论文标题
在AI中快速思考
Thinking Fast and Slow in AI
论文作者
论文摘要
本文提出了一个研究方向来推进AI，从人类决策的认知理论中汲取灵感。前提是，如果我们对AI中仍然缺乏某些人类能力的原因有所了解（例如，适应性，可推广性，常识和因果推理），我们可能会通过嵌入这些因果成分来在AI系统中获得类似的能力。我们希望本文中包含的对愿景的高级描述以及我们建议考虑的几个研究问题，可以刺激AI研究社区以更好地理解人类和机器智能的精神来定义，尝试评估，评估新的方法论，框架和评估指标。
This paper proposes a research direction to advance AI which draws inspiration from cognitive theories of human decision making. The premise is that if we gain insights about the causes of some human capabilities that are still lacking in AI (for instance, adaptability, generalizability, common sense, and causal reasoning), we may obtain similar capabilities in an AI system by embedding these causal components. We hope that the high-level description of our vision included in this paper, as well as the several research questions that we propose to consider, can stimulate the AI research community to define, try and evaluate new methodologies, frameworks, and evaluation metrics, in the spirit of achieving a better understanding of both human and machine intelligence.
