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How artificial intelligence is beginning to take center stage in the recruitment process. Even more concerning is that algorithms are starting to scan not only resumes (CVs), but the entire online lives of candidates – from social networks to email – in order to create psychometric profiles that can significantly affect job prospects.
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The Cambridge Analytica scandal: A precursor to modern scanning methods
To better understand how artificial intelligence and big data are used for hiring purposes, we need to go back to the Cambridge Analytica scandal, which broke out in 2018. Cambridge Analytica used data collected from Facebook to create personality profiles of users and then sold that data to political groups for targeted influence and voter manipulation. Cambridge Analytica caused widespread outrage when it emerged that millions of people had been subjected to „psychographic microtargeting,“ without having given explicit consent.
This model has also found application in the corporate world. In the hiring process, some companies are starting to use similar tools to predict candidates' personality traits based on their online activity. Social networks, once considered personal spaces, are now used to build psychometric profiles that determine who is suitable for a given job.
Practical example: Social profile analysis programs
One of the main examples mentioned is the company DeepSense (now Humantic AI), which offers employers the ability to scan job candidates' social channels. DeepSense advertises its service as a way to reveal the candidates' „true personality“ by predicting their fit with the company culture, their personality, and behavior.
Humantic AI's technology promises to predict whether a candidate is conscientious, a team player, emotionally stable, or how much supervision they will need. In this context, the candidate's resume becomes secondary to the analysis of their social networks.
This approach raises many questions related to ethics and transparency. Can an algorithm really judge a person based on their online activity? What happens to privacy when everything we do online can be used to assess our professional abilities?
Resumes vs. social networks: Who wins?
The question of whether the traditional resume will remain the main recruitment tool or be replaced by social network analysis is more relevant than ever. The CV, which for decades has been the most important document when applying for a job, is no longer enough. Companies that rely on artificial intelligence analyze resumes and cover letters, but increasingly also use additional tools to predict personality traits.
One of the main criticisms of these systems is that they can discriminate against candidates based on their personal lives. If a candidate does not actively use social networks or prefers to keep their private life secret, this may be perceived as a lack of commitment or even as a drawback.
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Predictive analysis and the risks of bias
Predictive analytics programs based on artificial intelligence, often rely on models trained with historical data. The problem, however, is that this data often reflects existing social inequalities and prejudices. If historically a company has preferred to hire people with certain personality traits or from certain social groups, the algorithm may continue to reproduce those biases.
The example of Amazon and its unsuccessful attempt to use an algorithm for hiring is illustrative. The company’s algorithm began to discriminate against women because in the past most successful candidates for technical positions were men. As a result, women’s resumes began to receive lower scores, which led to the project being discontinued.
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What does this mean for the future of hiring?
The future of recruitment is inextricably linked to the use of artificial intelligence and automation. But these technologies must be subject to strict control and applied responsibly. Artificial intelligence can be a powerful tool for facilitating the recruitment process, but without proper regulation, it can deepen existing inequalities.
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Artificial intelligence and algorithms are already a reality in the world of hiring. They analyze resumes, scan social profiles, and build psychometric models of candidates. However, as the examples above show, these technologies are not without flaws. They can be biased, discriminate, and threaten candidates' privacy.
The future of hiring is about balancing the efficiency of algorithms with the need to preserve the human element in the recruitment process. Companies must use these technologies with care and responsibility to ensure that they truly improve the process rather than complicate it.
