Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

Data Carbon Ladder

Organisation(s): loughborough university

It remains the case that very few commentators across the academic and grey literatures have considered the impact of digital data practices on CO2 production. Digital decarbonization is a critical movement to address this, one that offers great potential to reduce the collective CO2 footprint, but how can the carbon cost across stages of the digital data to information to knowledge journey be captured by organizations? In response, we present the data carbon ladder.

To provide background to its interpretation, global emissions from cloud computing have been observed to range from 2.5% to 3.7% of all global greenhouse gas emissions, thereby exceeding emissions from commercial flights (about 2.4%) and other existential activities that fuel our global economy (Lavi, 2022). To put this into context, according to the Paris-based non-profit The Shift Project, emissions generated from watching 30 minutes of Netflix sum up to about 1.6 kg of CO2, equal to driving almost 6 kilometres (roughly 4 miles) in your car. However, more recent research shows that the true output should be substantially lower by now, as data centres improve their processing power. 

Given this context we present a new measurement tool—the data carbon ladder—to enable organizations to diagnose the data carbon footprint from data acquisition and along the data journey through to the analytics used (e.g. AI). The ladder represents a sequential process for completion by data engineers, data stewards, and/or data analysts.

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