Self-study
In any field, experience is required for a proficient person to become an expert. ███████ ███████████ █ ██████████ ██████ █████████ ████████ █ █████████ ██ █████ ██████████ ████ ██████ ██ ██████████ █████████ ████████ ██ ████ ███ ██████████ ████ ██ ███ ████████ ██ ██████████ ███ ███ ████ ██████ ████████████ ███████ ████████ ██████ ██ ██ ████ ██ █████ ████████ ████████ █████████ ████ ███ ███████ ██ █████ ████████ ██ ████ ██ ████████████ ███ █████████ ██ █████ ████████ ███ ███████ ████ ███ ██████████ ██ █████████ ██ ███████████ ██ ███ ██████ ██████ █████ ██████ ██ ███ ████ ██ █████ ███ ██████
Summary
The author concludes that computers cannot be as good as human experts.
Why?
Because experts, through experience, develop a collection of model situations that allows an immediate, intuitive response to a new situation.
In addition, the knowledge of human experts is not stored within their brains in the form of rules and facts.
Notable Assumptions
The author assumes that computers cannot develop a collection of model situations that allows an immediate, intuitive response to a new situation.
The author assumes that computers cannot store experience if it is not in the form of rules and facts.
6.
The argument requires the assumption ██ █████ ███ ██ ███ ██████████
a
Computers can show ██ ████ ███████████ ██ ██████████ ██ █ █████████ ████ ████ █████ ████ ████ ██ █████ ██████████
Not necessary, because the level of “originality” in a response is irrelevant to the reasoning. The argument is that computers can’t be as good as human experts, because computers can’t store the same kind of experience-based knowledge in their systems as human experts can store in their brains. But whether a computer can come up with a more “original” response than the designers intended has nothing to do with computers’ inability to store experience-based knowledge in their systems.
b
The knowledge of █████ ███████ ██████ ██ ██████████ ████████ ████ ███ ████ ██ ███████████ ████ █ ████████ ███ ██████
Necessary, because if it were not true — if the knowledge of human experts CAN be adequately rendered into info thta a computer can store — then this opens the possibility that computers CAN store the kind of experience-based knowledge that experts accumulate. This would show that the mere fact experts don’t store knowledge in the form of rules/facts does not automatically prove computers can’t be as good as experts.
c
Human experts rely ██ ███████████ ████ ███ ██ █████████ ██ █████ ███ █████ ████ ████ ███████ ██ ███ ███████████
Not necessary, because we’re told that human experts do NOT store experience-based info in the form of rules and facts.
d
Future advances in ████████ ██████████ ████ ███ ██████ █████████ ███████ ██ ███████ ███████ ███████ ███████ ██ ████████████
Not necessary, because the reason the author believes computers can’t be as good as experts has nothing to do with the amount of knowledge that computers can stores. It has to do with the fact human experts don’t store their experience-based knowledge in the form of rules and facts.
e
Human experts rely ███████ ██ █████████ █████ ████ ███ ██████████ █ █████████ ██ █████ ███████████
Not necessary, because we’re told that developing a repertory of model situations allows for an intuitive response. But we’re not told that intuition is involved in building that repertory (collection) of model responses. Even if intuition is NOT part of what builds the repertory, the reportory can still allow for intuitive responses based on the knowledge in that repertory.