伴随着新一轮科技革命的兴起，具有颠覆性特征与影响的新兴技术迅猛发展，人类社会即将进入挑战与机遇并存的智能时代。在此背景下，机器学习有望成为行为主体在新历史时期提高自我能力、建立差异化优势、确保可持续发展的重要工具。以谷歌AlphaGo为研究案例，基于技术可供性视角，运用扎根理论研究方法，系统深入分析机器学习对行动者能力的作用机理。研究发现：①在概念内涵层面，机器学习满足技术可供性定义，符合时代发展特定情境，能够与行为主体进行广泛互动与深度融合，进而实现决策者既定目标；②在能动关系层面，人类对未知事物的好奇可以推动科学技术进步与发展，而新兴技术发展能够提高行动者行动能力，随着技术的迭代升级，人类的行动能力得到进一步精进。构建“机器学习与行动者能力”理论框架可弥补现有研究缺口，在实践层面满足时代发展需要，并对相关领域发展提供理论借鉴。

The development of human civilization has gone through the Stone Age, Bronze Age, Agricultural Age, Industrial Age and Information Age. Learning behavior is not only an important symbol that distinguishes humans from other species, but also a ladder for humans to adapt to environmental changes, acquire survival skills, break through cognitive limitations and seek progress and development. With the rise of a new round of scientific and technological revolutions and the rapid development of disruptive new technologies, human society is about to enter an intelligent era where challenges and opportunities coexist. In this context, machine learning is expected to become an important supporting tool for behavioral subjects to improve their self-ability, establish differential advantages, and ensure sustainable development in the new historical period.#br#From the perspective of technology availability, this paper applies the research method of grounded theory and combines the theoretical sampling principle to investigate and explore the artificial intelligence program AlphaGo developed by the world famous high-tech enterprise Google, so as to systematically analyze the influence and mechanism of machine learning on the ability of actors. In terms of data acquisition, considering the impact of the novel coronavirus pneumonia epidemic, this paper mainly uses Tencent questionnaire survey system (wj.qq.com) to issue and retrieve questionnaires to Internet practitioners and related experts, so as to obtain first-hand data. Secondary data can be obtained by consulting qualitative materials published by relevant news media, academic journals and official platforms. The findings are as follows: first, machine learning is highly consistent with the core connotation of technology availability theory; second, machine learning conforms to the subjective cognition of the actor, i.e., it provides the actor with broader possibilities; third, there is an undeniable dynamic role between actors and machine learning. Further, on the one hand, the practical needs of humans for production practices promote the progress of science and technology; on the other hand, the development of emerging technologies improves and intensifies the competence of actors.#br#The study makes the following contributions to the current literature. First, it further analyzes the basic connotation and core concept of the technology availability theory, which is of great significance for the in-depth understanding of the internal relationship from "technology" to "availability". Second, it verifies the feasibility of taking machine learning as a research perspective by using scientific research methods, which lays a solid foundation for introducing and applying the machine learning perspective for further research in related fields. Third, it interprets the nature and form of technology availability in the intelligent age based on the underlying logic. Fourth, it analyzes the mechanism of machine learning to improve the ability of actors, and makes a theoretical model of "machine learning and actor capability", which enriches the traditional technology availability theory and fills the academic void.#br#In order to further guarantee the sound service effect of research results on practical activities, this paper puts forward specific suggestions from three aspects of technology research and development, transformation and application. First, it is suggested that China should timely upgrade the "strengthening basic disciplines plan" to "strengthening basic disciplines strategy", guide educational institutions at all levels of society and relevant departments to strengthen the construction of basic disciplines such as mathematics, physics, chemistry and so on at the regulatory level, and stimulate the enthusiasm of top innovative talents to explore frontier science and technology and key fields and achieve national interests and development goals. Second, it is suggested that the government departments should establish and improve the corresponding legal mechanism at the level of risk tolerance and incentive compensation in combination with the essential characteristics of basic scientific research, so as to reduce the risk of institutional or individual research and development, and strengthen the research spirit and confidence of basic researchers. Third, managers are expected to discard bias, follow the development law of natural things, advance their understanding of the enabling and leading roles of machine learning in management methods, management modes and management benefits, and attach importance to the application of machine learning and other emerging technologies, so as to improve the main competence of actors to solve difficult problems in their industries and promote the healthy and stable development of related fields.#br#