• Funding : Yes
• Title : Supporting Trustworthy AI with Enterprise Blockchain
• Thesis Director: Pr. Camille Salinesi
• Thesis co-Director: Dr. Nicolas Herbaut
• Keywords: blockchain, AI, trust

Trustworthy artificial intelligence (AI) is a multifaceted concept underpinned by threecritical pillars: Trustworthy Machine Learning, Trustworthy Inference (often associated with Explainable AI, or XAI), and Trustworthy Data Management [1]. Together, these components form the backbone of ethical and reliable AI systems. Trustworthy Machine Learning ensures that AI models are developed with integrity, fairness, and accountability. Trustworthy Inference focuses on the ability of AI systems to provide transparent and understandable explanations for their decisions, thereby enhancing user trust. Lastly, Trustworthy Data emphasizes the importance of high-quality, secure, and privacy-respecting data as the foundation upon which AI models are trained. The interconnection of these concepts is essential for the realization of AI systems that are not only effective but also align with ethical standards and societal values. We will investigate in this PhD if blockchain may be an interesting solution to support trustworthy AI.