Human and computer interaction in information system design for managing business

Artificial intelligence seems to be all pervasive and slowly has become an integral part of commercial entities. However, there needs to be an approach that can integrate human and machine interaction and make it a sustainable implementation. Using framework developed by Mohapatra ( 2019 ), we find...

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Bibliographic Details
Published in:Information systems and e-business management 2021-03, Vol.19 (1), p.1-11
Main Author: Mohapatra, Sanjay
Format: Article
Language:English
Subjects:
Artificial intelligence
Banking
Business and Management
Cognition & reasoning
Cognitive ability
Domains
Explicit knowledge
Information Systems Applications (incl.Internet)
IT in Business
Knowledge management
Management
Original Article
Retail banking
Robots
Semantics
Systems design
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Summary:Artificial intelligence seems to be all pervasive and slowly has become an integral part of commercial entities. However, there needs to be an approach that can integrate human and machine interaction and make it a sustainable implementation. Using framework developed by Mohapatra ( 2019 ), we find that such parameters that can improve physical interactions with humans and domain processes. This article is an attempt to characterise these challenges and to exhibit a set of key decisional issues that need to be addressed for a cognitive robot to successfully share space and tasks with a human in retial services in a banking domain (Yang et al. in Inf Syst e-Bus Manag 17(1):1–25, 2019). Here, we identify first the needed individual and collaborative cognitive skills from the published framework and then apply them to a case study in retail banking domain. The article discusses each of these abilities, presents working implementations, and shows how they combine in a coherent and original deliberative architecture for human–robot interaction, which can be used for servicing customers (Tobias and Sebastian in Inf Syst e-Bus Manag 16(3):493–546, 2018). Supported by experimental results, we eventually show how explicit knowledge management, both symbolic and geometric, proves to be instrumental to richer and more natural human–robot interactions by pushing for pervasive, human-level semantics within the robot’s deliberative system.
ISSN:1617-9846
1617-9854
DOI:10.1007/s10257-020-00475-3