One aim of our project is to build an AI-based product database that enables the development of a recommendation assistant. This paper explains how scraping technologies can be used to request publicly available data about products and information about their sustainability, and how this information can be integrated into a central database. Furthermore, the first…
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.