Environment Community

Proposal for friendly user test

AI devours and pollutes our resources. But there is not (yet) a simple tool to assess environmental impacts. So, why are we waiting?

Together, let’s create a field tool to guide the action, before we launch into audits and certifications. Our Impact AI environment community has devised two original, pragmatic solutions that are accessible to everyone. Are you interested?

Become a “friendly user” of our innovation by testing the model, and sending us your feedback via our questionnaire.

Environment Community

Proposal for friendly user test

AI devours and pollutes our resources. But there is not (yet) a simple tool to assess environmental impacts. So, why are we waiting?

Together, let’s create a field tool to guide the action, before we launch into audits and certifications. Our Impact AI environment community has devised two original, pragmatic solutions that are accessible to everyone. Are you interested?

Become a “friendly user” of our innovation by testing the model, and sending us your feedback via our questionnaire.

Thanks

to our workshop coordinators
and contributors.

  • Ariane Thomas and Axel Rakotonoera from L’Oréal,

  • Olivier Servoise from Engie,

  • Claire Guidi from the French building federation,

  • Nicolas Marescaux from Macif,

  • Wilfrid Nkodia from Orange,

  • Jean-Baptiste Ratier from Safran Group,

  • Julie Ravillon from Salesforce,

  • Nathan Sorin from Skema Business School,

  • Antoine Roux from Frugrr

Thanks to our workshop coordinators and contributors.

  • Ariane Thomas and Axel Rakotonoera from L’Oréal,

  • Olivier Servoise from Engie,

  • Claire Guidi from the French building federation,

  • Nicolas Marescaux from Macif,

  • Wilfrid Nkodia from Orange,

  • Jean-Baptiste Ratier from Safran Group,

  • Julie Ravillon from Salesforce,

  • Nathan Sorin from Skema Business School,

  • Antoine Roux from Frugrr

Together, the community has developed two simple self-assessment tools, self-guided questionnaires with scoring and recommendations.

 

These tools are intended to be quick, and educational, utilizing easy closed-choice questions for non-experts (SME project managers, managers). They respond to two cases of use among the most frequent:

Is my AI project adopting the best practices for reducing its direct environmental footprint?

Evaluation of best practices for eco-design and environmental footprint optimization in AI applications (e.g. eco-design, right-sizing).

Can my AI solution legitimately create a net positive environmental impact?

Evaluation of AI’s contribution to reducing an organization’s overall environmental impact (e.g. reduction of the carbon bill via generative AI).

Together, the community has developed two simple self-assessment tools, self-guided questionnaires with scoring and recommendations.

These tools are intended to be quick, and educational, utilizing easy closed-choice questions for non-experts (SME project managers, managers). They respond to two cases of use among the most frequent:

Is my AI project adopting the best practices for reducing its direct environmental footprint?

Evaluation of best practices for eco-design and environmental footprint optimization in AI applications (e.g. eco-design, right-sizing).

Can my AI solution legitimately create a net positive environmental impact?

Evaluation of AI’s contribution to reducing an organization’s overall environmental impact (e.g. reduction of the carbon bill via generative AI).