Explaining Cognitive Computing Through the Information Systems Lens
January 16, 2022 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Samaa Elnagar, Manoj Thomas
arXiv ID
2201.05945
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.ET,
cs.IR
Citations
3
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Cognitive computing (COC) aims to embed human cognition into computerized models. However, there is no scientific classification that delineates the nature of Cognitive Computing. Unlike the medical and computer science fields, Information Systems (IS) has conducted very little research on COC. Although the potential to make important research contributions in this area is great, we argue that the lack of a cohesive interpretation of what constitutes COC has led to inferior COC research in IS. Therefore, we need first to clearly identify COC as a phenomenon to be able to identify and guide prospective research areas in IS. In this research, a phenomenological approach is adopted using thematic analysis to the published literature in COC research. Then, we discuss how IS may contribute to the development of design science artifacts under the COC umbrella. In addition, the paper raises important questions for future research by highlighting how IS researchers could make meaningful contributions to this emerging topic.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted