Human beings can see the spatial relations among objects by processing information conveyed by light. Scientists trying to build computers...

GMAT Critical Reasoning : (CR) Questions

Source: Official Guide

Critical Reasoning

Strengthen

MEDIUM

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Human beings can see the spatial relations among objects by processing information conveyed by light. Scientists trying to build computers that can detect spatial relations by the same kind of process have so far designed and built stationary machines. However, these scientists will not achieve their goal until they produce such a machine that can move around in its environment.

Which of the following, if true, would best support the prediction above?

Human beings are dependent on visual cues from motion in order to detect spatial relations.

Human beings can often easily detect the spatial relations among objects, even when those objects are in motion.

Detecting spatial relations among objects requires drawing inferences from the information conveyed by light.

Although human beings can discern spatial relations through their sense of hearing, vision is usually the most important means of detecting spatial relations.

Information about the spatial relations among objects can be obtained by noticing such things as shadows and the relative sizes of objects.

Solution

Passage Analysis:

Text from Passage	Analysis
Human beings can see the spatial relations among objects by processing information conveyed by light.	What it says: Humans detect how objects relate to each other in space by using light information What it does: Sets up the basic process that scientists want to copy What it is: Background fact about human vision
Scientists trying to build computers that can detect spatial relations by the same kind of process have so far designed and built stationary machines.	What it says: Scientists have created computers that copy human spatial vision, but these machines don't move What it does: Shows current progress and reveals a key limitation compared to the human process What it is: Current state of scientific development
However, these scientists will not achieve their goal until they produce such a machine that can move around in its environment.	What it says: Scientists won't succeed unless they build a moving machine What it does: Makes a prediction that contradicts the apparent success mentioned before What it is: Author's prediction/main claim

Argument Flow:

"The argument starts by establishing how humans process spatial information, then describes what scientists have accomplished so far (stationary machines), and finally predicts they need mobility to truly succeed."

Main Conclusion:

"Scientists won't achieve their goal of building computers that detect spatial relations like humans do until they create machines that can move around."

Logical Structure:

"The argument assumes there's something essential about movement that the current stationary machines are missing. It suggests that true spatial detection requires mobility, though it doesn't explicitly explain why movement is necessary."

Prethinking:

Question type:

Strengthen - We need to find information that would make the author's prediction more believable. The prediction is that scientists won't achieve their goal of building computers that detect spatial relations like humans do until they make machines that can move around.

Precision of Claims

The key claim is very specific - scientists will NOT achieve their goal UNTIL they produce a machine that can MOVE around in its environment. This is about the necessity of movement for success, not just improvement.

Strategy

To strengthen this prediction, we need information that explains WHY movement is essential for detecting spatial relations the way humans do. We should look for evidence that shows either: (1) human spatial detection fundamentally requires movement, (2) stationary machines miss crucial spatial information that only movement can provide, or (3) the goal cannot be achieved without the mobility component that humans naturally have.

Answer Choices Explained

Human beings are dependent on visual cues from motion in order to detect spatial relations.

This directly strengthens the prediction by explaining WHY movement is necessary. If humans depend on visual cues from motion to detect spatial relations, then stationary machines are fundamentally missing a crucial component of the human process they're trying to replicate. This provides strong logical support for why scientists won't succeed until they build moving machines - because motion-based visual information is essential, not optional.

Human beings can often easily detect the spatial relations among objects, even when those objects are in motion.

This actually works against the prediction. If humans can easily detect spatial relations even when objects are moving, this suggests that movement isn't necessarily required for spatial detection. This would weaken rather than strengthen the claim that machines need to move around to succeed.

Detecting spatial relations among objects requires drawing inferences from the information conveyed by light.

While this describes part of the process mentioned in the passage, it doesn't explain why movement specifically is necessary. Drawing inferences from light information could theoretically be done by stationary machines, so this doesn't strengthen the prediction that mobility is essential.

Although human beings can discern spatial relations through their sense of hearing, vision is usually the most important means of detecting spatial relations.

This is about comparing vision to hearing for spatial detection, but it doesn't address the mobility issue at all. Whether vision is more important than hearing doesn't explain why moving machines would be superior to stationary ones for detecting spatial relations.

Information about the spatial relations among objects can be obtained by noticing such things as shadows and the relative sizes of objects.

This describes various types of visual information (shadows, relative sizes) that can help with spatial detection, but none of these necessarily require the machine itself to move around. Stationary machines could potentially notice shadows and relative sizes, so this doesn't support the prediction about needing mobility.

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