You want a quick web performance win at work that’s sure to get you a promotion? Want it to only take five minutes? Then I got you. Capo.js is a tool to get your head in order. It’s based o…
A Perspective on tomorrow’s digital world - Manifesto from professional digital user associations to European decision-makers. - MANIFESTO-2024-A-perspective-on-tomorrows-digital-world-EN-Feb.2024.pdf
ecoCode : réduisons l'empreinte écologique de nos logiciels
ecoCode est un projet collectif visant à réduire l'impact environnemental des solutions numériques : baisse de la consommation énergétique, inclusivité, accessibilité...
Formation EN 301 549 et RAAM : auditer l’accessibilité numérique des applications mobiles – Access42 Formations
Cette formation à l’accessibilité numérique apporte les outils et ressources indispensables pour évaluer la conformité des applications mobiles conformément au RAAM et à la norme EN 301 549.
Document de travail - La consommation de métaux du numérique : un secteur loin d’être dématérialisé - fs-2020-dt-consommation-metaux-du-numerique-juin.pdf
Verdir l’IA : un cheval de Troie pour étendre son usage ? - AOC media
Si les problèmes publics qui entourent le développement de l’Intelligence Artificielle (IA) font souvent les gros titres (discriminations raciales, surveillance de masse, automatisation des emplois, etc), la conjonction du mouvement critique contre la tech et des activistes du climat pointe, depuis quelques années, de manière plus discrète, les effets néfastes de l’IA sur l'environnement.
Thinking about a way to estimate website energy use
In this post, I want to continue building out an incremental model, but rather than focusing on emissions calculations I want to create a model to estimate energy use.
More than 272 million new laptops are manufactured every year, making the IT industry responsible for as much greenhouse gas pollution as the entire airline industry. This equates to the IT industry contributing 2% of global carbon dioxide (CO2) emissions. Internet usage continues to rise, with more people using mobiles and tablets in their everyday … What Is The Carbon Footprint Of A Laptop? Read More »
Estimating the environmental impact of Generative-AI services using an LCA-based methodology
Generative AI (Gen-AI) represents a major growth potential for the digital industry, a new stage in digital transformation through its many applications. Unfortunately, by accelerating the growth of digital technology, Gen-AI is contributing to the significant and multiple environmental damage caused by its sector. The question of the sustainability of IT must include this new technology and its applications, by measuring its environmental impact. To best respond to this challenge, we propose various ways of improving the measurement of Gen-AI's environmental impact. Whether using life-cycle analysis methods or direct measurement experiments, we illustrate our methods by studying Stable Diffusion a Gen-AI image generation available as a service. By calculating the full environmental costs of this Gen-AI service from end to end, we broaden our view of the impact of these technologies. We show that Gen-AI, as a service, generates an impact through the use of numerous user terminals and networks. We also show that decarbonizing the sources of electricity for these services will not be enough to solve the problem of their sustainability, due to their consumption of energy and rare metals. This consumption will inevitably raise the question of feasibility in a world of finite resources. We therefore propose our methodology as a means of measuring the impact of Gen-AI in advance. Such estimates will provide valuable data for discussing the sustainability or otherwise of Gen-AI solutions in a more transparent and comprehensive way. We intend to help this discussion by differentiating in our approach between the embodied and operational impacts of Gen-AI. In this way, we can consider the sustainability of models, as we already do for equipment.