Information technology in organisations and societies : multidisciplinary perspectives from AI to technostress / edited by Zach W. Y. Lee, Tommy K. H. Chan, and Christy M. K. Cheung.

Format:

Book

Contributor:

Lee, Zach W. Y., editor.

Chan, Tommy K. H., editor.

Cheung, Christy M. K., editor.

Language:

English

Subjects (All):

Information technology.

Electronic data processing.

Physical Description:

1 online resource (231 pages)

Place of Publication:

Bingley, England : Emerald Publishing Limited, [2021]

Summary:

Information Technology in Organisations and Societies: Multidisciplinary Perspectives from AI to Technostressconsolidates studies on key issues and phenomena concerning the positive and negative aspects of IT use as well as prescribing future research avenues in related research.

Contents:

Intro

Half Title Page

Title Page

Copyright Page

Dedication Page

Contents

List of Figures and Tables

About the Editors

About the Contributors

Preface

Acknowledgements

Chapter 1: AI and Its Implications for Organisations

Introduction

Components of AI

Analytics-based Prediction

Automation

Goals

Standardisation

Personalisation

Reducing Human Involvement

Maximising Use

Signal Innovation

Types of AI

Based on Task Orientation

Weak AI. Due to a defined scope of tasks and suitable expected effects, adoption of weak AI has particularly been high. Top management of organisations chooses to invest in weak AI to perform repetitive tasks which are otherwise performed by low to medium

Strong AI. Strong AI refers to systems with intellectual capability that is functionally equal to a human's (Open computing facility (OCF)

Searle, 1980). Where weak AI can perform specific tasks in specific domains, strong AI is expected to be akin to h

Agency of AI Technology

Human-AI Hybrid Systems. AI technologies have found more acceptance and success when used with a 'human in the loop' (Nushi, Kamar, Horvitz, &amp

Kossmann, 2016). 'Human in the loop' ML systems have been used across a variety of contexts from semi-autonomous

Human-AI Hybrid System with Human as the Expert. Human-AI hybrid system with human as the expert are systems where a human expert uses recommendations from the AI algorithms to aid their decision making in complex tasks (Athey, Bryan, &amp

Gans, 2020

Stone

Human-AI Hybrid System with AI as the Expert. Human-AI hybrid system with AI as the expert is the system where humans follow recommendations of AI. Humans consider the system the expert considering that AI-based prediction system is developed with compete.

Fully Autonomous Systems. Fully autonomous systems are AI systems that can perform their function by collecting and processing information automatically (Totschnig, 2020). They do not need human interference or help at any stage. Chatbots and conversation

Vulnerabilities

Training Data Integrity

Concept Drift. Concept drift occurs when the accuracy of the prediction is threatened due to change in the context of target variable changes in unexpected ways. This can happen if significant time has passed between data collection and the implementation

Covariance Shift. Covariance shift occurs when the accuracy of the prediction is threatened due to difference in the covariance of training data and data the system is supposed to work with (Simester et al., 2019). This can happen if the environments of t

Information Loss. Information Loss occurs when sufficient variables are not available for suitable prediction (Simester et al., 2019). The model may still perform the prediction by aggregating the required variables based on other inputs, but in the absen

Data Imbalance. Data imbalance occurs when some data categories are over or under-represented (Simester et al., 2019). This may happen if data collected is not representative of the population. For example, in a forum to rate restaurants, the majority of

Model Poisoning Attacks

Programmer Bias

Technology

Black-box Algorithms. ML and deep learning have found mainstream ­acceptance as they can be trained quickly with data spanning decades. While some parts of these algorithms are interpretable (e.g. decision trees), significant parts of the algorithms are.

Sensor Failures. Robotics and IoT have also made a lot of progress in the past few decades. However, sensor faults can be blamed for many of the unintended consequences in AI systems. For example, computer vision relies heavily on cameras capturing accura

Reliance on Cloud. Most AI systems that use high-performance GPUs connect to them using the cloud. While the cloud access and redundancies offered by cloud services providers do hedge some risk, reliance on high-speed internet connectivity also poses as a

Unintended Consequences

Backfire

Negative Spillover

False Progress

Recommendations

Clear Objectives

Choosing the Right Type of AI

Mitigating Vulnerabilities

Workforce Implications

Conclusion

References

Chapter 2: Collaboration of Human and Machine for Knowledge Work: An Organisational Transformation Framework for Data-driven Decision-making

1. Introduction

2. Overview of Key Concepts

2.1. Knowledge Work

2.2. Intelligent Machines and Big Data

2.3. Data-driven Decision-making in an Organisational Context

2.4. Knowledge Work and Data-driven Decision-making in the Age of Intelligent Machines

3. Research Methodology

4. Organisational Transformation Framework for Data-driven Decision-making Based on the Collaboration of Human and Machine for Knowledge Work (OTxDD Framework)

5. Application and Evaluation of the Framework

5.1. Overview of the Telecommunication Organisation

5.2. Application of the Proposed OTxDD Framework

6. OTxDD Update and Contribution

6.1. Implications for Research

6.2. Implications for Practice

7. Conclusion

Chapter 3: Does Technostress Trigger Insider Threat? A Conceptual Model and Mitigation Solutions

Information Technology and Stress (Technostress)

Digitisation and IS Security.

Technostress and Information Security (A Proposed Conceptual Model)

Counteraction Strategies to Respond to Information Security Threats and Technostress

Chapter 4: Sociological Mechanisms Behind ICT-Related Technostress in the Workplace

Technostress

ICT-related Stressors

ICT Errors. ICT errors represent any ICT crash or login difficulties. Within technostress research, we see a tendency to investigate ICT errors from a neurophysiological perspective. For example, research reports that an IT error or a system breakdown can

Interruptions. ICTs can expose the individual to an endless stream of email notifications, reminders and instant messages (Tams et al., 2018). When workers feel they have control over interruptions, they perceive them as less disturbing (Tams et al., 2018

Work-home Conflict. Constant connectivity comes at the cost of blurred work-home boundaries. Research shows that employees who feel that they can be reached through ICTs at any time, experience a perceived work-home conflict (Ayyagari et al., 2011).

Role Ambiguity. Receiving demands for attention by always having one's email open or getting other notifications takes time from other work tasks. The interruptions and the need to multitask add a layer of decision making and can lead to individuals exper

Continuous Partial Attention. As an addition to role ambiguity and multitasking, continuous partial attention refers to the motivation that leads people to certain behaviours - for example, a desire to be more productive and efficient, being afraid of mis

Electronic Leash and Expectations of Availability. Continuing on this line, ICTs have become like an electronic leash that pulls employees to work, even outside working hours. Subsequently, the time needed for rest is used for work (Sellberg &amp

Susi, 2014).

ICT Usability

Techno-overload. Techno-overload arises when it is 'too much', as when employees face an overload of information and tasks. Employees feel forced to work faster, do more work than they can handle, work with tight schedules, change their work habits, and d

Techno-invasion. Techno-invasion is the feeling of being 'always connected' and never free of ICTs. Employees report that they spend less time with their family due to ICTs, that their life is invaded due to ICT usage (Tarafdar et al., 2011). At the same

Techno-complexity. Techno-complexity can be described by the word ­'difficult', as employees find ICTs intimidating. Employees report feeling that they do not know enough about ICTs to complete their tasks, need a long time to understand and use new techn

Techno-insecurity. The techno-insecurity dimension addresses feeling 'uncomfortable'. Employees report feeling anxious about losing their jobs, a constant need to update their skills, and that they should share less knowledge with others in order to have

Techno-uncertainty. Techno-uncertainty means 'too often and unfamiliar'. Employees feel unsettled by the number of ICT updates, upgrades and the changes in the ICTs used in the organisation (Tarafdar et al., 2011).

Technostrain

Anxiety. Computer anxiety is a widely studied technostrain experience. Employees experience fear or agitation when interacting with technology, such as fear of losing information, making a mistake or finding the interaction with the computer intimidating

Fatigue. Fatigue represents a negative psychological experience produced by the use of ICT and is characterised by low psychological activation. Research makes us aware of a specific type of fatigue resulting from interacting with ICTs, called information.

Negative Attitudes Towards Technology. Fatigue and exhaustion can also lead to a distant, indifferent, sceptical and cynical attitude towards ICTs (Salanova et al., 2013). Scepticism comes from the job burnout literature and represents the display of dist.

Notes:

Description based on print version record.

Includes bibliographical references and index.

Other Format:

Print version: Lee, Zach W. Y. Information Technology in Organisations and Societies

ISBN:

1-83753-236-2