• Shailesh Chauhan
• Piyush Chauhan
• Rishabh Chauhan

In modern digital ecosystems, artificial intelligence is at the core of shaping user experiences, ranging from recommendation systems to voice assistants. AI systems have been used to make the process of interacting with any system more intuitive and personalized with efficiency. As more integration of AI systems starts to happen within UX design, one of the major concerns has been the way in which socio-cultural biases can infiltrate these systems. Bias in AI systems can be caused by the data they are being trained on, the algorithms they use, or the way they have been integrated and often perpetuate harmful stereotypes or excluding certain groups. This article shall look into how AI could be used in the detection and mitigation of socio-cultural biases within UX design. We will cover where biases come from, how they are detected, and ways these biases can be mitigated to help build an even more inclusive, equitable, and diverse digital environment. We shall see, with the help of real-world case studies, data-driven insights, and best practices, how AI helps UX designers build systems that are indeed fair and respect and reflect user base diversity.

Artificial Intelligence, Algorithmic Bias, Explainable AI , AI in User Experience, Human-Centered AI, Socio-Cultural Bias

"Bias Detection in UX Design through AI: Mitigating Socio-Cultural Biases", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.g172-g187, November-2024, Available :http://www.jetir.org/papers/JETIR2411614.pdf

"Bias Detection in UX Design through AI: Mitigating Socio-Cultural Biases", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. ppg172-g187, November-2024, Available at : http://www.jetir.org/papers/JETIR2411614.pdf