We present a theoretically motivated design perspective, challenges, and applications of next-generation artificial intelligence (AI) systems. We envision systems with greater capabilities for meaningful human interaction, including socially adaptive behavior that incorporates personalization and sensitivity to social context and intentionality. Personalized knowledge graphs combining generic, common-sense, and domain-specific knowledge with both sociocultural values and norms and individual cognitive models provide a foundation for building humanity-inspired AI systems.