From Amazon and Netflix to LinkedIn and TikTok – your digital footprints offer glimpses into your personality. Algorithms can use these footprints to reveal your soft skills and suitability for a particular role, say the authors of The Future of Recruitment

What do you think reveals the most about you, your carefully curated resumé, or your online browsing habits? I think we all would agree that the latter would give any stranger an accurate picture of your unique values, characteristics and personality.

If I know that you spend a lot of time browsing and contributing to Wikipedia, as opposed to if I know you spend your time bouncing from one influencer to the next on TikTok, I can make a safe bet that you’re intellectually curious — a personality trait that is a strong predictor of job performance.

When evaluating job applicants, recruiters are evaluating a candidate on their technical skills and expertise, alongside their soft skills – or in other words, their personality. The field of industrial-organisational psychology (I-O psychology) is dedicated to identifying and measuring the personality characteristics that explain who performs at work, and who doesn’t.

Thousands of scientific studies have demonstrated that psychological qualities – such as being disciplined, curious and considerate, to name just a few – consistently predict important work outcomes, such as leadership effectiveness, innovation, and collaboration, as well as which industries or vocations would be most engaging. These findings are then used by recruiters to improve their hiring decisions and organisational performance.

Digital footprints offer new ways to evaluate applicants’ suitability

While it is somewhat easy to measure one’s technical ability, understanding whether a candidate has the ability to work alongside others, stay motivated and practice curiosity is much harder. Recruiters are often left to their intuitions (which are inadvertently biased) or rely on psychometric tests that are usually cumbersome, expensive, and often unscientific. Fortunately, new technologies powered by machine-learning and our digital footprints may offer new ways to identify top talent and evaluate the suitability of job applicants. They can also open up new job opportunities to underserved communities, save time and minimise the bias that holds many people back.

As you live and work online, you leave a large trail of digital footprints that reveals an insight into what makes you, you. The films you watch on Netflix, the things you purchase on Amazon, the TikTok influencers you follow — each provide a tiny glimpse into your personality. These footprints can be aggregated and mined by machine-learning algorithms to reveal your soft skills.

Nearly 10 years ago, researchers from Cambridge University demonstrated that your Facebook Likes could accurately predict your personality, with greater accuracy than your closest friends and family. In other words, you are what you Like. Other researchers have since expanded these findings to include Spotify playlists, Tweets, smartphone usage, and many other sources of online behaviour. So how does this impact the way organisations recruit talent?

Benefits of incorporating digital footprints into the job application process

The fundamental objective of all talent assessments is to sufficiently understand a person’s tendency to behave in a given way and infer that they will continue to do so in the future. After all, if talent is the product of the right personality in the right place, recruiters need more accurate and comprehensive tools of one’s dispositions, decision-making styles and motivations. Incorporating digital footprints into the job application process offer multiple advantages over traditional talent assessment methods:

1. User experience. Digital footprints can be analysed in seconds, as opposed to the 30 minutes or more that it takes applicants to complete a traditional talent assessment.
2. Fairness. If trained and deployed correctly, algorithm-powered talent assessments standardise the job application process. This means that all candidates are assessed against the same criteria, minimising human bias and subjectivity.
3. Diverse talent pools. Digital footprints allow for ‘one click’ job applications, and when coupled with the switch to virtual working, they can attract applications from underrepresented groups and communities. New assessment methods can reduce barriers to entry and build more inclusive organisations.
4. Accuracy. Digital footprints provide an accurate and objective measure of an individual’s disposition. By using objective behavioural data, from a variety of sources across multiple points in time, recruiters can gain an accurate insight into one’s dispositions and potential. 
5. Transparency. It is hard to understand and ‘debug’ human decision-making, it is comparatively easy to study how algorithms work. The use of algorithms in hiring contexts will lead to talent decisions that can be easily explained — another way to combat bias.

Ethical use of algorithms  

We hope that you are hearing alarm bells as you read this article. There are legitimate reasons to be concerned about the use of such data and technologies in the hiring process. As US mathematician, Cathy O’Neil, writes, algorithms that are used to evaluate people and guide human decision-making can become ‘weapons of math destruction’. In fact, we have already seen how these technologies have been used to foster social tension and inadvertently lead to biased recruiting decisions. That said, we believe it is better to be proactive about the future and guide the development of these technologies for the benefit of individuals and society. 

To ensure that the promise of alternative measures of talent can be fully realised and used ethically, it is important that the developers and users of these next-generation technologies think critically and intentionally about the following questions:

1. A lack of transparency. To what extent do applicants and recruiters know how their data is being processed, weighted and analysed by the algorithm?
2. Power asymmetry. What can be done to equalise the imbalance of power between those wielding the algorithm and those being subjected to its decisions?
3. Bias and discrimination. Can the developers and users of talent algorithms demonstrate that there is no adverse impact on the selection of minority and protected groups?
4. Privacy. Are the requested digital records relevant, made clear to the applicant, and what safeguards are being made to ensure their privacy is being protected?

Talent algorithms should not replace human agency and decisions. Instead, they are a tool to balance our intuition and subjectivity that so often leads to bad hires and wasted resources. As the way people live and work changes, so must organisations change the way they understand and recruit talent. Digital footprints show promise to be a valuable addition to the job application process, providing we can ensure that it is done with fairness, transparency and ethics.

Franziska Leutner is a Lecturer in Occupational Psychology at Goldsmiths College, University of London.
Reece Akhtar is a Co-Founder and CEO of personality assessment firm, Deeper Signals.
Tomas Chamorro-Premuzic is Professor of Business Psychology at University College London and Columbia University.

Franziska Leutner, Reece Akhtar and Tomas Chamorro-Premuzic are the authors of The Future of Recruitment: Using the New Science of Talent Analytics to Get Your Hiring Right (Emerald, 2022).