AI Beyond the Hype: Five Leadership Lessons from Season 1 of the RHEMINISCING Podcast
“AI is powerful, but power without purpose, governance, and human judgment is not progress.” — Dr. Anthony J. Rhem
This … Read More
AI in Knowledge Management : Moving from Static Repositories to Intelligent Knowledge Ecosystems
Note: The Chapter AI in Knowledge Management will be published in the AI and Ethics Handbook, edited by Dr. … Read More
From AI Pilots to Enterprise AI
Why Governance, Knowledge Architecture, and Leadership Now Matter Most
Introduction
Artificial Intelligence has moved beyond experimentation. Many organizations have already … Read More
What is Enterprise Intelligence?
Enterprise Intelligence
Enterprise Intelligence – History
Enterprise intelligence (EI) is not a new paradigm, however as it is positioned today … Read More
Why Assessing AI Algorithms Is No Longer Optional
Artificial intelligence is moving fast, but responsible organizations cannot afford to move carelessly. AI is no longer confined to experimental … Read More
In print:
Essential Topics in Artificial Intelligence AI evolved from expert systems to today’s machine learning and generative models; covers ethics, LLMs, AGI, and NLP basics.
Essential Topics in Information Architecture Information Architecture (IA) details important areas of interest in the principles and practice of implementing information architecture.
Knowledge Management in Law Firms is a collection of insights on managing knowledge in a law firm, from Knowledge Management professionals around the globe. KM in Law Firms is produced in association with the International Bar Association.
Knowledge Management Matters brings together the expertise of the world's thought leaders of KM, who share tips, tactics, and techniques.
Knowledge Management in Practice gives detailed information on applying knowledge management (KM) practices, procedures and techniques to solve real world problems.
UML for Developing Knowledge Management Systems provides knowledge engineers the framework in which to identify types of knowledge and where this knowledge exists in an organization.
It also shows ways in which to use a standard recognized notation to capture, or model, knowledge to be used in a knowledge management system (KMS).
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