In the field of technological recruitment, it's increasingly important to promote diversity, inclusion, and accessibility for applicants. To achieve this, it's essential to recognize and avoid biases that can arise in different stages of the selection process. These biases can negatively affect objectivity and fairness in evaluating applicants, as well as limit the diversity of talents that can contribute to an organization.
Especially nowadays, where artificial intelligence (AI) is revolutionizing processes, and where we all want to automate absolutely everything, it's vital to remember that recruitment is an intrinsically human process, and letting an algorithm decide who to select for a process is to begin applying biases that can arbitrarily discriminate against qualified applicants for the position.
What are the common methodologies used in talent recruitment and selection, the biases associated with each of them, and what strategies can we use to avoid them?
Structured interviews:
Structured interviews involve asking predefined and standardized questions to all applicants. However, this approach can be subject to biases such as confirmation bias, where interviewers seek information that confirms their pre-existing expectations about a candidate, and similarity bias, which can lead to a preference for applicants who resemble the interviewers.
To avoid these biases, it is recommended to use questions based on relevant competencies and train interviewers on the importance of being impartial and objective in their evaluation.
A good strategy is to create and use evaluation scorecards, with well-defined skill or competency indicators. A well-designed scorecard allows for impartiality from anyone using it to evaluate people.
👉🏽 Create evaluation scorecards in your Get on Board ATS
Psychometric assessments:
Psychometric assessments evaluate skills, aptitudes, and personality traits. However, they can be subject to cultural biases if the tests are not validated for different contexts. Additionally, self-reporting bias can arise if applicants provide answers they consider socially desirable instead of genuine responses.
To avoid these biases, it is necessary to use validated tests adapted to different cultures, complement assessments with other evaluation methods and consider the results in conjunction with other relevant variables.
👉🏽 Learn about Get on Board's cultural fit and adaptability tests
Competency assessment:
Competency assessment focuses on the skills necessary for a position. However, evaluators can be influenced by stereotype biases, such as prejudices based on gender, race, or other characteristics, and by halo and horn effects, where a generalized positive or negative impression affects the evaluation of all competencies.
To mitigate these biases, it is crucial to establish clear evaluation criteria based on competencies, train evaluators to be impartial, and use evaluation panels to promote collective decisions.
When searching for talent on Get on Board, you can see the technical skills declared by each professional along with their level of competence and certifications, if they have any.
👉🏽 Learn about applicants' skills and their level.
Simulation exercises:
Simulation exercises, such as case studies or role-playing, can help assess practical skills. However, they can be affected by performance bias, where applicants may not behave as they would in real situations, and by subjective evaluation biases, where evaluators can be influenced by their own interpretations.
To counter these biases, realistic and relevant exercises should be designed, clear evaluation criteria (rubrics) should be established, and evaluators should be trained to be objective and aware of these potential personal biases in order to avoid them.
If the position you're looking for is in development, you can easily apply code challenges in your job postings to objectively filter your applicants.
👉🏽 How to add selection questions and code challenges to your job postings.
References and background checks:
References and background checks provide information about a candidate's past performance. However, they can be subject to selective reference bias, where candidates provide favorable and biased references, and confirmation bias, where evaluators give more weight to references that confirm their expectations.
To avoid these biases, it is important to request references from diverse sources, conduct background checks systematically, and use a structured approach in collecting and evaluating references.
In technological recruitment, we recommend first looking at each professional's portfolio or code repository before moving on to background checks. It is also important to request at least 3 names of people who have worked with the professionals within the same company (supervisor, peer, and subordinate if applicable) to have a 360-degree evaluation of the profile.
In summary
Avoiding biases in personnel recruitment and selection is essential to foster diversity, inclusion, and accessibility in the technological field. By applying strategies to avoid biases in each methodology, we can make more objective and equitable decisions, resulting in a broader and more enriching selection of talents.
By promoting diversity and inclusion, organizations benefit from greater creativity, innovation, and diverse perspectives, leading to better performance and stronger results. Improving the recruitment process is not only a step towards justice and equality but also an intelligent strategy to drive a company's success in the increasingly competitive and global technological environment.
Part of Get on Board's mission is to advance in collaborating with companies to have a more inclusive and fair recruitment process, free of biases.
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