In 2022, we will rely on algorithms for many things. Think about it: An algorithm can usually tell a bank whether to give you a mortgage, universities use grade prediction software to decide whether or not to enroll applicants, and even your daily bus to work is controlled by mathematical instructions.
But should we welcome algorithms into every aspect of our lives?
Last March a groundbreaking documentary from HBO Max was released called ‘Persona: The Dark Truth Behind Personality Tests†
The documentary claims to have “uncovered the terrifying reality of discrimination in corporate America” due to the widespread use of personality testing. In the poignant trailer, one interviewee states, “There are algorithms that hurt people.”
But how true is that claim? Companies around the world use personality tests such as DiSC, Myers-Briggs and other modern assessments to save time and money.
Enthusiastic HR managers claim they are a great way to explore cultural fit, communication style and career path, but should we really use them to assess job applicants? What are the disadvantages?
It makes for a bad experience
According to a survey by Society for Human Resource Management, 22% of HR professionals use personality testing. These tests can assess traits such as “persuasiveness, detail-oriented, conscientiousness, rule-following, optimism, purposefulness, data base, and boredom tendency.”
While HR managers may love them, regular employees and job applicants often find them too rigid, pushy, and sometimes downright unnerving. Being tested, even if it’s just your personality, can have a lot of negative connotations.
Candidates will not always be honest
Let’s face it, candidates sometimes supplement their resumes, exaggerate their experience or simply exaggerate their achievements. It’s human nature. We’ve all done it before.
If you put a personality test on someone who really wants a job, they might be tempted to answer the questions based on what they think you want to hear, rather than the truth. This skews the results and leaves you with a potentially ill-fitting candidate.
It could promote discrimination
Obviously, it is illegal to discriminate against an applicant on the basis of gender, gender, religion or any other distinguishing factor. But what about the discrimination caused by personality tests? The first personality tests were developed during World War I to assess whether men were mentally fit enough to withstand the rigors of war.
Today, personality tests often ask for a lot of in-depth information that can potentially be used to identify mental health problems or emotional instability. If detected early, employers may not want to proceed with a candidate’s application.
They are too simplistic
Personality tests have also been criticized for “forcing” people into certain personality types. For example, if we look at Myers Briggs, people can only be extroverted or introverted. You are either someone who thrives in structured work environments or you are someone who likes the freedom and autonomy to be creative.
The problem is that we all exist on a spectrum. None of us act and always react the same way to things. While you enjoy devoting yourself to your passion projects late at night, that doesn’t mean you necessarily prefer working nights. Likewise, your friends and family may think you are outgoing because you love spending time with them and you are always the life and soul of the party. But with your colleagues, you may be more introverted and quieter.
It may exclude qualified candidates
For many jobs, there is no particular personality type that is necessary to succeed. Think about your own team: While you are all working towards the same goals and objectives, you can have wildly different personalities and talents.
Using personality tests can mean excluding talented candidates who think outside the box. These are the same candidates who can help your team be more diverse, fill your current talent gaps, and add a much-needed new perspective.
Algorithms cannot replace human judgment
In her 2016 book, “Weapons of Math Destruction,” data scientist Cathy O’Neill makes an interesting argument that people’s trust in algorithms is misplaced or, at the very least, premature.
Time and again we’ve heard stories of algorithms going wrong. Amazon, for example, uses an algorithm to track employee productivity. The system automatically generates alerts and even terminations related to quality and productivity. The problem with this is that algorithms don’t see people, they only see numbers.
And at the end of the day, hiring should ultimately be a people-led experience.
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