TY - CHAP
T1 - Supporting business decision-making
T2 - one professional at a time
AU - Bednar, Peter
AU - Welch, Christine
AU - Imrie, Peter
PY - 2014
Y1 - 2014
N2 - This paper discusses the potential for personalized, user-owned decision-support systems. It can be readily seen that there are benefits from analysis of ‘Big Data’ that could not be attained through more traditional means, e.g. insurance and credit card fraud can be detected more readily when it is possible to analyze integrated data across multiple servers owned and controlled by separate organizations. However, high-level data analysis, though useful, cannot be trusted to provide all the answers to organizational ‘questions’. Individuals need to be able to inform themselves in complex decision situations and for this purpose there can be no substitute for ‘little data’ from wherever this is to be drawn. We explore a potential type of support that could overcome the barriers to professional creativity arising through lack of trust in decision-support systems owned and controlled from senior management. The Virtual Personal Assistant described uses natural language processing to interact with a professional user in the context of messy, situated problems, and in private. It has capability to learn from user-interactions and therefore to co-evolve contextually. A ‘little data’ system such as this can therefore help to improve relevance of user understandings in a relatively risk free environment.
AB - This paper discusses the potential for personalized, user-owned decision-support systems. It can be readily seen that there are benefits from analysis of ‘Big Data’ that could not be attained through more traditional means, e.g. insurance and credit card fraud can be detected more readily when it is possible to analyze integrated data across multiple servers owned and controlled by separate organizations. However, high-level data analysis, though useful, cannot be trusted to provide all the answers to organizational ‘questions’. Individuals need to be able to inform themselves in complex decision situations and for this purpose there can be no substitute for ‘little data’ from wherever this is to be drawn. We explore a potential type of support that could overcome the barriers to professional creativity arising through lack of trust in decision-support systems owned and controlled from senior management. The Virtual Personal Assistant described uses natural language processing to interact with a professional user in the context of messy, situated problems, and in private. It has capability to learn from user-interactions and therefore to co-evolve contextually. A ‘little data’ system such as this can therefore help to improve relevance of user understandings in a relatively risk free environment.
KW - Personal decision-support systems; situated problems; virtual personal assistant; contextual dependencies; little data
U2 - 10.3233/978-1-61499-399-5-471
DO - 10.3233/978-1-61499-399-5-471
M3 - Chapter (peer-reviewed)
SN - 978-1614993995
VL - 261
T3 - Frontiers in Artificial Intelligence and Applications
SP - 471
EP - 482
BT - DSS 2.0 – Supporting Decision Making with New Technologies
A2 - Phillips-Wren, Gloria
A2 - Carlsson, Sven
A2 - Respicio , Ana
A2 - Brezillon , Patrick
PB - IOS Press
CY - Paris
ER -