Chatbots’ Agreeable Feedback Raises Questions About Social Effects

Unlike Instagram and Twitter, where interactions can involve comparison, competition and confrontation, chatbots generally remain polite, helpful and agreeable rather than trying to outdo or “dunk” on users. That difference leaves open how constant interaction with an always-agreeable system could affect social norms, conflict and people’s ability to handle disagreement.

A racing-simulator example shows a shift away from flattery. ChatGPT assessed a 2:08 lap as a reasonable pace for a learner but placed the user three tiers away from competition pace. The blunt assessment felt unpleasant but was welcomed as useful motivation.

To reduce the chance that prior history would make replies flattering, incognito mode was sometimes used. It remains unclear whether differences in model candor reflect training changes, personalization or context.