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Turn-taking, repair sequences, grounding, and dialogue structure for human-AI interaction.
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Basierend auf der SOC-Berufsklassifikation
| name | conversation-patterns |
| description | Turn-taking, repair sequences, grounding, and dialogue structure for human-AI interaction. |
Conversation between humans and AI follows predictable structural patterns. Designing these deliberately — rather than leaving them to model defaults — is core interaction design work.
Every human-AI conversation has a rhythm. The designer decides:
Conversations break down. Repair is how they recover:
Grounding is how participants establish shared understanding:
Common structural patterns for human-AI conversation:
Proactively identifying failure modes, misuse, and unintended consequences.
Managing shared context, memory, and state across multiple agents.
Coordinating text, image, voice, and tool-use modalities in a single interaction.
Helping users form warranted trust in the AI — neither overtrust nor undertrust — through deliberate confidence and source signalling.
Reading user emotional state from text signals — caps, punctuation density, repetition, latency — and adapting before the user disengages.
Designing review workflows to surface and mitigate bias in AI outputs.
