Introducing a new thinking architecture for AI — “Dialectical Arbitration.” When an AI receives a complex question, it doesn’t just generate an answer — it launches a deep analysis process. First, the system creates 10+ thematic sectors (ethics, economics, technology), including a mandatory emotions sector. Within each sector, two opposing extremes engage in debate: they take turns presenting arguments and counterarguments, with each exchange counted as a unit of mental energy.
The process continues until the extremes reach consensus or hit the 200-energy limit. This “duel” yields two key metrics: the percentage of agreement between the extremes and the total energy expended. The more energy a sector consumes, the more critical that topic is for the final answer.
The process concludes with the Arbiter — a module that analyzes data from all sectors. It identifies the most contentious aspects of the problem, zones of clarity and uncertainty, and then forms a final response by weighing the significance of each sector. As a result, the user receives not just a conclusion, but a transparent view of the AI’s thinking process, complete with justification for the strengths and weaknesses of different positions.
I’m using this as a promt now. Please tell me the downsides.