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.
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