To realize large-scale socially embedded ambient intelligence systems, this paper proposes a design methodology towards society-centered design. Participatory technologies and multiagent systems are essential in the new system design perspective. Multiagent systems make it possible to test and predict the behavior of socially embedded systems. We have already developed the scenario description language, which describes interaction protocols that link agents to society. We use the virtual space, wherein agents behave under given scenarios, in explaining each step of society-centered design. The process consists of participatory simulation, where agents and human-controlled avatars coexist in virtual space to jointly perform simulations, and augmented experiment, where an experiment is performed in real space by human subjects, scenario-controlled agents, and human extras. For realizing realistic interactions between agents and humans during participatory simulations, an agent model that can reproduce human-like agent behaviors is needed. We show a direction for agent modeling based on learning from humans in actual application environments.