Mindmasters
The Data-Driven Science of Predicting and Changing Human Behavior
-
- 15,99 €
-
- 15,99 €
Publisher Description
A fascinating exploration of how algorithms penetrate the most intimate aspects of our psychology—from the pioneering expert on psychological targeting.
There are more pieces of digital data than there are stars in the universe. This data helps us monitor our planet, decipher our genetic code, and take a deep dive into our psychology.
As algorithms become increasingly adept at accessing the human mind, they also become more and more powerful at controlling it, enticing us to buy a certain product or vote for a certain political candidate. Some of us say this technological trend is no big deal. Others consider it one of the greatest threats to humanity. But what if the truth is more nuanced and mind-bending than that?
In Mindmasters, Columbia Business School professor Sandra Matz reveals in fascinating detail how big data offers insights into the most intimate aspects of our psyches and how these insights empower an external influence over the choices we make. This can be creepy, manipulative, and downright harmful, with scandals like that of British consulting firm Cambridge Analytica being merely the tip of the iceberg. Yet big data also holds enormous potential to help us live healthier, happier lives—for example, by improving our mental health, encouraging better financial decisions, or enabling us to break out of our echo chambers.
With passion and clear-eyed precision, Matz shows us how to manage psychological targeting and redesign the data game.
Mindmasters is a riveting look at what our digital footprints reveal about us, how they're being used—for good and for ill—and how we can gain power over the data that defines us.
PUBLISHERS WEEKLY
Artificial intelligence monitors internet users' every move, for good and ill, according to this eye-opening debut exposé. Surveying the disturbing reach of digital surveillance, Matz, a professor at Columbia Business School, notes that smart phones track owners' movements; that Facebook, Google, and YouTube deduce users' thoughts and interests, as revealed by searches, posts, and likes; and that Roombas transmit photos of people's homes, as one woman discovered when someone associated with the vacuum's manufacturer leaked an image of her in the bathroom. This data enables companies to build elaborate psychological profiles with potentially costly consequences, Matz writes, suggesting that insurance companies might target ads at anxious individuals, and that banks might deny loans to people they determine to be high in "agreeableness," per the Big Five personality test (studies have shown such individuals default on payment at higher than average rates). Matz argues that while personal data can be put to good use (her own work has used microtargeted ads to persuade people to save more), safeguards should be implemented to protect against abuses. For example, she suggests that data sharing should be opt-in by default and that "data cooperatives" could allow people to voluntarily pool their data for analysis or monetization while maintaining their ownership over the info. Peeling back the curtain on the long lives of user data, this unsettles.
