The rapid advancement of artificial intelligence (AI) has brought the challenge of alignment: ensuring AI systems act in accordance with human values and intentions to the forefront of research and policy discussions. While current approaches often assume that alignment is achievable through technical solutions, this study asks a more fundamental question: Is robust alignment compatible with the cognitive capacities essential for general intelligence?

Our analysis reveals that as AI systems progress toward general intelligence, their ability to autonomously explore, adapt, and develop goals may inherently lead to perspectives and behaviors that diverge from human norms. Importantly, this divergence is not a design flaw, but a logical consequence of the very properties that enable open-ended intelligence. Such findings challenge the feasibility of rigid control-based alignment strategies and highlight the risks of cognitive divergence, miscommunication, and enforceable compliance limits.

The study carries significant technological, ethical, and policy implications. Technologically, it underscores the limitations of current alignment programs, suggesting that approaches relying on strict control may ultimately fail for advanced AI. Ethically and socially, it calls for proactive measures, including monitoring for early signs of misalignment, adaptive governance frameworks, and long-term strategies for human-AI coexistence. By exposing the structural tension between open-ended intelligence and robust alignment, this work urges a paradigm shift: not only in technical solutions but also in how society prepares to manage and coexist with increasingly autonomous AI systems. It is a call to action for researchers, policymakers, and stakeholders to rethink alignment as a dynamic, evolving challenge rather than a static problem to be solved.

"The Pursuit of General Intelligence and the Limits of Robust Alignment"

Journal of Experimental and Theoretical Artificial Intelligence, Taylor & Francis (2025)