Foundation of Trustworthy AI

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Authors: Vincent Oostlander, Christina Bassani, Hugo Bergmann
Cited by: 0

Abstract

AI is built on data. From healthcare and finance to public policy and autonomous systems, AI relies on vast amounts of information to make decisions that can have significant social and economic impact. This chapter explores how the trustworthiness of AI systems depends not only on powerful algorithms but, more fundamentally, on the integrity and transparency of the data infrastructure that supports them. Reliable storage systems are essential for retaining, accessing, and auditing the data that fuels AI, especially as regulations demand greater accountability and explainability. Highlighting innovations from Seagate, the chapter illustrates how modern storage technologies are evolving to meet the challenges of AI-scale data—ensuring that organizations can build systems that are ethical, compliant, and sustainable. Understanding this foundation is key to developing AI that earns and maintains trust in real-world applications.

Fields of Study & Subjects

Ethics and Social Impacts of AI Explainable Artificial Intelligence (XAI) Advanced Data Storage Technologies

Publication details

Journal / source
Auerbach Publications eBooks
Pages
36–51
Publication date
3 February 2026
Language
EN
Document type
Book chapter