This dissertation examines how the integration of artificial intelligence (AI) systems destabilize the epistemic, institutional, and practical foundations of expert communities. Using the Go community’s response to AlphaGo—a landmark AI system developed by DeepMind—as an empirical case, I explore how human expertise is reconfigured when confronted with powerful machine intelligence. While AlphaGo’s 2016 victory over Korean Go champion Lee Sedol was globally celebrated as a milestone in AI development, this dissertation approaches the event as a site of rupture in expert knowledge, authority, and practice.Based on twelve months of ethnographic fieldwork—including over 40 interviews with Go players, AI engineers, and tournament organizers—I analyze how the Go community responded to three major challenges posed by AI systems: symbolic disruption, epistemic reorientation, and ethical breakdown. The dissertation is structured around three empirical chapters, each addressing a distinct dimension of destabilization and social responses. The first paper, Move 37 Revisited, analyzes how one specific move in the AlphaGo–Lee Sedol match was mythologized as evidence of machine creativity. Initially received as a divine or artistic gesture, “Move 37” became a symbol of AI’s surpassing of human intuition. Yet over time, that myth was quietly revised, as later analysis revealed the move’s statistical ordinariness. This chapter shows how symbolic disruptions are socially constructed, moderated, and reinterpreted over time within expert communities. The second paper, Redefining Human Experts in the Post-AI Era, investigates how Go professionals redefined their roles in response to the knowledge generated by AI. As AI systems outperformed humans in direct competition, professionals carved out new forms of relevance—as interpreters of AI logic, communicators of machine-produced strategies, and educators who could translate between humans and algorithms. Expertise, I argue, became relational and interpretive, oriented toward curating meaning rather than securing authority. The third paper, Cheating and AI Use in Go, addresses the institutional fallout of AI’s diffusion. As cheating scandals proliferated, the community struggled to enforce fair play in environments where human and AI moves were increasingly indistinguishable. This chapter demonstrates how professional communities engage in moral and regulatory work to restore the integrity of their practices under new technological conditions. Together, these chapters illuminate how destabilization and social responses are not merely a technological effect, but a situated process involving symbolic negotiation, institutional reconfiguration, and everyday labor. By treating Go not as an isolated case but as a high-resolution site of broader dynamics, this dissertation contributes to science and technology studies (STS), the sociology of professions, and critical AI studies. It argues that expertise in the age of AI must be understood not as static or obsolete, but as a dynamic, contested, and continually remade relationship between human communities and intelligent machines.