Seeing (Movement) is Believing: The Effect of Motion on Perception of Automatic Systems Performance

Section 2.2 (page unavailable) describes how explanations can help users understand a system but can also overwhelm them, and how animation can aid understanding yet sometimes cause confusion. This supports the idea that presentation matters, but the paper does not specifically say that differences in presentation account for the contradictory results cited in the sentence. (LLM, conf=0.78)

Section 3.4 describes collecting users’ evaluations after presenting systems under different conditions, including in crowdsourcing studies. But participants viewed system outputs rather than hypothetical scenarios; Section 3.2 says the MTurk samples were kept to eight participants per condition, and Section 6 describes crowdsourcing as less controlled than the lab. The paper therefore supports collecting user reactions online, but not the claimed hypothetical-scenario method or a demonstrated ability to collect controlled data at scale. (LLM, conf=0.83)

Section 2.2 (page unavailable) says explanations can help users understand smart systems but can also overwhelm or confuse them; it explores animation as another way to present system activity. This supports the idea that presentation matters, but the paper does not say that presentation accounts for contradictory findings about transparency’s effects; it also identifies system uncertainty as a reason effects differ. (LLM, conf=0.78)

The Methodology and Procedure sections describe simulated system tasks with standardized conditions, including studies conducted through MTurk, so the paper supports collecting user data through such methods. But Participants says recruitment was deliberately limited to eight people per condition, and Study 2 calls crowdsourcing less controlled than a lab; the paper does not establish collection of controlled data at scale. Page numbers are unavailable in our copy. (LLM, conf=0.84)

Section 2.2 (page unavailable) discusses how explanations can improve understanding and trust, but does not report that users anticipated preferring transparency before using a system. I searched for pre-use expectations and preferences; the Procedure section (3.4, page unavailable) describes an initial questionnaire but reports no such preference. (LLM, conf=0.74)

Section 2.2 discusses how explanations can help users understand smart systems, but it does not report that users anticipated preferring transparency before use. Section 3.4 describes a questionnaire before the task and evaluations after participants saw the systems; it does not report a pre-use transparency preference. Searches for that preference and its timing found no supporting passage in our copy. (LLM, conf=0.72)

Section 3.4 (page unavailable) describes participants viewing system interfaces and evaluating their performance, rather than reacting to hypothetical scenarios. Section 2.2 discusses prior studies of explanations and system intelligibility, but does not describe the claimed scenario-based method. Searches for hypothetical scenarios and vignettes found no passage establishing it. (LLM, conf=0.72)