Human-AI Communication

Human-AI communication refers to how people and AI systems exchange information, instructions, and feedback, including the interfaces, disclosures, and conversational norms that shape those exchanges. For enterprise governance, this matters because the way an AI system presents its outputs, states its limitations, and handles user inputs can determine whether employees rely on it appropriately or are misled into overtrusting it. Regulators and courts increasingly look at whether customers and staff were told they were interacting with an AI, and at whether the system's wording could create misleading impressions about accuracy or authority.

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ResearchGlobal2026-10-25

Research Finds AI Text Harder to Read Than Human Writing, Raising Output Quality Risk

A psycholinguistic study from the University of Texas at Austin finds that nine frontier AI models consistently produce harder-to-read text than comparable human writing. The study identifies specific structural patterns driving the gap, including longer sentence dependencies and unusual word choices. Compliance teams face direct implications for transparency obligations that require AI-generated content to be intelligible to end users.

AI output quality transparency LLM alignment human-AI communication readability output validation human oversight