Public perceptions of AI energy consumption: Awareness, responsibility attribution, and strategies

Engineering notes

Key topics: autonomous driving, perception. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Abstract Generative artificial intelligence (GenAI) is widely used in the gig economy and electronic markets. However, its progress incurs substantial environmental costs due to its high and constantly increasing energy consumption. As inference—the process by which GenAI generates output—accounts for a large part of this demand, individual usage patterns are becoming a key factor in understanding the overall energy footprint and a crucial prerequisite for developing effective educational strategies and policies. Drawing from the construal-level theory of psychological distance, this study explores individuals’ perceptions related to GenAI energy consumption. Based on a nationally representative sample of 1080 participants from the USA, we provide evidence that individuals are aware of GenAI-related energy consumption. Moreover, we show that, compared to household appliances, there is a diffusion of responsibility for GenAI’s energy consumption, with more emphasis placed on policy-makers and developers than on users. We also explore how individuals intend to implement pro-environmental strategies and shed light on different avenues suggested by individuals to lower energy consumption when using GenAI. We conclude with implications for theory, practice, and policymaking.

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