Abstract:In recent years, the general model is one of the most important development trends of artificial intelligence. With the rapidly increasing research and deployment of general models, the social and ethical effects of general models have received extensive attention. Grounded in the characteristics of general models, this article analyzes the potential ethical challenges of the models at three levels:algorithm, data, and computing power. The detailed challenges include uncertainty, truthfulness, reliability, bias, toxicity, fairness, privacy, and environmental issues. Also, through the lens of philosophy of technology, it elaborates the important reasons for the ethical challenges:the "mirroring" effect and transparency problem caused by the data-driven general models' mediation between human and the world. This relation can be depicted as "human-model (data)-world". Finally, from the perspectives of governance tools and governance mechanisms, this article reviews the current countermeasures and reflects on their limitations. It is recommended to establish an open, full-process, value-embedded ethical restraint mechanism to ensure that the general model develops in accordance with legal and ethical requirements.