Description: Generational bias refers to the tendency of artificial intelligence (AI) systems to favor or discriminate against certain age groups based on the data they have been trained on. This phenomenon can manifest in various applications, from advertising to hiring processes, where algorithms may perpetuate stereotypes or prejudices associated with different generations. For instance, an AI system analyzing resumes might favor younger candidates, mistakenly assuming they possess more technological skills, while dismissing older individuals due to biases about their adaptability. This bias not only affects fairness in decision-making but can also have repercussions on individuals’ work and social lives, exacerbating inequality and exclusion. The ethics of AI development and use demand special attention to such biases, as justice and equity are fundamental principles that should guide the implementation of technologies impacting society as a whole. Identifying and mitigating generational bias is, therefore, a crucial challenge for AI developers, who must ensure that their systems are inclusive and representative of all age groups.
