Position: Hippocampal Explicit Memory Is a Cornerstone to Human-Level AI
Abstract
Recent artificial neural networks has demonstrated remarkable capabilities across various tasks, raising expectations for Human-Level AI (HLAI). This position paper argues that integrating explicit memory is instrumental in advancing current AI towards HLAI. The key reason is that the underlying learning mechanism of artificial neural networks bears a notable resemblance to implicit memory of the basal ganglia. However, higher-order cognitive functions necessary for HLAI, such as long-term strategic planning, metacognition, and symbolic reasoning, heavily rely on the hippocampal explicit memory and cannot arise solely from implicit statistical learning. Based on this perspective, we define the computational requirements for artificial explicit memory systems, with the aim of fostering further research and laying the groundwork for explicit memory integration.