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.

中文翻译：

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知识图谱赋能受人类启发的人工智能系统

我们提出了下一代人工智能 (AI) 系统的理论驱动设计视角、挑战和应用。我们设想系统具有更强大的有意义的人类交互能力，包括结合个性化和对社会背景和意图的敏感性的社会适应性行为。将通用、常识和特定领域知识与社会文化价值观和规范以及个人认知模型相结合的个性化知识图为构建受人类启发的 AI 系统提供了基础。