The Privacy Pillar - A Conceptual Framework for Foundation Model-Based Systems

AI and its relevant technologies are currently undergoing a profound transformation of development and organizational processes within companies. Foundation models present both significant challenges and incredible opportunities. In this context, ensuring the quality attributes is of importance, and with a particular focus on the challenging issue of privacy due to the sensitive nature of the data and information involved. However, there is currently a lack of consensus regarding the scope of both technical and non-technical issues that the privacy evaluation process should encompass. Additionally, there is uncertainty about which existing methods are best suited to effectively address these privacy concerns. In response to this challenge, this paper introduces a novel conceptual framework that integrates various responsible AI patterns from multiple perspectives, with the specific aim of safeguarding privacy.