Over the past five years, European Union (EU) law and policy have been characterized by intense legislative and policy activity aimed at advancing the digital and green transitions. A central focus of these efforts has been the governance and regulation of data. Key initiatives such as the EU AI Act, the Data Governance Act, the Data Act, and proposals for Common European Data Spaces exemplify the EU’s data-centered legislative agenda. This emphasis is unsurprising, given the pivotal role information technology and data play in driving societal transformation. The influence of Data-Driven and Artificial Intelligence (DDAI) technologies is already evident across various sectors, including healthcare, work, entertainment, finance, and banking. These technologies are being developed and applied for a wide range of objectives and purposes, such as the creation and development of ‘smart cities’.  However, DDAI technologies raise significant concerns from legal, regulatory, social equity and environmental sustainability perspectives.  

From a legal-regulatory perspective, DDAI raises important questions that require urgent answers, such as: the ways in which law and regulation can contain DDAI and address the risks it poses for the individuals and society at large, without constraining its development and potential positive societal and environmental impact; how can the legal-regulatory framework deal with the challenges and implications of the privatization of public power through digitalization and legal tech, and in this context, organize the relationship between (big) tech companies and public authorities on data collection and processing; how may law and regulation ensure respect for human rights in the context of DDAI technologies, entailing un unprecedented use of AI, algorithms, surveillance and large-scale data collection and processing in both the private and public domains. 

From a social equity standpoint, DDAI systems often exacerbate existing vulnerabilities and inequalities faced by marginalized communities, for instance in the context of the rapid development of smart cities. This occurs through mechanisms such as over- or underrepresentation or by reinforcing exclusions based on attributes like sex or race. Moreover, the labor practices underpinning DDAI development—particularly in training Large Language Models (LLMs)—have been criticized for their exploitative nature. 

From an environmental perspective, while DDAI has been leveraged to address ecological challenges, such as through the European Green Deal and initiatives like the proposed Common European Green Deal Data Space, these technologies also pose significant environmental risks. For instance, the energy-intensive processing and storage of massive datasets contribute to greenhouse gas emissions, while data centers rely heavily on water for cooling and require the extraction of minerals for technological components. Additionally, DDAI systems generate substantial e-waste. These issues highlight the need for critical examination of the inherent (un)sustainability of DDAI technologies—a subject that remains relatively unexplored in legal scholarship. 

Against this backdrop, this special track seeks to investigate the complex interplay between data-driven technologies and their legal, social and environmental impact.  We particularly welcome submissions that propose legal frameworks for governing DDAI technologies in light of these challenges. Contributions addressing all types of technologies and applications are encouraged, with a special interest in the following themes: 

1. Sustainable Smart Cities 
2. Data-Driven Technologies in Health and Care 
3. Data-Driven Technologies in International Finance and Banking 
4. Data-Driven Solutions for Environmental Policy 

The organizers encourage submissions that integrate doctrinal legal research with insights from related fields, including the philosophy of law, ethics and philosophy of technology, political science and governance studies, economics, and law and technology.