This paper will add to an evolving new paradigm for financial decision-making by exploring the important roles that intuition, heuristics, and impulses play as a bridge between how the conscious and unconscious can wo...This paper will add to an evolving new paradigm for financial decision-making by exploring the important roles that intuition, heuristics, and impulses play as a bridge between how the conscious and unconscious can work together more effectively in making better decisions. Historically, the roles of financial/accounting theory and cognitive psychology have been extensively studied and documented in attempting to explain individual financial decision-making. More recently, neuroscience has made substantial contributions to learning how prospective financial decisions and outcomes affect brain activity and observed decision-making behavior. The evidence from neuroscience indicates that up to 90% of our decisions are initiated at the unconscious level, which is only beginning to be investigated in a systematic manner. Integrating these findings from multiple disciplines, including recent contributions from neuroscience, has many implications, not only with respect to personal and corporate financial decisions and how markets work, but also as an essential component in the tool box of the general decision maker.展开更多
The long-term goal of artificial intelligence （AI） is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems t...The long-term goal of artificial intelligence （AI） is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models： one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.展开更多
文摘This paper will add to an evolving new paradigm for financial decision-making by exploring the important roles that intuition, heuristics, and impulses play as a bridge between how the conscious and unconscious can work together more effectively in making better decisions. Historically, the roles of financial/accounting theory and cognitive psychology have been extensively studied and documented in attempting to explain individual financial decision-making. More recently, neuroscience has made substantial contributions to learning how prospective financial decisions and outcomes affect brain activity and observed decision-making behavior. The evidence from neuroscience indicates that up to 90% of our decisions are initiated at the unconscious level, which is only beginning to be investigated in a systematic manner. Integrating these findings from multiple disciplines, including recent contributions from neuroscience, has many implications, not only with respect to personal and corporate financial decisions and how markets work, but also as an essential component in the tool box of the general decision maker.
基金Project supported by the Chinese Academy of Engi- neering, the National Natural Science Foundation of China （No. L1522023）, the National Basic Research Program （973） of China （No. 2015CB351703）, and the National Key Research and Development Plan （Nos. 2016YFB1001004 and 2016YFB1000903）
文摘The long-term goal of artificial intelligence （AI） is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models： one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.
