[Review] Mindmasters (Sandra Matz) Summarized.

[Review] Mindmasters (Sandra Matz) Summarized.
9Natree
[Review] Mindmasters (Sandra Matz) Summarized.

Oct 31 2026 | 00:10:02

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Episode • October 31, 2026 • 00:10:02

Show Notes

Mindmasters (Sandra Matz)

- Amazon USA Store: https://www.amazon.com/dp/1647826314?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Mindmasters-Sandra-Matz.html

- Apple Books: https://books.apple.com/us/audiobook/mindmasters-anna-caputo-version-the-data-driven/id1779151529?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree

- eBay: https://www.ebay.com/sch/i.html?_nkw=Mindmasters+Sandra+Matz+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/1647826314/

#Psychologicaltargeting #Behavioralresidues #Digitalfootprintinference #GenerativeAIpersonalization #Datacooperatives #Mindmasters

Mindmasters: The Data-Driven Science of Predicting and Changing Human Behavior is a nonfiction examination of psychological targeting by Sandra Matz, a computational social scientist and professor at Columbia Business School. The book explains how data generated through ordinary digital activity can be analyzed to infer traits, preferences, values, and likely decisions. Its subject is not merely personalized advertising, but the expanding ability of organizations to model the psychological conditions under which people can be persuaded. Matz combines behavioral-science research, data analytics, and practical examples to show how this capability operates in commercial and social settings. She treats the technology as inherently dual-use: it can help people make healthier, better-informed choices, while also enabling intrusive influence and reducing individual agency. The book therefore has two linked purposes. It clarifies the mechanisms behind algorithmic profiling for non-specialists, and it asks what ethical governance should look like when intimate inferences can be drawn from seemingly routine data.

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