Reading Basics part 2
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Artificial intelligence (AI) can already predict the future.
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Police forces are using it to map when and where crime is likely to occur.
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Doctors can use it to predict when a patient is most likely to have a heart attack or stroke.
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Researchers are even trying to give AI imagination so it can plan for unexpected consequences.
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Many decisions in our lives require a good forecast, and AI is almost always better at forecasting than we are.
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Yet for all these technological advances, we still seem to deeply lack confidence in AI predictions.
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Recent cases show that people don’t like relying on AI and prefer to trust human experts, even if these experts are wrong.
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If we want AI to really benefit people, we need to find a way to get people to trust it.
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To do that, we need to understand why people are so reluctant to trust AI in the first place.
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Take the case of Watson for Oncology, one of technology giant IBM’s supercomputer programs.
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Their attempt to promote this program to cancer doctors was a PR disaster.
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The AI promised to deliver top-quality recommendations on the treatment of 12 cancers that accounted for 80% of the world’s cases.
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But when doctors first interacted with Watson, they found themselves in a rather difficult situation.
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On the one hand, if Watson provided guidance about a treatment that coincided with their own opinions, physicians did not see much point in Watson’s recommendations.
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The supercomputer was simply telling them what they already knew, and these recommendations did not change the actual treatment.
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On the other hand, if Watson generated a recommendation that contradicted the experts’ opinion, doctors would typically conclude that Watson wasn’t competent.
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And the machine wouldn’t be able to explain why its treatment was plausible because its machine-learning algorithms were simply too complex to be fully understood by humans.
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Consequently, this has caused even more suspicion and disbelief, leading many doctors to ignore the seemingly outlandish AI recommendations and stick to their own expertise.
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This is just one example of people’s lack of confidence in AI and their reluctance to accept what AI has to offer.
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Look around on your next plane trip.
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The iPad is the new pacifier for babies and toddlers.
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Younger school-aged children read stories on smartphones; older kids don’t read at all, but hunch over video games.
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Parents and other passengers read on tablets or skim a flotilla of email and news feeds.
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English literature scholar and teacher Mark Edmundson describes how many college students actively avoid the classic literature of the 19th and 20th centuries in favour of something simpler as they no longer have the patience to read longer, denser, more difficult texts.
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Multiple studies show that digital screen use may be causing a variety of troubling downstream effects on reading comprehension in older high school and college students.
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In Stavanger, Norway, psychologist Anne Mangen and colleagues studied how high school students comprehend the same material in different mediums.
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Mangen’s group asked subjects questions about a short story whose plot had universal student appeal; half of the students read the story on a tablet, the other half in paperback.
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Results indicated that students who read on print were superior in their comprehension to screen-reading peers, particularly in their ability to sequence detail and reconstruct the plot in chronological order.
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Ziming Liu from San Jose State University has conducted a series of studies which indicate that the ‘new norm’ in reading is skimming, involving word-spotting and browsing through the text.
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Many readers now use a pattern when reading in which they sample the first line and then word-spot through the rest of the text.
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When the reading brain skims like this, it reduces time allocated to deep reading processes.
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In other words, we don’t have time to grasp complexity, to understand another’s feelings, to perceive beauty, and to create thoughts of the reader’s own.
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There’s an old rule in neuroscience that does not alter with age: use it or lose it.
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It is a very hopeful principle when applied to critical thought in the reading brain because it implies choice.
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The story of the changing reading brain is hardly finished.
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We possess both the science and the technology to identify and redress the changes in how we read before they become entrenched.
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If we work to understand exactly what we will lose, alongside the extraordinary new capacities that the digital world has brought us, there is as much reason for excitement as caution.
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The Persians, who lived in present-day Iran, were one of the first civilizations to build tunnels that provided a reliable supply of water to human settlements in dry areas.
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The excavated soil was taken up to the surface using the shafts, which also provided ventilation during the work.
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Once the tunnel was completed, it allowed water to flow from the top of a hillside down towards a canal, which supplied water for human use.
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Remarkably, some qanats built by the Persians 2,700 years ago are still in use today.
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Roman tunnel projects were carefully planned and carried out.
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The length of time it took to construct a tunnel depended on the method being used and the type of rock being excavated.
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The type of rock could also influence construction times.
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When the rock was hard, the Romans employed a technique called fire quenching which consisted of heating the rock with fire, and then suddenly cooling it with cold water so that it would crack.
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Progress through hard rock could be very slow, and it was not uncommon for tunnels to take years, if not decades, to be built.
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