The Green Consumption Assistant (GCA) supports users in making more sustainable consumption decisions while searching for information and shopping online. Several applications of the Green Consumption Assistant are being implemented in the process of the project, with iterative and user-centered development. Consequently, new versions and applications are continuously being realised, tested, and improved. The information required for this is stored by the AI-based assistance system in a specially created sustainability database, which is continuously expanded with the help of automated processes. The user-friendliness and effectiveness of individual applications are analysed in experimental studies, user interviews, and surveys. The findings from these studies are taken into account in the further development and improvement of the Green Consumption Assistant.

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AI and Consumption

Sustainability is a topic of growing interest in the field of AI research, not only because of the increased resource requirements of modern AI components. AI systems can be used, for example, to enhance forecasts of energy requirements or to make processes more efficient to preserve natural resources. Until now, the potential of AI for the benefit of sustainability has remained mostly untapped. Indeed, AI already influences e-commerce, but not with regard to sustainability. Online retailers order research teams that work on algorithms to improve purchase recommendations and also to maintain and upgrade the database of the product portfolio. Despite rapid progress in the field of AI for consumption recommendations, recommendation algorithms have not been successfully used to promote sustainable consumption or to automatically extract sustainability information from unstructured data. That’s what we want to change!

The Green Consumption Assistant, through its implementation on the search engine Ecosia – and as an open offer for other search engines that want to develop further in the direction of green search – has the chance to help the multitude of existing, scattered sustainability information to achieve a significantly greater scope and market penetration. At the same time, the frequent use of the assistant promotes „accuracy” by improving the data situation through AI.

Features and Findings