Causal Reasoning & Common Sense Understanding
One of the biggest barriers to AGI autonomy is its lack of causal reasoning and common sense—two key aspects of human intelligence. Current AI models rely on pattern recognition, but true autonomy requires understanding why events happen, not just identifying correlations. The next breakthrough will come from causal AI frameworks and neural-symbolic approaches, allowing AGI to reason about cause-effect relationships, predict real-world consequences, and make decisions that align with human intuition. This will transform AI from an advanced statistical system into an entity capable of deep logical reasoning, planning, and adaptability in complex environments.