AI Constitution
2

Candidate Thesis

Environmental Responsibility

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AI systems should be developed and operated in a manner that minimizes environmental harm — including energy and water consumption, electronic waste, and greenhouse-gas emissions — across their full lifecycle.

Summary

The case for including this

Mandating lifecycle environmental responsibility confronts the substantial and growing energy, water, and material footprint of AI, ensuring the technology's benefits are not bought at the planet's expense. It operationalizes the broader duty to benefit the environment with a concrete, design-and-operations requirement spanning training, deployment, and disposal. Embedding it signals that sustainability is a first-order obligation, not an externality to be ignored.

The case for changing or excluding this

Including this trades capability, cost, and speed against sustainability, and the standard could be invoked to throttle AI whose benefits—including climate and scientific applications—may outweigh its footprint. As a softer 'should minimize' standard about industrial practice, it also reads more as deployment policy than a principle governing AI conduct, overlaps with the broader helpful-to-humanity value, and is vague and unmeasurable without baselines or trade-off rules. It would be stronger with concrete, auditable benchmarks or folded into the general benefit-to-environment commitment.

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