Challenges with today's Centralized AI & AGI Attempts
The pursuit of Artificial General Intelligence (AGI) represents one of the most ambitious and consequential technological projects in human history. The rapid progress of large language models and related architectures has demonstrated extraordinary capabilities in natural language, reasoning, and task automation. Yet these achievements remain stepping stones, not destinations. The path toward AGI is marked by deep and unresolved challenges that span technical, economic, philosophical, and societal domains.
From a technical perspective, today’s AI systems face architectural limitations, fragility, and inefficiency. Monolithic approaches struggle to integrate diverse forms of cognition, leaving fundamental capability gaps that scaling alone cannot close. Safety and alignment remain unsolved. Reliability is still a question with models exhibiting unpredictable behaviors under normal conditions, let alone adversarial manipulation.
Beyond the technical layer, AGI raises philosophical and ethical dilemmas about representation, inclusivity, and the values embedded in intelligent systems. Whose knowledge, perspectives, and moral frameworks are reflected in AGI architectures? Whose are excluded? These questions cut to the core of legitimacy and fairness in intelligence design.
The development of AGI also intersects with economic and environmental constraints. Training and deploying large-scale models consume vast computational and energy resources, raising questions about long-term sustainability. Meanwhile, concentrated ownership of AGI risks collapsing economic mobility, centralizing wealth, and exacerbating inequality.
The societal and governance dimensions are profound. Regulatory frameworks struggle to keep pace with the speed, complexity, and opacity of AI development. Concentration of capability creates civilization wide fragilities, where single points of failure could have planetary-scale consequences. At the same time, open-source alternatives face resource and coordination barriers that limit their ability to counterbalance proprietary dominance.
Taken together, these challenges reveal that the pursuit of AGI is not a purely technical project, but a multidimensional transformation touching nearly every domain of human life. To confront it seriously, we examine the barriers across technical architectures, alignment and safety, inclusivity and ethics, economic sustainability, societal resilience, and governance capacity. Understanding these dimensions is essential for steering AGI toward futures that are not only more powerful, but also more equitable, participatory, and secure.
In the sections that follow, we will examine these challenges in greater depth. Each chapter unpacks a different dimension of challenges - technical, ethical, economic, societal, and governance. Through this, we aim to reveal how these issues interlock, why they persist, and what they imply for the future of intelligence.
Power, Representation, and Inequality in AI
Failed Remedies: Alignment, Interpretability, and the Limits of Control & Ethical Models