The Green Consumption Assistant (GCA) supports consumers in making more sustainable decisions during online shopping. The GCA displays green product alternatives on the search engine Ecosia and provides information about more sustainable alternatives, for example, references to repair, rental, or sharing options. In addition, sustainable websites will be highlighted on Ecosia and the climate commitments of the organisations and companies will be made transparent in a ranking. For the recommendations of the GCA, a comprehensive product database (Green Database) with ecological and social sustainability information is being built up using machine learning techniques.
The GCA is a collaboration project between the Technische Universität Berlin, the Berliner Hochschule für Technik, and the green search engine Ecosia and is funded by the Bundesumweltministerium as a lighthouse project for artificial intelligence in use for ecological challenges. The project embodies a new, interdisciplinary partnership that combines sustainable and behavioural research with machine learning, user-centered design, and digital product development.
In the project, we rely on cooperation and exchange with various sustainability actors, scientists, and label organisations or online shops, to ensure a reliable and comprehensive data set for the recommendations of the Green Consumption Assistant.
Since the Paris Climate Conference, hundreds of companies have published ‘Net Zero Pledges’ in which they show how they intend to contribute to climate protection. In order to make the ambitions behind these pledges transparent, the TU Berlin has developed the Climate Pledge Rating together with the search engine Ecosia. In the article at RESET…
Since the Paris Climate Conference, hundreds of companies have published ‘Net Zero Pledges’ in which they show how they intend to contribute to climate protection. In order to make the ambitions behind these pledges transparent, the TU Berlin has developed the Climate Pledge Rating together with the search engine Ecosia. In the article at Bundesverband…
In chapter 7 of the anthology Corporate Social Responsibility in the Digital Space, an article on the GCA has been published. Marja Lena Hoffmann, Maike Gossen and Nina Güldenpenning present the green consumption assistant as a potential solution for the information complexity of sustainable consumption decisions. The anthology aims to collect current German-language research on…
In this paper, we present the high data quality of GreenDB. It is shown that Machine Learning (ML) can be used to predict the sustainability of products. Therefore, it is demonstrated that other ML-based systems, such as recommendation systems, can incorporate product recommendations as a parameter. Download Article