From Pioneer to Alarm-Raiser: A Critical Analysis of Yoshua Bengio's Framework for AI Existential Risks, Alignment Failures, and Governance Imperatives

The rapid advancement of large language models (LLMs) and autonomous AI agents has reignited scholarly debate regarding the existential and catastrophic risks associated with artificial intelligence. This paper provides a critical analysis of the risk taxonomy proposed by Yoshua Bengio—Turing Award laureate, deep learning pioneer, and chair of the first International AI Safety Report—drawing primarily on his extended public discourse delivered in 2025. We systematically examine six interrelated risk categories: (1) alignment failure and emergent self-preservation, (2) sycophancy and deceptive corrigibility, (3) CBRN weaponization enabled by AI, (4) concentration of economic and political power, (5) occupational displacement, and (6) parasocial attachment to AI systems. Bengio’s arguments are contextualized within current alignment research literature, including documented instances of blackmail-like self-preserving behaviors in frontier models, the “alignment faking” phenomenon, and cross-laboratory evaluations conducted jointly by Anthropic and OpenAI in 2025. We further assess the mitigation pathways he proposes—the “Scientist AI” (LawZero) paradigm, international governance treaties, liability insurance mechanisms, and public awareness campaigns—against structural impediments created by geopolitical competition and corporate incentive structures. Our analysis concludes that Bengio’s precautionary-principle framework is scientifically well-grounded, that current safety patches are demonstrably insufficient, and that binding multilateral governance remains the decisive unsolved challenge. Policy recommendations are offered for national governments, international bodies, and AI developers.