[AISWorld] CFP: HICSS-53 Minitrack: AI, Machine Learning, IoT, and Analytics: Exploring Implications for KM and Innovation

[Rhonda Syler]

*HICSS-53*

*January 8-10, 2020*

Grand Wailea, Maui, Hawaii




*MINI-TRACK: AI, Machine Learning, IoT, and Analytics: Exploring the
Implications for Knowledge Management & Innovation*

 *Mini-Track Chairs:*

*Ron Freeze, **University of Arkansas, *rfreeze at walton.uark.edu

*Rhonda Syler, **University of Arkansas, *rsyler at walton.uark.edu


The exponential growth of data-intensive technologies such as IoT, IoMT,
augmented reality, machine learning applications, and artificial
intelligence is creating a rich landscape for the collection, organization,
storage, and dissemination of knowledge. The implications of the impact
these technologies have on the knowledge management ecosystem include
process integration issues, data storage and data management challenges,
behavioral issues such as trust in output from these technologies, and even
challenges in the analytics process. Additionally, understanding the
potential impacts of these systems helps inform how to build and use the
infrastructures and processes to achieve improved decision making and
organizational performance.

This mini-track seeks a focus on studies that contribute to the
understanding of the characteristics of these artifacts and the challenges
they present in the context of knowledge management and knowledge creation.
All aspects of the impacts of these artifacts on any facet of knowledge
management - knowledge capture, acquisition, transfer, storage, and flow –
as well as the behavior implications of the development and use of such
systems are within the scope of interest.

We welcome both theoretical and design-science based papers that focus on
AI, machine learning, IoT, IoMT or other related data-intensive
technologies as it relates to KM or knowledge innovation. Paper topics
include, but are not limited to:

·         All aspects of the impacts of AI/Machine Learning, IoT, and
Analytics on knowledge management - knowledge capture, acquisition,
transfer, storage, and flow

·         Behavioral implications of the development and use AI/ML, IoT, or
analytics particularly in the context of knowledge management

·         Development frameworks for the use of big data flows

·         The challenges of data storage from cognitive computing and IoT
systems

·         Management of disparate data sources in the context of IoT

·         Behavioral aspects of the interactions between man and machine,
such as trust and cognitive effort, in the context of AI/ML, IoT, or
analytics

·         Factors influencing the development, adoption, use and/or success
of cognitive computing systems

·         Empirical studies converting big data to actionable information
and knowledge

·         Studies that examine the role of analytics or visualization in
cognitive computing or IoT ecosystems

·         Methodologies for determining the frequency and granularity of
data stream snapshots necessary for knowledge creation

·         Dynamics of the interaction between man and machine in the
context of cognitive computing systems



Papers must be submitted through HICSS-53 submission system.
http://hicss.hawaii.edu/.




*Important Dates: **Submission Period Opens: *April 15, 2019

*Paper Submission Deadline*: June 15, 2019, 11:59 p.m. HST

*Notice of Acceptance/Rejection:* August 17, 2019

*Final Manuscripts for Publication Due:* September 22, 2019

*Deadline for at least one author to register:* October 1, 2019



*Mini-Track Chairs: *

*Ron Freeze*

*University of Arkansas*

rfreeze at walton.uark.edu



*Rhonda Syler*

*University of Arkansas*

rsyler at walton.uark.edu



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