arXiv:2606.10861v1 Announce Type: cross Abstract: LLM-powered chatbots are increasingly embedded in everyday workflows, raising sustainability concerns due to their energy use. Most mitigation strategies emphasize model or infrastructure efficiency, while the user-interface (UI) layer remains underexplored despite its potential to shape interaction behavior. We investigate whether sustainability-oriented UI interventions can increase users' energy awareness and encourage more energy-responsible chatbot use without reducing usability. We first conducted a baseline survey with 77 participants to
As LLM adoption accelerates, the energy consumption of these systems is becoming a critical and highly visible concern, prompting immediate research into mitigation strategies beyond just model optimization.
This research addresses a growing constraint on the scalable deployment and societal acceptance of AI, highlighting a new dimension for sustainable development in the AI sector by empowering users to make energy-conscious choices.
The focus expands from backend and model efficiency to include user-facing interventions as a viable path for reducing AI's energy footprint, potentially altering how AI products are designed and adopted.
- · AI product designers
- · Energy-efficient AI providers
- · Users concerned about sustainability
- · Energy-intensive AI services
- · Hardware-only efficiency solutions
UI/UX design principles for AI will increasingly incorporate sustainability metrics and user nudges.
Public perception of AI's environmental impact may improve as user-centric solutions gain traction, fostering broader adoption.
Energy efficiency could become a competitive differentiator in the AI market, driving innovation in both model and interface design.
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Read at arXiv cs.AI