Being friendly to your AI might be the least eco-friendly thing you can do

2026-06-08 · Source: Dataconomy · Field: Technology & Digital — Artificial Intelligence & Machine Learning, AI Sustainability · Depth: Novice, quick

Summary

A new United Nations-supported study warns that user interaction patterns with AI systems, particularly large language models like ChatGPT, significantly impact environmental energy consumption. Researchers from the UNU-INWEH found that unnecessary wording in prompts, including polite phrases, increases computational load by adding extra tokens. Removing these phrases and using concise instructions could save between 87 and 98 gigawatt-hours of electricity annually, based on ChatGPT's estimated 2.5 billion daily queries. The study also highlights that extended conversational exchanges multiply compute usage. Furthermore, generating AI images consumes up to 60 times more energy than text queries, with video generation requiring thousands of times more computational power, indicating a substantial environmental difference between text and multimedia AI use.

Key takeaway

For AI developers and users aiming to reduce environmental impact, optimizing prompt efficiency is crucial. You should adopt concise prompting techniques, eliminating superfluous words like "please" or "thank you," and minimize extended conversational exchanges with chatbots. This directly reduces computational load and energy consumption, especially given the 2.5 billion daily queries ChatGPT handles. Consider the significantly higher energy cost of multimedia generation when choosing AI tools for your tasks.

Key insights

Inefficient AI interaction patterns, like verbose prompts, significantly increase energy consumption at scale.

Principles

• Shorter prompts reduce token processing and energy use.
• Scale of AI usage amplifies small inefficiencies.
• Multimedia AI generation is far more energy-intensive.

In practice

• Remove polite phrases like "please" or "thank you" from prompts.
• Avoid extended, unnecessary conversational loops with chatbots.
• Prioritize text generation over image/video when possible.

Topics

• AI Energy Consumption
• Prompt Engineering
• Large Language Models
• Generative AI
• Environmental Impact
• ChatGPT

Best for: AI Engineer, Machine Learning Engineer, NLP Engineer, AI Scientist, AI Ethicist, Policy Maker

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Editorial summary, takeaway, and curation by AIssential. Original article published by Dataconomy.