Breaking Bias: Addressing Ageism in Artificial Intelligence

Ageism, a pervasive form of discrimination based on age, has become a growing concern across various fields. Artificial Intelligence (AI), despite its transformative potential, has unintentionally reinforced ageist stereotypes through flawed design, biased datasets, and implementation practices. This review delves into the complex interplay between ageism and AI, offering a thorough analysis of existing research on the subject and its consequences for older adults. It highlights significant gaps, including the underrepresentation of older individuals in datasets and the absence of age-inclusive design standards, which perpetuate algorithmic biases. Ethical principles, policy development, and societal implications of ageist AI systems are critically assessed. Furthermore, the article proposes constructive strategies and outlines future research directions to promote equitable and inclusive AI systems. By addressing these challenges, this review aims to contribute to a fair and dignified technological landscape for all age groups.