Bias in AI

In the age of Artificial Intelligence (AI), as technology becomes increasingly intertwined with our daily lives, the ethical considerations surrounding its development and implementation have never been more critical. Among these considerations, three pillars stand out prominently: fairness, transparency, and human involvement. Fairness in AI pertains to the equitable treatment of all individuals, irrespective of factors such as race, gender, or socioeconomic status. Biases inherent in data or algorithms can lead to discriminatory outcomes, amplifying societal inequalities. Thus, ensuring fairness requires meticulous attention to dataset curation, algorithm design, and ongoing evaluation to mitigate bias and promote equal opportunities for all.