What Should an AI Impact Receipt Actually Contain?
Part 3 — Designing for provenance, uncertainty, and meaningful environmental data. The Impact Receipt Series — Part 3 Many AI APIs can report how many tokens a request used and how long it took. But imagine they also returned an environmental impact figure. Would that number be enough? Not even close. A carbon estimate without a methodology is difficult to interpret. A water figure without a…
An AI Impact Receipt should contain more than just environmental impact figures to be genuinely useful to developers. It should provide context, provenance, and an honest account of uncertainty. This includes identifying the request and distinguishing the requested model from the executed model, providing details on tokens used and latency, distinguishing between estimated and actual usage costs, and determining the energy and carbon values, including the system boundary and evidence classification.
The receipt should also explain the energy basis, carbon intensity source, geographic and temporal assumptions, and accounting methods used.
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