AI bias can result in unfair and discriminatory outcomes, affecting important decisions in everyday life. When AI systems rely on biased data, they may treat certain groups unfairly, leading to issues in hiring, finance, healthcare, and security. Some key areas where AI bias can cause discrimination include:

• Unfair Hiring Decisions – AI used in recruitment may favour certain groups if trained on biased data (e.g., preferring male candidates over female ones)
• Bias in Facial Recognition – AI may struggle to correctly identify people from certain ethnic backgrounds, leading to unfair treatment
• Inequality in Loan Approvals – AI in banking might deny loans to specific groups if past data shows discrimination in lending practices
• Healthcare Disparities – AI used in medical diagnosis may not work as well for underrepresented groups, leading to incorrect or delayed treatment