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 4 publications

(1 citation statement)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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

View full text Add to dashboard Cite

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.

show abstract

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

View full text Add to dashboard Cite

Extending the indexing vocabulary of case based reasoning with task specific features

Fischer

Smith

Proceedings Eighth Conference on Artificial Intelligence for Applications

Self Cite

View full text Add to dashboard Cite

One of the central issues in case-based reasoning is the choice of an indexical vocabulary that allows for e f i -cient retrieval of experiential knowledge from memory. Presently, most systems use a vocabulary of domain concepts specific to the application domain (medicine, engineering, etc...). This paper proposes a new additional indexical Vocabulary based on features of abstract problem types(planning, diagnosis, etc.. .). The rationale f o r such a vocabulary is supported by empirical data gathered in the domain of alloantibody identification, and by the interpretation of this data in terms of the computational complezity of abductive reasoning. Finally a case-based reasoning model of abduction is proposed that integrates both domain and problem type specific indexical vocabulary. The advantages of this model in terms of memory retrieval, case adaptation and problem solving are discussed.Area :Diagnosis, medicine. AI Topics: Knowledge representation, case based reasoning, problem solving. Impact: The Generic Task(GT) paradigm has been a successful approach to knowledge based systems engineering. The work presented in this paper is an extension of the G T paradigm to case based reasoning.

show abstract

Errors in abductive reasoning

Cited by 4 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

Extending the indexing vocabulary of case based reasoning with task specific features

Contact Info

Product

Resources

About