NVIDIA's task force, the argument claims, is exceptional in how well it evaluates emerging AI safety standards. Dr Lin, a part of the task force, will benefit immensely from the praise the task force has garnered, as her clientele who adopts her independent reports - related ones, or new ones in the future - can hold her by the same standards.
Naturally, we need to pick a choice with the same flaw - That just because A did B correct, her doing of C, D, E and will also be correct.
Let's see which choice most conforms to this thinking.
A. This essentially states, because X team won an award, Caleb, who WAS NOT a part of the time, will design something award-winning. As there's no participation of Caleb in the winning team, this isn't the same logic.
B: This essentially states, X found success with his benchmarking suite. His role with Y, another product, will have another qualitative advantage. Eliminate, because we're looking at variable advantages here.
C: Priya's university is widely respected. Priya's a part of the university - so she has to be the reason why the university is widely respected. Definitely eliminate.
D: This states, a company produced a strong product. A person part of it, his future / alternate work, will be just as reliable. Direct parallel to the reasoning.E: This talks about analysts who voted to support something, rather than an achievement / success, and thus, predicts behavior rather than presents a continuation of success. Please eliminate.
Bunuel
A leading tech journal recently praised the joint research panel assembled by NVIDIA, calling its twelve-engineer task force “remarkably rigorous and unbiased” in its evaluation of emerging AI safety standards. Since Dr. Lin served on that task force, corporate clients adopting her independent AI-audit reports can confidently expect the same level of rigor and impartiality.
Which of the following exhibits flawed reasoning most similar to that in the passage?
A. A team at a robotics company won an award for designing a drone-navigation module. Since Caleb worked on a different product line at the same company, his new project is also likely award-winning.
B. An open-source contributor helped build a widely trusted machine-learning benchmark suite. Since he tested a separate model last year, that model must also represent industry-standard quality.
C. The AI ethics division at Priya’s university is widely respected for its rigorous verification methods. Since Priya recently published a rigorous verification review, she is likely one of the contributors to the division’s strong reputation.
D. A multi-institutional consortium produced a highly reliable dataset for autonomous-vehicle training. Since Dr. Ahmadi was a member of that consortium, her solo data-labeling work for a different project will be just as reliable.
E. A group of analysts at a cloud-security firm unanimously voted to support a shift to zero-trust architecture. Since Jordan is one of those analysts, she also supports a transition to zero-trust practices.
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