Organizational Cognition Beyond All Individuals

Throughout my investment career, I have developed numerous trading strategies and later introduced multi-factor models and other strategies that utilize simple machine algorithms and neural networks. These strategies statistically show a clear probabilistic advantage (higher winning odds), but after thorough research, I often could not understand why the trading system selected certain stocks. In the new development structure of the company, I have largely withdrawn from intervening in the decision-making of other investment personnel. I observed that my colleagues often made investment decisions that contradicted my cognitive understanding and expectations, or were incomprehensible to me. Yet, their subsequent results were quite successful, with some strategy modules significantly outperforming the portfolios I managed. Examples like a young mother unaware of her pregnancy being recommended baby products by online platforms or AlphaGo AI defeating nearly all human Go players demonstrate that decision-making systems created by humans can sometimes produce decisions that surpass human cognition. Based on various examples I have encountered, I firmly believe that as long as the system architecture is scientifically sound, the constructed organization can create decision-making schemes that surpass the cognition of all organizational individuals.

Under the concept of Intelligenism, the Intelligent Consortium is seen as an organizational form with an autonomous intelligence degree, likely inevitably exhibiting local or overall behaviors that exceed the cognition and understanding of most or all organizational individuals. In such a system, where operations exceed the comprehension of most or all organizational individuals, we should not feel confused or skeptical, as this may precisely be an inevitable manifestation of a higher intelligent degree. As normal humans, we cannot even fully understand all the thoughts and behavioral meanings of a pet dog or cat. When facing a higher-level neural network with humans as its neurons, we inevitably encounter situations where we cannot fully understand or feel puzzled by some or most of its behavioral outputs. Just as in the stock market, if viewed as a bottom-up neural network-like structure, an individual human, as one of tens of thousands of neurons, cannot fully comprehend the meaning expressed by the overall market trend.