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Analysis of noise and bias errors in intelligence information systems.
- Source :
- Journal of the Association for Information Science & Technology; Dec2022, Vol. 73 Issue 12, p1755-1775, 21p, 2 Diagrams, 3 Charts, 4 Graphs
- Publication Year :
- 2022
-
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]
- 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
Subjects
Details
- Language :
- English
- ISSN :
- 23301635
- Volume :
- 73
- Issue :
- 12
- Database :
- Complementary Index
- Journal :
- Journal of the Association for Information Science & Technology
- Publication Type :
- Academic Journal
- Accession number :
- 160177903
- Full Text :
- https://doi.org/10.1002/asi.24707