Reducing Information Pollution

The Efficiency Paradox: What Big Data Can’t Do

Embedded algorithms processing big data are proposed to reduce human information processing demands. Edward Tenner in his book The Efficiency Paradox: What Big Data Can’t Do [Alfred a Knopf, 2018] proposes that the efficiency from embedded Big Data Analytics can be counterproductive, e.g., missed opportunities, adopting new approaches, less intuitive thinking. He provides a persuasive rationale for his position including many valuable examples. Tenner recommends that a selective combination of embedded algorithms and human intuition will improve judgments, learning and decision-making. Marty B #IORGforum, #EndInfoOverload

Source: Amazon
Author: Edward Tenner
Date: April 17, 2018
Excerpt: Embedded algorithms processing big data are proposed to reduce human information processing demands. Edward Tenner in his book The Efficiency Paradox: What Big Data Can’t Do [Alfred a Knopf, 2018] proposes that the efficiency from embedded Big Data Analytics can be counterproductive, e.g., missed opportunities, adopting new approaches, less intuitive thinking. He provides a persuasive rationale [...]
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