This thought-provoking issue began as part of a seminar by Professor Jeonghan Kang from the Department of Sociology at Yonsei University during the 12th Youth Leadership Workshop on GCED, which made us UX professionals reconsider our work in an era where everyone relies on AI to create personas or simulate user responses. The important question that always follows in the minds of researchers is, "How can we be sure that AI truly understands the context of that user group and is not just providing stereotypical answers?" That's why the arrival of Nemotron-Personas from NVIDIA fills this gap. Because this is not just about issuing a prompt to create floating simulated profiles, but a dataset of millions of Synthetic Personas profiles meticulously designed to reflect the complexities of demographics, culture, and local languages. And when the realism of this dataset is integrated with a process called the Deliberation Protocol, we will have a research architecture that ensures AI's responses can truly "represent" the needs of the people thru the following steps: Create realistic representatives thru the Deliberation Protocol Participants: Extracting profiles from Nemotron-Personas to serve as simulated participants helps eliminate the bias problem of general AI. We can accurately define sample groups that reflect humanity and subcultures, ensuring that the voices of all target groups, whether primary or secondary, are brought to the negotiation table. Options & Critiques: When we present tasks or Design Options to these simulated groups, they do not process them thru the central logic of AI but critique them thru the "biases and personal limitations" of their respective Personas. For example, an elderly person in rural Thailand would provide feedback on an application interface that is completely different from that of a teenager in New York. AI Mediator - the mediator who listens to every voice: When representatives with diverse backgrounds come together, conflicts are bound to arise. The AI Mediator steps in as the intermediary. However, instead of "averaging" and dismissing the needs of minority groups, the system analyzes to find the most balanced common ground, mediates the demands, and designs compromises that honor the context of all user groups, "Fair Representation". Group Statement: The outcome is UX Insights thoroughly refined. It is an answer born of debates, arguments, and the search for common ground across millions of profiles, ensuring that this direction truly "Represents" the majority of people.