AI for Good: How Real People Are Using Artificial Intelligence to Fix Things That Matter
Language: English
Published by Simon & Schuster (edition ), 2026
- Hardcover
- Used

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Condition: Used - Very good
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With dust jacket. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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- Title
- AI for Good: How Real People Are Using Artificial Intelligence to Fix Things That Matter
- Author
- Tyrangiel, Josh
- Publisher
- Simon & Schuster (edition )
- Publication year
- 2026
- Condition
- Very Good
- Dust jacket
- Dust Jacket Included
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1668082500
- ISBN 13
- 9781668082508
AI is often framed as a force of radical transformation, either catapulting us into a utopian future or dragging us toward existential ruin. But this book tells a different story. It’s not about high-profile tech CEOs who want to use AI to “break shit,” but about a bunch of smart pragmatists using AI to make the world better.
Josh Tyrangiel’s journey into AI began with a late-night YouTube video featuring General Gustave Perna, the retired four-star general who orchestrated the distribution of Covid vaccines during Operation Warp Speed. Perna’s success—and the end of the pandemic—depended on AI’s practical ability to synthesize and standardize vast amounts of logistical data. AI wasn’t the hero of the story—it was the tool that helped real people get things done.
This book follows those people, who make up a kind of AI counterculture. It explores AI’s quiet revolution in government services, medicine, education, and human connection—places where it’s being used to amplify human judgment rather than replace it. It tells the stories of teachers, doctors, and bureaucrats who often stumbled into AI as a means to solve specific, tangible problems, often with no prior software expertise.
While the loudest voices in AI debate doomsday scenarios and trillion-dollar market opportunities, this book focuses on those working in the messy, incremental, but deeply impactful space of AI practice. However, there is one big caveat—success is not guaranteed. Change is hard. Institutions move slowly. But even in failure there are lessons for everyone who’s interested in using AI—carefully, thoughtfully—to build a better world today.
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