Errors in abductive reasoning

Fraser, Jane; Strohm, Patricia L.; Smith, Jack W.; Svirbely, John R.; Rudmann, Sally V.; Miller, Thomas E.; Blazina, Janice; Kennedy, Melanie S.; Smith, Philip J.

doi:10.1109/icsmc.1989.71478

Cited by 7 publications

(1 citation statement)

References 8 publications

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“…During prior interviews, we discovered that it is generally recognized among professional analysts that there is a vulnerability to prem ature closure during the analysis process. Note that there are also concerns about prem ature closure in inferential analysis tasks in other domains such as medical diagnosis (McSherry, 1997, Baldwin and Rice, 1997, Fraser et al, 1989 due to the costs of obtaining further information and in general about the effects of time pressure on hum an judgm ent and decision making (Svenson and Maule, 1993). The potential impacts of prem ature closure include a degraded quality of the analytic product and poorly calibrated confidence in the veracity of the analytic product.…”

Section: Table 24 Bases Of Confidence In Analysesmentioning

confidence: 99%

A Simulation Study of Computer-Supported Inferential Analysis Under Data Overload

Woods

Patterson

1999

Proceedings of the Human Factors and Ergonomics Society Annual

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A simulation study of inferential analysis under data overload was conducted with professional intelligence analysts. Using a process tracing methodology, patterns in information sampling and sources of inaccurate statements were identified when analysts were asked to analyze something outside their base of expertise, were tasked with a tight deadline, and had a large data set. The main contribution from this study is a better understanding of potential vulnerabilities in inferential analysis in challenging situations. These vulnerabilities are informative because they point to a set of design criteria that human-centered solutions to data overload should meet in order to be useful. These evaluation criteria are interesting, in part, because they are so difficult to address. They are not amenable to simple, straightforward adjustments or feature additions to current tools. Meeting these design criteria will require innovative design concepts.

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Section: Table 24 Bases Of Confidence In Analysesmentioning

confidence: 99%

A Simulation Study of Computer-Supported Inferential Analysis Under Data Overload

Woods

Patterson

1999

Proceedings of the Human Factors and Ergonomics Society Annual

View full text Add to dashboard Cite

show abstract

Aiding the intelligence analyst in situations of data overload: A simulation study of computer-supported inferential analysis under data overload

Patterson¹,

Roth²,

Woods³

1999

PsycEXTRA Dataset

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An empirical evaluation of the performance of antibody identification tasks

Miller

Fraser

et al. 1991

Transfusion

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Four empirical studies were conducted for better understanding of the nature of problem-solving activities by medical technologists and medical technology students when performing antibody identification tasks. The results indicated the importance of strategies that ensure the collection of converging evidence, as these strategies protect against the fallibility of commonly used heuristics and against errors due to simple slips. The results also indicate that not only do students make significant numbers of errors, but so do practicing technologists. In one of the studies covering a 1-year period, for instance, a group of 16 technologists made a total of 41 errors in 1057 cases. On the basis of these findings, several alternatives are proposed to reduce errors.

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Errors in abductive reasoning

Cited by 7 publications

References 8 publications

A Simulation Study of Computer-Supported Inferential Analysis Under Data Overload

A Simulation Study of Computer-Supported Inferential Analysis Under Data Overload

Aiding the intelligence analyst in situations of data overload: A simulation study of computer-supported inferential analysis under data overload

An empirical evaluation of the performance of antibody identification tasks

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