scholarly journals The rise of artificial intelligence – understanding the AI identity threat at the workplace

2021 ◽  
Author(s):  
Milad Mirbabaie ◽  
Felix Brünker ◽  
Nicholas R. J. Möllmann ◽  
Stefan Stieglitz
Keyword(s):  
Artificial Intelligence ◽  
Information Systems ◽  
Future Research ◽  
Identity Threat ◽  
Work Loss ◽  
Work Related ◽  
Status Position

AbstractArtificial intelligence (AI) is being increasingly integrated into enterprises to foster collaboration within humanmachine teams and assist employees with work-related tasks. However, introducing AI may negatively impact employees’ identifications with their jobs as AI is expected to fundamentally change workplaces and professions, feeding into individuals’ fears of being replaced. To broaden the understanding of the AI identity threat, the findings of this study reveal three central predictors for AI identity threat in the workplace: changes to work, loss of status position, and AI identity predicting AI identity threat in the workplace. This study enriches information systems literature by extending our understanding of collaboration with AI in the workplace to drive future research in this field. Researchers and practitioners understand the implications of employees’ identity when collaborating with AI and comprehend which factors are relevant when introducing AI in the workplace.

scholarly journals Artificial Intelligence Value Alignment Principles: The State of Art Review from Information Systems Research

2021 ◽  
Author(s):  
Shengnan Han ◽  
◽  
Shahrokh Nikou ◽  
Keyword(s):  
Artificial Intelligence ◽  
Information Systems ◽  
Information And Communication Technologies ◽  
Human Values ◽  
Future Research ◽  
Critical Question ◽  
Is Research ◽  
Systems Research ◽  
Information Systems Research ◽  
Information And Communication

t Information and communication technologies (ICTs) must be designed and used for humane ends. The rapid adoption of Artificial Intelligence (AI) has raised the critical question of whether we can ensure AI's alignment with human values to guide its design and use. We perform a selective literature review with the specific search terms of the papers published in the top information systems (basket of 8 journals and 5 AIjournals in IS) from 2000-2020 to answer this question. The findings indicate that IS research has contributed insufficiently to a deeper understanding of human values and AI value alignment principles. Moreover, the mainstream IS research on AI is mostly dominated from its technical and managerial aspects. Thus, the future research agendas are proposed accordingly. The paper provides some food for thoughts in studying human values and AI alignment within the context of IS research.

scholarly journals Learning by Doing: Twenty Successful Active Learning Exercises for Information Systems Courses

10.28945/3643 ◽  
2017 ◽  
Vol 16 ◽  
pp. 021-046 ◽  
Author(s):  
Alanah Mitchell ◽  
Stacie Petter ◽  
Al Harris
Keyword(s):  
Information Systems ◽  
Active Learning ◽  
Learning Strategies ◽  
Learning By Doing ◽  
Future Research ◽  
Work Related ◽  
Passive Learning ◽  
Learning Techniques ◽  
Active Learning Strategies ◽  
Definition Of

Aim/Purpose: This paper provides a review of previously published work related to active learning in information systems (IS) courses. Background: There are a rising number of strategies in higher education that offer promise in regards to getting students’ attention and helping them learn, such as flipped classrooms and offering courses online. These learning strategies are part of the pedagogical technique known as active learning. Active learning is a strategy that became popular in the early 1990s and has proven itself as a valid tool for helping students to be engaged with learning. Methodology: This work follows a systematic method for identifying and coding previous research based on an aspect of interest. The authors identified and assessed research through a search of ABI/Inform scholarly journal abstracts and keywords, as well as additional research databases, using the search terms “active learning” and “information systems” from 2000 through June 2016. Contribution: This synthesis of active learning exercises provides guidance for information technology faculty looking to implement active learning strategies in their classroom by demonstrating how IS faculty might begin to introduce more active learning techniques in their teaching as well as by presenting a sample teaching agenda for a class that uses a mix of active and passive learning techniques to engage student learning. Findings: Twenty successful types of active learning exercises in IS courses are presented. Recommendations for Practitioners : This paper offers a “how to” resource of successful active learning strategies for IS faculty interested in implementing active learning in the classroom. Recommendation for Researchers: This work provides an example of a systematic literature review as a means to assess successful implementations of active learning in IS. Impact on Society: An updated definition of active learning is presented as well as a meaningful list of exercises that encourage active learning both inside and outside of the IS classroom. Future Research: In relation to future research, this study highlights a number of opportunities for IS faculty in regards to new active learning activities or trends to study further.

scholarly journals A Prologue to Artificial Intelligence, Mechanical Technology, and Research Streams to inspect the Financial and Authoritative results of related Advancements

2020 ◽  
Vol 9 (9) ◽  
pp. 60-68
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Information Systems ◽  
Future Research ◽  
Mechanical Assemblies ◽  
Level Information ◽  
Self Rule

This article gives a prologue to artificial intelligence, apply autonomy, and research streams that analyze the monetary and hierarchical outcomes of these and related innovations. We depict the beginning examination of human-made brainpower and mechanical technology in the financial matters and the board writing and sum up the principal methodologies taken by researchers around there. Investigations of AI and mechanical innovation based on their speculation and assessment on builds of computerization, apply self-rule and machine learning. In this array of composing, the use of robotization, human-made intellectual prowess, and AI developments can be used both as free and as destitute elements. While AI, mechanical autonomy, and motorization are related thoughts, it is fundamental to think about the separation between all of these developments. In this investigation, there is additionally creating writing in monetary issues, methods, and information systems that surveys the use of AI estimations in unique. A touch of the creator in this forming utilize truncated, little extension level information to attract experiences concerning how AI impacts firms or people contingent on their aptitudes part of this work examines whether and how the use of AI and AI mechanical assemblies affects solitary inclinations. Further in the exploration, progressively express to the board analysts, we need a point by point understanding about how AI and mechanical self-governance impact work. It fuses not precisely how AI and mechanized innovation change a given sort of work or occupation, yet also how modernized thinking and apply independence impact how individuals associate in the workplace. That is, we theorize that these headways will change the kind of work that we do, and how that work is arranged and made as a massive part of an increasingly conspicuous creation structure. We examine the ramifications of artificial intelligence, robotics, and computerization for the hierarchical plan and firm method, contend for more outstanding commitment with these points by authoritative and technique specialists, and diagram bearings for future research.

Trust in Management Information Systems (MIS)

2020 ◽  
Vol 64 (1) ◽  
pp. 6-16 ◽  
Author(s):  
Sarah M. Meeßen ◽  
Meinald T. Thielsch ◽  
Guido Hertel
Keyword(s):  
Information Systems ◽  
Information Overload ◽  
Management Information Systems ◽  
Empirical Work ◽  
Future Research ◽  
Management Information ◽  
Trust In Management ◽  
Actual Use ◽  
Trust In Technology ◽  
The Internet Of Things

Abstract. Digitalization, enhanced storage capacities, and the Internet of Things increase the volume of data in modern organizations. To process and make use of these data and to avoid information overload, management information systems (MIS) are introduced that collect, process, and analyze relevant data. However, a precondition for the application of MIS is that users trust them. Extending accounts of trust in automation and trust in technology, we introduce a new model of trust in MIS that addresses the conceptual ambiguities of existing conceptualizations of trust and integrates initial empirical work in this field. In doing so, we differentiate between perceived trustworthiness of an MIS, experienced trust in an MIS, intentions to use an MIS, and actual use of an MIS. Moreover, we consider users’ perceived risks and contextual factors (e. g., autonomy at work) as moderators. The introduced model offers guidelines for future research and initial suggestions to foster trust-based MIS use.

Development and Construct Validation of the German Workplace Trust Survey (G-WTS)

2010 ◽  
Vol 26 (1) ◽  
pp. 3-10 ◽  
Author(s):  
Nale Lehmann-Willenbrock ◽  
Simone Kauffeld
Keyword(s):  
Convergent Validity ◽  
Affective Commitment ◽  
Discriminant Validity ◽  
Organizational Context ◽  
Organizational Trust ◽  
Three Dimensional ◽  
Future Research ◽  
Work Related ◽  
Reliable Assessment ◽  
Workplace Trust

In research on trust in the organizational context, there is some agreement evolving that trust should be measured with respect to various foci. The Workplace Trust Survey (WTS) by Ferres (2002) provides reliable assessment of coworker, supervisor, and organizational trust. By means of a functionally equivalent translation, we developed a German version of the questionnaire (G-WTS) comprising 21 items. A total of 427 employees were surveyed with the G-WTS and questionnaires concerning several work-related attitudes and behaviors and 92 of these completed the survey twice. The hypothesized three-dimensional conceptualization of organizational trust was confirmed by confirmatory factor analysis. The G-WTS showed good internal consistency and retest reliability values. Concerning convergent validity, all of the three G-WTS dimensions positively predicted job satisfaction. In terms of discriminant validity, Coworker Trust enhanced group cohesion; Supervisor Trust fostered innovative behavior, while Organizational Trust was associated with affective commitment. Theoretical and practical contributions as well as opportunities for future research with the G-WTS are discussed.

scholarly journals Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 1022
Author(s):  
Hoang T. Nguyen ◽  
Kate T. Q. Nguyen ◽  
Tu C. Le ◽  
Guomin Zhang
Keyword(s):  
Artificial Intelligence ◽  
Flame Retardancy ◽  
Material Science ◽  
Construction Materials ◽  
Engineering Problem ◽  
Future Research ◽  
Fire Performance ◽  
Structural Components ◽  
Comprehensive Overview ◽  
Fire Engineering

The evaluation and interpretation of the behavior of construction materials under fire conditions have been complicated. Over the last few years, artificial intelligence (AI) has emerged as a reliable method to tackle this engineering problem. This review summarizes existing studies that applied AI to predict the fire performance of different construction materials (e.g., concrete, steel, timber, and composites). The prediction of the flame retardancy of some structural components such as beams, columns, slabs, and connections by utilizing AI-based models is also discussed. The end of this review offers insights on the advantages, existing challenges, and recommendations for the development of AI techniques used to evaluate the fire performance of construction materials and their flame retardancy. This review offers a comprehensive overview to researchers in the fields of fire engineering and material science, and it encourages them to explore and consider the use of AI in future research projects.

scholarly journals Artificial intelligence in hospitals: providing a status quo of ethical considerations in academia to guide future research

AI & Society ◽  
2021 ◽  
Author(s):  
Milad Mirbabaie ◽  
Lennart Hofeditz ◽  
Nicholas R. J. Frick ◽  
Stefan Stieglitz
Keyword(s):  
Artificial Intelligence ◽  
Citation Network ◽  
Status Quo ◽  
Biomedical Ethics ◽  
Future Research ◽  
Ethical Considerations ◽  
Ethical Discourse ◽  
The Status ◽  
Clinical Environments ◽  
Research Questions

AbstractThe application of artificial intelligence (AI) in hospitals yields many advantages but also confronts healthcare with ethical questions and challenges. While various disciplines have conducted specific research on the ethical considerations of AI in hospitals, the literature still requires a holistic overview. By conducting a systematic discourse approach highlighted by expert interviews with healthcare specialists, we identified the status quo of interdisciplinary research in academia on ethical considerations and dimensions of AI in hospitals. We found 15 fundamental manuscripts by constructing a citation network for the ethical discourse, and we extracted actionable principles and their relationships. We provide an agenda to guide academia, framed under the principles of biomedical ethics. We provide an understanding of the current ethical discourse of AI in clinical environments, identify where further research is pressingly needed, and discuss additional research questions that should be addressed. We also guide practitioners to acknowledge AI-related benefits in hospitals and to understand the related ethical concerns.

In the Moment: Fostering Mindfulness and Reducing Stressors in the Healthcare Workplace

2021 ◽  
pp. 193758672098824
Author(s):  
Shabboo Valipoor ◽  
Sheila J. Bosch
Keyword(s):  
Design Research ◽  
Healthcare Professionals ◽  
Well Being ◽  
Job Dissatisfaction ◽  
Future Research ◽  
Design Strategies ◽  
Environmental Interventions ◽  
Work Related ◽  
Healthcare Settings ◽  
The Moment

While healthcare design research has primarily focused on patient outcomes, there is a growing recognition that environmental interventions could do more by promoting the overall quality of care, and this requires expanding the focus to the health and well-being of those who deliver care to patients. Healthcare professionals are under high levels of stress, leading to burnout, job dissatisfaction, and poor patient care. Among other tools, mindfulness is recommended as a way of decreasing stress and helping workers function at higher levels. This article aims to identify potential environmental strategies for reducing work-related stressors and facilitating mindfulness in healthcare settings. By examining existing evidence on workplace mindfulness and stress-reducing design strategies, we highlight the power of the physical environment in not only alleviating stressful conditions but intentionally encouraging a mindful perspective. Strategies like minimizing distractions or avoiding overstimulation in the healthcare environment can be more effective if implemented along with the provision of designated spaces for mindfulness-based programs. Future research may explore optimal methods and hospital workers’ preferences for environments that support mindfulness and stress management. The long-term goal of all these efforts is to enhance healthcare professionals’ well-being, reignite their professional enthusiasm, and help them be resilient in times of stress.

scholarly journals Artificial Intelligence, 3D Documentation, and Rock Art—Approaching and Reflecting on the Automation of Identification and Classification of Rock Art Images

2021 ◽  
Author(s):  
Christian Horn ◽  
Oscar Ivarsson ◽  
Cecilia Lindhé ◽  
Rich Potter ◽  
Ashely Green ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Bronze Age ◽  
Data Augmentation ◽  
Rock Art ◽  
Training Data ◽  
Future Research ◽  
Rock Surface ◽  
Southern Scandinavia ◽  
Bounding Boxes

AbstractRock art carvings, which are best described as petroglyphs, were produced by removing parts of the rock surface to create a negative relief. This tradition was particularly strong during the Nordic Bronze Age (1700–550 BC) in southern Scandinavia with over 20,000 boats and thousands of humans, animals, wagons, etc. This vivid and highly engaging material provides quantitative data of high potential to understand Bronze Age social structures and ideologies. The ability to provide the technically best possible documentation and to automate identification and classification of images would help to take full advantage of the research potential of petroglyphs in southern Scandinavia and elsewhere. We, therefore, attempted to train a model that locates and classifies image objects using faster region-based convolutional neural network (Faster-RCNN) based on data produced by a novel method to improve visualizing the content of 3D documentations. A newly created layer of 3D rock art documentation provides the best data currently available and has reduced inscribed bias compared to older methods. Several models were trained based on input images annotated with bounding boxes produced with different parameters to find the best solution. The data included 4305 individual images in 408 scans of rock art sites. To enhance the models and enrich the training data, we used data augmentation and transfer learning. The successful models perform exceptionally well on boats and circles, as well as with human figures and wheels. This work was an interdisciplinary undertaking which led to important reflections about archaeology, digital humanities, and artificial intelligence. The reflections and the success represented by the trained models open novel avenues for future research on rock art.

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