Artificial Intelligence (AI) and Machine Learning (ML) are transforming industries such as healthcare, finance, education, and entertainment. However, these advancements are not benefiting everyone equally. Biases in datasets, algorithms, and design processes often lead to AI systems that unintentionally exclude or misrepresent underrepresented communities, reinforcing societal inequalities.

This talk, "AI for Everyone: Building Inclusive Machine Learning Models," explores the critical importance of developing AI systems that are ethical, fair, and accessible to all. We will examine real-world examples of AI bias, discuss techniques for identifying and mitigating bias in data and models, and explore frameworks for responsible AI development. Attendees will leave with actionable insights to design AI solutions that promote fairness, inclusivity, and social impact.