Abstract

The rapid integration of artificial intelligence into financial markets is transform ing the architecture of investment decision-making. As algorithmic trading systems operate at increasing speed, scale, and autonomy, systemic risk may emerge not from irrational human behavior but from synchronized algorithmic rationality. This paper asks a critical question: Can AI trigger the next financial crisis, and if so, who bears responsibility? The study introduces the concept of a structural responsibility gap in AI-mediated investment environments. By distinguishing computational output from normative judgment, it argues that investment decisions inherently involve risk endorsement, value commitment, and accountability beyond probabilistic calculation. When judgment is delegated to autonomous systems, responsibility becomes layered and fragmented across developers, institutions, investors, and regulators. Through analysis of algorithmic feedback loops, synchronization dynamics, and crisis amplification mechanisms—including flash crash events—the paper demon strates how automated coordination may intensify systemic instability. To address this gap, it proposes a Hierarchical Joint Responsibility Model designed to govern delegated judgment without attributing moral agency to AI systems. The stability of algorithmic finance ultimately depends not solely on technological control, but on the structural redesign of accountability.