One approach to incorporating a feedback mechanism and encouraging more balanced and fact-based conversations could be through the use of natural language processing and machine learning techniques. The AI could be trained to recognize when a user disagrees with its response and prompt the user for more information or evidence to support their claim.

For example, the AI could respond with something like, "I'm sorry to hear that you disagree with my response. Could you please provide more information or evidence to help me understand your perspective?" Based on the user's response, the AI could then adjust its own response and provide more detailed explanations or supporting evidence.

To avoid hardcoding responses, the AI could be trained using a large dataset of examples and counterexamples to help it recognize patterns and develop more nuanced responses. Additionally, the AI could be programmed to continually update its knowledge and understanding of a given topic by analyzing new information and incorporating it into its knowledge base.

Overall, developing an AI that can effectively handle disagreements and provide accurate responses in a variety of situations is a complex task, but by incorporating feedback mechanisms and using advanced machine learning techniques, it is possible to create a more flexible and responsive system.
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