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posted by martyb on Sunday June 14 2020, @11:36AM   Printer-friendly
from the tl;dr dept.

The brain uses minimum effort to look for key information in text:

A recently completed study indicates that the human brain avoids taking unnecessary effort. When a person is reading, she strives to gain as much information as possible by dedicating as little of her cognitive capacity as possible to the processing.

[...] According to the study, the brain is processing information by taking into account the relative importance of the content that is being read. When the brain is interpreting the meaning of the words being read, it attempts to allocate resources to interpreting the words that provide as much information as possible on the content of the text.

[...] In the recently published study, the perspective was expanded to the level above individual sentences, the discourse level. It was studied using six-sentence paragraphs. At this level, the relationship between words becomes increasingly complex, and the significance of context in interpreting individual words is increased. On the discourse level, very little about information processing by the brain has been known so far.

[...] "When someone reads the sentence 'Cats are small, usually furry mammals', words such as 'mammal' and 'furry' evoke a particular pattern of brain activity. This suggests that the brain is efficiently processing information: concentrating its efforts there where the most additional value in understanding the message is to be gained," says Michiel Spapé, a senior researcher who contributed to the study.

A related finding revealed that, by using AI-based techniques, brain measurements pertaining to individual words can be used to predict whether the information gain for the words read is low or high.

[...] Ruotsalo points out that the research is only at its basic stage.

Journal Reference:
Lauri Kangassalo, Michiel Spapé, Niklas Ravaja, et al. Information gain modulates brain activity evoked by reading [open], Scientific Reports (DOI: 10.1038/s41598-020-63828-5)


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  • (Score: 3, Insightful) by Anonymous Coward on Sunday June 14 2020, @12:35PM (1 child)

    by Anonymous Coward on Sunday June 14 2020, @12:35PM (#1007736)

    Yet another good reason to stop using the over-hyped term "AI" and go back to more descriptive terms like "pattern matching"...until there has been a lot more progress in understanding human brains.

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  • (Score: 0) by Anonymous Coward on Monday June 15 2020, @03:30AM

    by Anonymous Coward on Monday June 15 2020, @03:30AM (#1007999)

    Intelligence assumes a goal and the ability to self learn how to get to said goal more efficiently.

    For instance if a chess computer engine plays chess against an opponent and reviews its moves to look for moves that would either help it win or help it win in fewer moves for future games that would be AI.

    The problem is that often AI gets used instead of statistical analysis/pattern matching when in reality what's being described isn't intelligence (the thing isn't self improving, it's just matching new data to the data that's been fed to it and statistically identifying what the new thing it's looking at most likely is based on existing data or identifying what a user wants to click on based on what they typed by matching the contents of the search to the contents of the page).

    Now if Google's search engine automatically notices (without human intervention) that people that search for one thing tend to click the first link, click back, click the second link, and then seem to be satisfied and so it's search engine automatically reorders the search results accordingly (for everyone or for just that person?) I would call that legitimate AI. The search engine is actually self learning what people want based on what they click and making changes to account for what it learned.