What are the biggest biases in Executive Search and can AI help to eliminate them?

Biases in Executive Search can negatively impact the process and result in bad hiring decisions.

They can cause overlooking qualified potentials who don't fit the stereotype of the ideal candidate for the role.

It's important to be aware of unconscious biases and ensure that the assessment process is fair and objective.

Here are some of the biggest biases to be aware of during the Executive Search.

• Confirmation Bias: a tendency to favour information that confirms one's pre-existing beliefs or opinions.
• Homophily: a tendency to prefer people who are similar to oneself. In executive search, this can result in a preference for candidates who have a similar background, education, or personality to the interviewer, regardless of their qualifications for the role.
• Stereotyping: this refers to making assumptions about a group of people based on their gender, race, ethnicity, age, or other characteristics.
• Halo Effect: a tendency to overvalue the positive qualities of a candidate and overlook their negatives. In executive search, this can result in overlooking potential red flags in a candidate's background or qualifications.
• Anchoring Bias: a tendency to give too much weight to the first piece of information received, and to be influenced by that in subsequent decisions. In executive search, this can result in being overly influenced by a candidate's initial impression or a piece of information received early in the process, and not considering all relevant information received later in the process.

It's crucial to be mindful of these biases and take steps to reduce their impact on the Executive Search process.

Can Artificial Intelligence can help to bring more objectivity?

In many cases, AI can reduce humans’ subjective interpretation of data.

It is clear that AI can quickly screen every applicant’s resume for specific requirements like a degree or a specific amount of experience. If a hiring manager has a certain bias for or against a certain university or region, that bias can be eliminated with AI. At the same time, extensive evidence suggests that AI models can embed human and societal biases and deploy them at scale as underlying data rather than the algorithm itself are most often the main source of any issues.

We asked ChatGPT and were pleased to find out it recognises the invaluable need for a “human touch” in Executive Search:

“In theory, AI can help remove biases and subjectivity from the executive search process. By relying on data and algorithms to make hiring decisions, AI can help reduce the influence of human biases in the selection process. However, it's important to keep in mind that the algorithms used by AI systems are only as unbiased as the data they are trained on, and any biases present in the training data can be reflected in the results produced by the AI system.

To ensure that AI systems are used in an unbiased and effective manner, it's important to regularly monitor and evaluate the results they produce, and to address any biases that are identified. Additionally, human oversight and involvement in the executive search process is still important to ensure that candidates are evaluated holistically, and to provide a personal touch to the recruitment process.”