought readership and these relate to issues that are becoming very familiar as humanity grapples with the pros and cons of AI.

• Bias – One challenge is that AI algorithms could show bias. This means the technology could be more likely to match candidates with job roles that are traditionally held by people of the same race, gender, or socioeconomic background because they may share similar thought patterns.
• Privacy – Another challenge is that ‘thought readership’ raises privacy concerns. Some people may be concerned about the idea of their thoughts being monitored and analysed by AI.

However, in general use, AI ‘thought readership’ would represent a far greater threat to personal privacy and freedom than simply detecting lies, big, or small. It is likely to be able to zero in on specific thoughts and emotions, something that has often been a recurring theme where popular culture, sci-fi and dystopia collide. This is likely to be an uncomfortable thought for pretty much everyone.

Despite these drawbacks, ‘thought readership’ has the potential to revolutionise the way that recruitment is done. By understanding candidates’ thoughts and motivations, AI could help match people with job roles that are a better fit for them. This is likely to lead to increased job satisfaction, productivity gains, and better retention.

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