The landscape of data and AI documentation approaches in the European policy context

Nowadays, Artificial Intelligence (AI) is widely adopted in all sectors of the economy, making Data –the raw material used to build AI systems– is an extremely valuable asset. Consequently, both data and AI are having an unprecedented impact on society, and there is a need to ensure that they work to its benefit. For this reason, they are attracting the attention of policy makers across many jurisdictions, including the European Union, where they are the subject of a number of recent legislative and investment initiatives. A common element that plays an important role in these regulations is transparency, understood as the provision of information to relevant stakeholders to support their understanding of AI systems and data throughout their lifecycle. In this context, effective documentation practices are key to support a wide range of regulatory objectives. In recent years, a number of approaches for documenting AI and datasets have emerged, both within academia and the private sector. In this paper, we analyse this landscape of documentation approaches and consider their relevance from the angle of European regulatory objectives, assessing their coverage of AI technologies and economic sectors, and their suitability to address the specific needs of multiple stakeholders.

MICHELI Marina;  HUPONT TORRES Isabelle;  DELIPETREV Blagoj;  SOLER GARRIDO Josep; 

2024-06-21

SPRINGER

JRC131211

1435-5655 (online),    0951-5666 (print),   

https://doi.org/10.1007/s10676-023-09725-7,    https://publications.jrc.ec.europa.eu/repository/handle/JRC131211,   

10.1007/s10676-023-09725-7 (online),