The Book Look: AI Governance

Technics Publications has started publishing a line of Data-Driven AI books, and one of the first books in this series is “AI Governance” by Dr. Darryl J Carlton. The goal of the book in one sentence is to enable the reader to gain the knowledge and tools to effectively govern and oversee the use of artificial intelligence in their organization, while being compliant with emerging global regulations. This book contains four sections: 

  1. “A Brief History of AI” — Unravel the history of AI as a context to understand the current state and how AI will evolve over the next few years. Darryl weaves in some science fiction into this historical perspective, including characters such as Hal, Gort, and even Frankenstein. I love the idea of Isaac Asimov’s Three Laws of Robotics as being the first ethical framework for AI. 
  1. “The Eight Guiding Principles of AI” — By adopting and adhering to these principles, your organization will be well-positioned to navigate the complex landscape of AI regulation and remain compliant across most jurisdictions. This section is a distillation of all current AI frameworks. Darryl presents the common denominator across all of these global frameworks into eight powerful principles. 
  1. “Ethics and AI” — Connect ethics with AI by examining case studies and proposing an ethical framework to guide your successful deployment of AI. “Just because you can do something, should you?” 
  1. “Conformance Assessment” — Implement a Conformance Assessment Checklist to establish effective AI governance and oversight practices in your organization. This is everything you need to consider before deploying an AI project. The content is in the form of a useful checklist. 

I very much enjoyed reading this book and I think it was for two main reasons: writing style and presentation. Darryl’s writing style combines practicality with preciseness, yet still presents an entertaining read. In addition, the material is presented with an objective, yet slightly positive outlook. So much of what we read about AI is “doom and gloom,” but Darryl does a good job of presenting the positive side and amazing potential of AI. 

To give you a taste of the style and content of “AI Governance,” here is an excerpt, used with permission from Technics Publications. This is from the introduction to Chapter 2 on the Eight Guiding Principles of AI: 

The emergence of artificial intelligence (AI) as a dominant force heralds a transformative shift in our society. As stewards of this potent technology, we must ensure that the development and deployment of AI systems adhere to a set of core principles that prioritize Human, Social, and Environmental Well-being. AI should be a lever for positive change, enhancing individuals’ quality of life, enriching society’s fabric, and nurturing our planet’s ecological balance. 

AI systems must be anchored in Human-Centered Values, championing the cause of human rights, the richness of diversity, and the sanctity of individual autonomy. In doing so, they become not just tools of convenience or efficiency but instruments that resonate with the fundamental ethos of our existence. 

Fairness must be the cornerstone of AI, embodied in systems that are inclusive and accessible to all, transcending barriers and biases. An AI devoid of fairness is a mirror reflecting our past prejudices into the future. We must ensure that AI is a bridge to equality, not a barrier. 

Privacy Protection and Security are paramount in an age where data is as valuable as currency. AI systems should be bastions of trust, protecting the sanctity of personal information while safeguarding against breaches that can undermine the very foundations of our digital society. 

Reliability and Safety are the hallmarks of any technology that stands the test of time. AI systems should be unwavering in their performance and steadfast in their functions, operating with the precision and purpose they were designed for. This reliability extends beyond mere functionality, ensuring that safety is embedded in every line of code and every decision made without human intervention. 

Transparency and Explainability must cut through the opacity that often shrouds technological advancements. People have an unequivocal right to understand when and how AI impacts them. The ability to discern AI’s involvement in our daily interactions ensures that the human element remains informed and empowered. 

Contestability is critical, providing a voice to those impacted by AI. There must be clear, efficient avenues for individuals and communities to question and rectify decisions made by AI systems, ensuring that the technology remains a servant, not a master. 

Finally, accountability is the thread that ties all these principles together. There must be a clear line of responsibility from the inception of an AI system through its lifecycle. Those who design, develop, and deploy AI must be identifiable and answerable for their creations, with the provision for human oversight ever-present. 

In conclusion, as we stand at the frontier of a new digital dawn, AI principles must be etched in policy documents and the algorithms that will define our future. The vision for AI uplifts, protects, and harmonizes, forging a path where technology and humanity march together to a horizon of shared prosperity and collective well-being. 

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Steve Hoberman

Steve Hoberman

Steve Hoberman has trained more than 10,000 people in data modeling since 1992. Steve is known for his entertaining and interactive teaching style (watch out for flying candy!), and organizations around the globe have brought Steve in to teach his Data Modeling Master Class, which is recognized as the most comprehensive data modeling course in the industry. Steve is the author of nine books on data modeling, including the bestseller Data Modeling Made Simple. Steve is also the author of the bestseller, Blockchainopoly. One of Steve’s frequent data modeling consulting assignments is to review data models using his Data Model Scorecard® technique. He is the founder of the Design Challenges group, Conference Chair of the Data Modeling Zone conferences, director of Technics Publications, and recipient of the Data Administration Management Association (DAMA) International Professional Achievement Award. He can be reached at

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