-------- Forwarded Message -------- Subject: [AISWorld] FINAL CFP: HICSS-52 AI, Machine Learning, IoT, & Analytics: Exploring the Implications for KM & Innovation Management Date: Mon, 11 Jun 2018 01:25:30 -0500 From: Rhonda Syler rhonda.syler@gmail.com To: aisworld@lists.aisnet.org CC: Ron Freeze rfreeze@walton.uark.edu

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

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 on knowledge management - knowledge capture, acquisition, transfer, storage, and flow – as well as the behavior implications of the development and use of such systems · Studies that focus on the interactions between man and machine, particularly in terms of knowledge acquisition, transfer, management, and storage · Development frameworks for the use of big data flows · Papers that focus on the challenges of data storage from cognitive computing systems · Management and construction of disparate data sources focused on the Internet of Things · Papers that focus on the behavioral aspect of the interactions between man and machine such as trust and cognitive effort · Studies examining the factors that influence the development, adoption, use and success of cognitive computing systems · Empirical studies converting big data to actionable information and knowledge · Case Studies on data scientist success · Studies that examine the role of analytics or visualization in cognitive computing ecosystems · Methodologies for determining the frequency and granularity of data stream snapshots necessary for knowledge creation · Papers that make a theoretical contribution to the dynamics of the interaction between man and machine in the context of cognitive computing systems

*Papers must be submitted through HICSS-52 submission system. For more information and submission instructions, visit **http://* *http://hicss.hawaii.edu/* http://amcis2016.aisnet.org/index.php/sessions/call-for-papers*. For other questions contact mini-track chairs, Ron Freeze,* *rfreeze@walton.uark.edu* rfreeze@walton.uark.edu*, or Rhonda Syler, * *rsyler@walton.uark.edu* rsyler@walton.uark.edu*, University of Arkansas.*

*IMPORTANT DATES:* *Paper Submission Deadline*: June 15, 2018, 11:59 p.m. HST

*Notice of Acceptance/Rejection:* August 17, 2018

*Final Manuscripts for Publication Due:* September 22, 2018

*Deadline for at least one author to register:* October 1, 2018

*Mini-track Co-chairs:*

*Ronald D. Freeze (Primary Contact) Rhonda A. Syler*

Department of Information Systems Department of Information Systems

University of Arkansas University of Arkansas

Sam M. Walton College of Business Sam M. Walton College of Business

204 Business Building 204 Business Building

1 University of Arkansas 1 University of Arkansas

Fayetteville, Arkansas 72701-1201 Fayetteville, Arkansas 72701-1201

(479) 575-6961 Direct (479) 575-4743 Direct

(479) 575-4168 Fax (479) 575-4168 Fax

e-mail: rfreeze@walton.uark.edu e-mail: rsyler@walton.uark.edu

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