Philip Emeagwali

Answer choices

1. A

   Correct82% picked this

   Until recently, computer scientists have had very limited awareness of many of the mathematical principles that have been shown to underlie a

   Why this is right

   This is probably not a very appealing answer on a first pass, but once we've seen all five, we might work our way back here and see its "best available" appeal. It seems to be the only answer that addresses both 1. Computer scientists 2. A difference between the past and the present/near future If, in the past, a computer scientist had wanted to use nature as inspiration to solve a technical problem, they probably wouldn't have gotten very far with that solution path, since it wasn't until recently that we had any decent awareness of the mathematical principles underlying nature. Emeagwali is a computer scientist who looked to the natural phenomenon of tree branching in order to solve a technical problem about oil flow, but he did so with "a network design based on the mathematical principle that underlies the branching structures of trees". There's no way to harness the insights of nature and then apply them to our manmade problems unless we actually grasp the insights of nature. So because this answer is saying, "computer scientists didn't have the ability to grasp the underlying math of nature (in order to potentially use it as inspiration) until recently ... so now that they finally understand the mathematical principles of nature, we will increasingly see solutions inspired by nature." This is sort of like strengthening the prediction that "genetic scientists will increasingly try to bio-engineer traits they want through genetic manipulation" by saying, "it wasn't until recently that they could precisely target and alter specific genes". Or strengthening the prediction that "Josie will increasingly get better at basketball" by saying, "it wasn't until recently that Josie had access to a basketball".

   Skill tested: Strengthen · how this choice captures the passage's function is the move to repeat next time.

   82%
2. B

   Weakens, if anything3% picked this

   Some of the variables affecting global weather patterns have yet to be discovered by scientists

   This is super-duper weak ("some'), so it's very unattractive as a correct answer on Strengthen / Weaken (whether it's LR or RC). This seems to be talking about us not understanding parts of nature. How could that help us argue that scientists will increasing use nature as inspiration for solving technical problems? If we don't understand something fully, we'd be less likely to craft a clever solution from it.

   3%
3. C

   Unrelated to Goal5% picked this

   Computer designs for the prediction of natural phenomena tend to be more successful when those phenomena are not

   This is saying that our computer models are more successful at prediction what nature will do, if humans aren't involved in the thing we're predicting. We're looking for an answer that helps us say, "more and more, scientists will be using nature as inspiration for solving a complex technical problem". "Computer models that try to predict nature" has nothing to do with using nature as inspiration to solve a technical problem (like using the 3D spacing of a honeycomb to solve the technical problem of weather modeling).

   5%
4. D

   Weak / No Impact7% picked this

   Some of the mathematical principles underlying Emeagwali's model of oil field flow also underlie his designs for other

   This is super-duper weak ("some'), so it's very unattractive as a correct answer on Strengthen / Weaken (whether it's LR or RC). This is only talking about Emeagwali's models and designs. But we're trying to strengthen a prediction about other computer scientists increasingly looking to nature for inspiration. This doesn't seem to speak to other scientists at all.

   7%
5. E

   No Impact3% picked this

   Underlying the designs for many traditional technologies are mathematical principles of which the designers of those technologies

   This is saying that many traditional technologies were designed without the designers being explicitly aware of the underlying mathematical principles. Okay. What does that have to do with predicting an increase in scientists looking to nature as inspiration to solve a technical problem?

   3%