CYAIMay 8

What if AI systems weren't chatbots?

arXiv:2605.0789685.5
AI Analysis

This paper provides a critical perspective for AI developers and policymakers on the societal risks of the chatbot paradigm, but it is primarily a position piece without empirical results.

The paper argues that the dominant chatbot paradigm in AI has structural downsides, including failing to meet user needs in complex contexts, contributing to deskilling and homogenization of knowledge, and causing labor displacement and environmental costs. It calls for alternative directions emphasizing pluralistic design and task-specific tools.

The rapid convergence of artificial intelligence (AI) toward conversational chatbot interfaces marks a critical moment for the industry. This paper argues that the chatbot paradigm is not a neutral interface choice, but a dominant sociotechnical configuration whose widespread adoption reshapes social, economic, legal, and environmental systems. We examine how treating AI primarily as conversational assistants has extensive structural downsides. We show how chatbot-based systems often fail to adequately meet user needs, particularly in complex or high-stakes contexts, while projecting confidence and authority. We further analyze how the normalization of chatbot-mediated interaction alters patterns of work, learning, and decision-making, contributing to deskilling, homogenization of knowledge, and shifting expectations of expertise. Finally, we examine broader societal effects, including labor displacement, concentration of economic power, and increased environmental costs driven by sustained investment in large-scale chatbot infrastructures. While acknowledging legitimate benefits, we argue that the current trajectory of AI development reflects specific value choices that prioritize conversational generality over domain specificity, accountability, and long-term social sustainability. We conclude by outlining alternative directions for AI development and governance that move beyond one-size-fits-all chatbots, emphasizing pluralistic system design, task-specific tools, and institutional safeguards to mitigate social and economic harm.

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