View in EDS HTML Full Text PDF Full Text

Analysis of noise and bias errors in intelligence information systems.

Saved in:
Bibliographic Details
Title: Analysis of noise and bias errors in intelligence information systems.
Authors: Labib, Ashraf1,2 ashraf.labib@port.ac.uk, Chakhar, Salem1,2, Hope, Lorraine3, Shimell, John4, Malinowski, Mark4
Source: Journal of the Association for Information Science & Technology. Dec2022, Vol. 73 Issue 12, p1755-1775. 21p. 2 Diagrams, 3 Charts, 4 Graphs.
Subjects: Counterterrorism, Teams in the workplace, Experimental design, Judgment (Psychology), Labor productivity, Noise, Research methodology, Security systems, Information professionals, Military service, Client/server computing, Human error, Research funding, Decision making, Scale analysis (Psychology), Professional competence, Information storage & retrieval systems, Systems development
Geographic Terms: United Kingdom
Abstract: An intelligence information system (IIS) is a particular kind of information systems (IS) devoted to the analysis of intelligence relevant to national security. Professional and military intelligence analysts play a key role in this, but their judgments can be inconsistent, mainly due to noise and bias. The team‐oriented aspects of the intelligence analysis process complicates the situation further. To enable analysts to achieve better judgments, the authors designed, implemented, and validated an innovative IIS for analyzing UK Military Signals Intelligence (SIGINT) data. The developed tool, the Team Information Decision Engine (TIDE), relies on an innovative preference learning method along with an aggregation procedure that permits combining scores by individual analysts into aggregated scores. This paper reports on a series of validation trials in which the performance of individual and team‐oriented analysts was accessed with respect to their effectiveness and efficiency. Results show that the use of the developed tool enhanced the effectiveness and efficiency of intelligence analysis process at both individual and team levels. [ABSTRACT FROM AUTHOR]
Copyright of Journal of the Association for Information Science & Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 160177903
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Analysis of noise and bias errors in intelligence information systems.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Labib%2C+Ashraf%22">Labib, Ashraf</searchLink><relatesTo>1,2</relatesTo><i> ashraf.labib@port.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Chakhar%2C+Salem%22">Chakhar, Salem</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Hope%2C+Lorraine%22">Hope, Lorraine</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Shimell%2C+John%22">Shimell, John</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Malinowski%2C+Mark%22">Malinowski, Mark</searchLink><relatesTo>4</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Journal+of+the+Association+for+Information+Science+%26+Technology%22">Journal of the Association for Information Science & Technology</searchLink>. Dec2022, Vol. 73 Issue 12, p1755-1775. 21p. 2 Diagrams, 3 Charts, 4 Graphs.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Counterterrorism%22">Counterterrorism</searchLink><br /><searchLink fieldCode="DE" term="%22Teams+in+the+workplace%22">Teams in the workplace</searchLink><br /><searchLink fieldCode="DE" term="%22Experimental+design%22">Experimental design</searchLink><br /><searchLink fieldCode="DE" term="%22Judgment+%28Psychology%29%22">Judgment (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Labor+productivity%22">Labor productivity</searchLink><br /><searchLink fieldCode="DE" term="%22Noise%22">Noise</searchLink><br /><searchLink fieldCode="DE" term="%22Research+methodology%22">Research methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Security+systems%22">Security systems</searchLink><br /><searchLink fieldCode="DE" term="%22Information+professionals%22">Information professionals</searchLink><br /><searchLink fieldCode="DE" term="%22Military+service%22">Military service</searchLink><br /><searchLink fieldCode="DE" term="%22Client%2Fserver+computing%22">Client/server computing</searchLink><br /><searchLink fieldCode="DE" term="%22Human+error%22">Human error</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+making%22">Decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Scale+analysis+%28Psychology%29%22">Scale analysis (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Professional+competence%22">Professional competence</searchLink><br /><searchLink fieldCode="DE" term="%22Information+storage+%26+retrieval+systems%22">Information storage & retrieval systems</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+development%22">Systems development</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22United+Kingdom%22">United Kingdom</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: An intelligence information system (IIS) is a particular kind of information systems (IS) devoted to the analysis of intelligence relevant to national security. Professional and military intelligence analysts play a key role in this, but their judgments can be inconsistent, mainly due to noise and bias. The team‐oriented aspects of the intelligence analysis process complicates the situation further. To enable analysts to achieve better judgments, the authors designed, implemented, and validated an innovative IIS for analyzing UK Military Signals Intelligence (SIGINT) data. The developed tool, the Team Information Decision Engine (TIDE), relies on an innovative preference learning method along with an aggregation procedure that permits combining scores by individual analysts into aggregated scores. This paper reports on a series of validation trials in which the performance of individual and team‐oriented analysts was accessed with respect to their effectiveness and efficiency. Results show that the use of the developed tool enhanced the effectiveness and efficiency of intelligence analysis process at both individual and team levels. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of the Association for Information Science & Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=160177903
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1002/asi.24707
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 21
        StartPage: 1755
    Subjects:
      – SubjectFull: Counterterrorism
        Type: general
      – SubjectFull: Teams in the workplace
        Type: general
      – SubjectFull: Experimental design
        Type: general
      – SubjectFull: Judgment (Psychology)
        Type: general
      – SubjectFull: Labor productivity
        Type: general
      – SubjectFull: Noise
        Type: general
      – SubjectFull: Research methodology
        Type: general
      – SubjectFull: Security systems
        Type: general
      – SubjectFull: Information professionals
        Type: general
      – SubjectFull: Military service
        Type: general
      – SubjectFull: Client/server computing
        Type: general
      – SubjectFull: Human error
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Decision making
        Type: general
      – SubjectFull: Scale analysis (Psychology)
        Type: general
      – SubjectFull: Professional competence
        Type: general
      – SubjectFull: Information storage & retrieval systems
        Type: general
      – SubjectFull: Systems development
        Type: general
      – SubjectFull: United Kingdom
        Type: general
    Titles:
      – TitleFull: Analysis of noise and bias errors in intelligence information systems.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Labib, Ashraf
      – PersonEntity:
          Name:
            NameFull: Chakhar, Salem
      – PersonEntity:
          Name:
            NameFull: Hope, Lorraine
      – PersonEntity:
          Name:
            NameFull: Shimell, John
      – PersonEntity:
          Name:
            NameFull: Malinowski, Mark
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Text: Dec2022
              Type: published
              Y: 2022
          Identifiers:
            – Type: issn-print
              Value: 23301635
          Numbering:
            – Type: volume
              Value: 73
            – Type: issue
              Value: 12
          Titles:
            – TitleFull: Journal of the Association for Information Science & Technology
              Type: main
ResultId 1