Philosophy of Data: The Raw Material of Thought and the Collective Mind
Language: English
Published by EliteLink Publishing, 2026
- Softcover
- New
Seller: California Books, Miami, FL, U.S.A.California Books
AbeBooks seller since October 27, 2023
Condition: New
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Add to basketSeller Inventory # I-9798993218434
- Title
- Philosophy of Data: The Raw Material of Thought and the Collective Mind
- Author
- Lai, May Ling
- Publisher
- EliteLink Publishing
- Publication year
- 2026
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798993218434
Data. Everyone uses the word, and almost no one can define it.
Ask the people who work with data every day what it is, and they reach for information, knowledge, or insight. Ask them to define information, and they hand the word data right back. For a field dedicated to catching errors of logic, that circular reference has gone unchallenged for a long time.
Philosophy of Data proposes a new starting point: data is the raw material of thought. It is what a conscious mind produces when it encounters the world, decides something matters, and captures it. Under this definition, a lie in a database counts as data. So does a troll comment, a census category, or a tally mark on a bone. Truth and value are judgments made afterward. Data also gains a history that runs back to the first scratches on a cave wall, long before spreadsheets.
Drawing on philosophy going back to Aristotle, the history of writing, and the factory floor from Ford to Deming to Tesla, and integrating Jung and Durkeim, we build a framework that holds up in theory and earns its keep in practice. Inside, she explores:
- Why there is no truth in data, and what that means for bias
- How a captured thought becomes usable
- Why volume is a poor measure of big data
- Where the tools of data work end and the process begins
- What data is worth to the people who create it
- What it means that AI, in its current form, is a collection of society's thoughts
Much of the public fear about AI is aimed at the algorithm. This book turns attention to what is fed into it. That shift opens the conversation beyond coders to philosophers, historians, writers, and anyone whose thoughts now shape the machine.
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