Analysis of noise and bias errors in intelligence information systems.
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| Title: | Analysis of noise and bias errors in intelligence information systems. |
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| 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 |
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| 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] |
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| ISSN: | 23301635 |
| DOI: | 10.1002/asi.24707 |
