Context is critical.
As noted in previous attention research and a forthcoming book:
How Attention Works: Finding Your Way in a World Full of Distraction (The MIT Press) March 2019
“we gather only relevant information. We focus on one snippet of information and assume that everything else is stable and consistent with past experience.”
Our perceptual process attempts to focus on the most salient data or pixel set (e.g., bold type, color, relative position) to reduce IO.
As van der Stigchel’s quote above suggests, we can be mislead by ignoring related contextual attributes. Thus, we need to ask ourselves if the perceptual input is complete and consistent with our task objective. ]
Critical thinking skills can help.
Don’t be an IO victim.
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.