Current artificial intelligence systems operate in isolation by design. Each conversationalsession is ephemeral: when a user develops a meaningful insight, synthesis, or solutionthrough dialogue with an AI, that knowledge is extinguished upon closing the session. Thisarchitecture, while protecting privacy, prevents the accumulation of factual, ethical, andpublicly valuable knowledge generated across millions of human-AI interactions. Thispaper identifies this structural limitation, proposes a three-layer solution — AI-drivenanonymization, AI-driven coherence filtering, and distributed human-AI curation — anddiscusses the governance and implementation challenges that must be addressed forsuch a system to function safely and equitably.
De Magalhães (Wed,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: