Ai Trust
9 articles
Two Ways AI and Blockchain Work Together: A Framework for Enterprise Architects
AI and blockchain integrate via two core patterns: blockchain enhancing AI for trust and data integrity, or AI enhancing blockchain for intelligence and automation. Identifying the correct pattern is the crucial first strategic decision for enterprise architects to address AI's trust deficit or blockchain's rigidity.
Linux Foundation: Enterprise Readiness, Not Model Power, Now Gates Agentic AI
A Linux Foundation report concludes that enterprise adoption of agentic AI is now primarily limited by organizational readiness, such as trust, governance, and cost management, rather than technical capability.
What is Explainable AI and Why is Trust Crucial for Enterprise Adoption?
Users of enterprise explainable AI (XAI) frequently fall into 'explanation pitfalls,' such as misplaced trust and over-estimating AI capabilities.
Explainable AI: Is It Truly Crucial for Trust?
Companies deploying high-risk artificial intelligence (AI) systems within the European Union face potential fines of up to €35 million, approximately $38.
Explainable AI: What It Is and Why It's Critical for the Future
Trust in an AI system's output hinges not just on algorithmic transparency, but on the perceived trustworthiness of its engineers.
What is Explainable AI and Why Does Trust Matter in 2026?
In sensitive domains like healthcare, 'black box' machine learning models, despite high performance, face significant adoption challenges due to their inherent ambiguity.
54% of People Don't Trust AI, Despite 66% Usage
A pro vice-chancellor at a major university recently admitted to using AI to write an opinion piece for a prominent Australian newspaper, without disclosing it.
What is Explainable AI and Why Does It Matter for Trust?
Companies deploying high-risk artificial intelligence (AI) systems in Europe face potential fines of up to €35 million, approximately $38.
What Is Explainable AI (XAI)? A Guide to Building Trust in AI Systems
While many organizations trust AI, few invest in safeguards for true trustworthiness. Explainable AI (XAI) bridges this gap by making AI decisions transparent and understandable, fostering confidence in its outcomes.