The carbon footprint of software and AI compute is rarely measured, so it cannot be managed
#00164
Running software and AI models consumes electricity whose CO2 cost varies by grid and workload, but the default toolchain reports latency, cost and accuracy and almost never emissions. Invisible to the people who could reduce it, the footprint goes unmanaged and unoptimised.
#00170Closed model and API providers do not disclose the data needed to compute a real footprint
Consumer-side tools must assume model architecture and a worldwide-average grid because providers publish almost nothing about model size, hardware, or data-centre efficiency. Every downstream estimate therefore carries wide, irreducible error bars.