OpenAI CEO reveals surprising cost of politeness with ChatGPT: Saying "please" and "thank you" adds millions to electricity bills annually.
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| Is being polite to AI costing us millions? Sam Altman's comment sparks debate on human-AI interaction and resource consumption. |
Dhaka, Bangladesh - April 22, 2025:
OpenAI CEO Sam Altman has revealed a startling detail about interacting with ChatGPT: the simple act of using polite language, such as "please" and "thank you," incurs tangible financial and environmental costs for the company, according to reports. Responding to a query on X, Altman confirmed that these seemingly innocuous courteous expressions contribute to tens of millions of dollars in electricity expenses annually.
While the OpenAI chief's comment might have been delivered with a touch of jest, it throws a spotlight on the very real computational demands associated with user interactions, even those intended to mirror human politeness. The more complex and verbose the input provided to AI models like ChatGPT, the greater the processing load placed on their underlying servers. This increased processing directly translates into higher energy consumption, a cost that accumulates rapidly given the massive scale of user interactions with such popular AI tools.
The revelation has also sparked broader discussions about how society is adapting its communication patterns towards artificial intelligence. Are users instinctively applying human etiquette when interacting with AI, and what are the large-scale operational consequences of this behavior for companies like OpenAI? The initial conversation began when a user on X playfully questioned the energy expenditure associated with polite phrasing. In response, Altman quipped that such politeness was "tens of millions of dollars well spent," indicating that while OpenAI prioritizes creating human-like interactions, these come with a significant, and perhaps unexpected, price tag. Altman's remark serves not just as a casual observation but also as a window into the substantial costs inherent in operating natural language processing at scale, prompting a deeper consideration of efficiency and the environmental footprint of our increasingly AI-driven world.