Unbias

To remove or free from bias; to make impartial or objective. This involves actively identifying and mitigating preconceived notions, prejudices, or stereotypes that could influence judgment or decision-making. The process necessitates critical self-reflection, a willingness to consider alternative perspectives, and a commitment to evidence-based reasoning. The ultimate aim is to achieve a fair and equitable assessment or course of action, devoid of undue influence from personal feelings, preferences, or societal biases. It also involves presenting information or arguments without slanting it to favor a particular viewpoint. This can be difficult in certain contexts.

Unbias meaning with examples

• The journalist worked tirelessly to unbias their reporting, ensuring that all sides of the story were presented fairly. They interviewed various sources, meticulously checked facts, and avoided using emotionally charged language. Their goal was to provide readers with an objective understanding of the complex situation, free from any personal agenda. This also included the editing process, where the editors removed any hints of bias.
• To unbias the hiring process, the company implemented blind resume reviews. Names and identifying details were removed from applications to prevent unconscious biases from influencing the selection committee. This allowed evaluators to focus solely on the qualifications and experience of each candidate, ensuring a more equitable assessment and diverse pool of employees, which is essential for fair treatment.
• During the debate, the moderator strove to unbias the questioning, asking neutral questions that allowed each candidate to present their views. They avoided interrupting or favoring any particular speaker, and gave equal time and opportunity to respond. This approach fostered a more productive exchange of ideas and helped the audience reach their own conclusions.
• Researchers employed various statistical techniques to unbias the results of the study. They controlled for confounding variables and adjusted for known biases to ensure the conclusions were supported by the data, rather than being a consequence of extraneous influences. The methods employed made sure no data was skewed or overlooked.