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Synopsis for the book: AI for the Rest of Us

Below is a synopsis of the  book  that I wrote with my co-author,  Phaedra Boinodiris . This is an excerpt from the book and is the last chapter. I wanted to share this synopsis — or “seeing altogether” of what our book is about and build hope for our shared future that our book resonates and inspires.


There is much we need to unlearn to evolve as better stewards of AI. So we dedicate this book to our sons and daughters and gentle readers so that you can champion the cause.

Chapter 1 — This book is for you: We need a billion more humans literate in AI systems. We need more people involved in the creation of AI. We need you; your story is essential for creating effective AI.

Chapter 2 — A conceptual model for Data: Data is an artifact of human experience, and information, knowledge, and wisdom require context, relationships, and stories.

Chapter 3 — What is AI: AI is a system that simulates human intelligence, and responsible AI aims to augment humans.

Chapter 4 — Stories that keep us up at night: The stories that keep us up at night are nothing compared to our resilience as a species. What divides us pales in comparison to what unites us.

Chapter 5 — The end of opacity: The end of opacity or ambiguity means that we can hold corporations responsible for their impact on individuals and communities for their deployment of AI.

Hold them accountable for ensuring what they deploy aligns with principles for trust and transparency.

Demand that AI systems have frequent auditing by ethically qualified personnel.

Demand that companies take on the burden of the total lifecycle cost of ownership if they reap the benefit. Align the incentives for corporations to take on the entire lifecycle of a product from the planning, development, and production phase through the use and then onto the end of the product.

Chapter 6 — Positive Parenting: Positive reinforcement works far better than negative; incentivize the behaviors you wish to see more of, replicate what works, be curious, and know that we borrow our world from our children.

Chapter 7 — Rules to live by: Models of how to live are all around us, and we can be the model by unlearning and rethinking our accountability.

Chapter 8 — Myth versus Reality: Understanding the myths and truths about AI and who benefits when we perpetuate those myths.

Chapter 9 — Language and Archaeology: Studying language and archaeology can give us the understanding we need to survive current Generative AI models.

Chapter 10 — Cognitive Science and Ontologies: Cognitive Science and Ontologies are different ways to examine AI and information systems, the cure that grows near the cause.

Chapter 11 — Roles and Responsibilities: Roles and responsibilities for responsible AI include many more than are currently being sought after for AI jobs.

Chapter 12 — The culture to curate AI responsibly: Systems of inequality are perpetuated through taking power away or building AI systems that control versus augment humans. The culture required to curate AI responsibly includes a growth mindset, multi-disciplinary teams, and diverse and inclusive leadership.

Chapter 13 — AI Education and Certification NOW: AI Education must start now at all levels, especially K-12. We are 100s of millions of people short of creating AI representative of the human race.

We need more people with diverse thoughts and stories to develop AI. We need people with the imagination to design and build AI to reflect better the communities that AI serves today.

In this book, we have attempted to teach that we need YOU. So please reach out to us. We want to hear from you!


One of my favorite things to do is look up the etymology of words, it is akin to archaeology and reminds me of how many stories can be contained within one word.

The word synopsis comes from 1610s, “a general view, an outline,”

from Late Latin synopsis “a synopsis,”

from Greek synopsis “a general view,” literally “a seeing altogether, a seeing all at once,”

from syn- “together” (see syn-) + opsis “sight, appearance,”

from PIE root *okw- “to see.”

-Online Etymology Dictionary