The Future of eSports

2020 ◽  
pp. 149-164
Keyword(s):  
Artificial Intelligence ◽  
Virtual Reality ◽  
Data Privacy ◽  
Future Research ◽  
Business And Society ◽  
Regulatory Issues ◽  
The Future ◽  
Impossible Task ◽  
Research Questions

Predicting the future is a difficult and, arguably, impossible task. This final chapter builds on the past and present and explores macro-level trends and how they may impact the future of eSports. This includes issues related to data privacy, blockchain, artificial intelligence, virtual reality, 5G wireless, and major policy and regulatory issues that may challenge eSports. Together, these trends offer a framework to map out how eSports may impact both business and society. The final section of this chapter synthesizes the detailed research questions from each chapter to guide future research in the field of eSports.

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.

Virtual Reality Exposure Therapy for treating social anxiety in stuttering: A scoping review

2021 ◽  
Author(s):  
Ian Chard ◽  
Nejra van Zalk
Keyword(s):  
Virtual Reality ◽  
Social Anxiety ◽  
Public Speaking ◽  
Exposure Therapy ◽  
Treatment Success ◽  
Future Research ◽  
Effective Technique ◽  
Virtual Reality Exposure Therapy ◽  
Research Questions ◽  
Virtual Reality Exposure

Virtual Reality Exposure Therapy (VRET) has been shown to be an effective technique for reducing social anxiety. People who stutter are at greater risk of developing heightened social anxiety. Cognitive behavior therapy protocols have shown promise in reducing social anxiety in people who stutter, but no studies have investigated VRET targeting social anxiety associated with stuttering. The aim of the current review is to provide an overview of VRET techniques used to treat social anxiety and insights into how VRET might be adopted in the case of comorbid stuttering and social anxiety. Twelve studies were reviewed to understand key distinctions in VRET protocols used to treat social anxiety. Distinctions include exercises targeting public speaking vs. general social anxiety, computer-generated virtual environments vs. 360 video, and therapist guided vs. automated VRET. An overview of wider research questions surrounding VRET is then presented to aid the understanding of treatment success and outline important directions for future research. Based on the review findings, suggestions are made regarding VRET design for stuttering. In sum, VRET should be tailored to situations and cognitive-behavioral processes that underlie the experience of social anxiety amongst people who stutter, with automated VRET using a virtual therapist a potentially suitable format for delivering treatment.

Artificial intelligence in the digital twins: State of the art, challenges, and future research topics

Digital Twin ◽  
2021 ◽  
Vol 1 ◽  
pp. 12
Author(s):  
Zhihan Lv ◽  
Shuxuan Xie
Keyword(s):  
Artificial Intelligence ◽  
Smart City ◽  
Traffic Accidents ◽  
Intelligent Manufacturing ◽  
Unmanned Vehicles ◽  
Urban Traffic ◽  
Future Research ◽  
Test Accuracy ◽  
Digital Twins ◽  
The Future

Advanced computer technologies such as big data, Artificial Intelligence (AI), cloud computing, digital twins, and edge computing have been applied in various fields as digitalization has progressed. To study the status of the application of digital twins in the combination with AI, this paper classifies the applications and prospects of AI in digital twins by studying the research results of the current published literature. We discuss the application status of digital twins in the four areas of aerospace, intelligent manufacturing in production workshops, unmanned vehicles, and smart city transportation, and we review the current challenges and  topics that need to be looked forward to in the future. It was found that the integration of digital twins and AI has significant effects in aerospace flight detection simulation, failure warning, aircraft assembly, and even unmanned flight. In the virtual simulation test of automobile autonomous driving, it can save 80% of the time and cost, and the same road conditions reduce the parameter scale of the actual vehicle dynamics model and greatly improve the test accuracy. In the intelligent manufacturing of production workshops, the establishment of a virtual workplace environment can provide timely fault warning, extend the service life of the equipment, and ensure the overall workshop operational safety. In smart city traffic, the real road environment is simulated, and traffic accidents are restored, so that the traffic situation is clear and efficient, and urban traffic management can be carried out quickly and accurately. Finally, we looked forward to the future of digital twins and AI, hoping to provide a reference for future research in related fields.

The Future of Tax Research: From an Accounting Professor's Perspective

2007 ◽  
Vol 29 (2) ◽  
pp. 87-93 ◽  
Author(s):  
Terry Shevlin
Keyword(s):  
Tax Policy ◽  
Future Research ◽  
Policy Debate ◽  
Senior Faculty ◽  
Research Designs ◽  
The Future ◽  
Research Questions ◽  
Tax Research

I provide some suggestions for future research in the empirical accounting tax area. These suggestions repeat and build on the suggestions in Shackelford and Shevlin (2001). I also provide references to some research that I consider to be excellent examples of the points I wish to make. I think there are still many interesting questions to be examined, provided they are linked to some broad-based theory that connects results across a variety of research questions and research designs. I also think we (or some of the more senior faculty) might profitably consider entering into the tax policy debate by proffering normative statements based on our research.

scholarly journals AI and the Future of Learning: Expert Panel Report

2020 ◽  
Author(s):  
Jeremy Roschelle ◽  
James Lester ◽  
Judi Fusco
Keyword(s):  
Artificial Intelligence ◽  
Computational Intelligence ◽  
Expert Panel ◽  
Research Priorities ◽  
Future Research ◽  
Panel Report ◽  
Additional Resource ◽  
Design Concepts ◽  
Educational Challenges ◽  
The Future

This report is based on the discussion that emerged from a convening of a panel of 22 experts in artificial intelligence (AI) and in learning. It introduces three layers that can frame the meaning of AI for educators. First, AI can be seen as “computational intelligence” and capability can be brought to bear on educational challenges as an additional resource to an educator’s abilities and strengths. Second, AI brings specific, exciting new capabilities to computing, including sensing, recognizing patterns, representing knowledge, making and acting on plans, and supporting naturalistic interactions with people. Third, AI can be used as a toolkit to enable us to imagine, study, and discuss futures for learning that don’t exist today. Experts voiced the opinion that the most impactful uses of AI in education have not yet been invented. The report enumerates important strengths and weaknesses of AI, as well as the respective opportunities and barriers to applying AI to learning. Through discussions among experts about these layers, we observed new design concepts for using AI in learning. The panel also made seven recommendations for future research priorities.

scholarly journals Citation review of Human-Machine Collaboration in Virtual Reality for Adaptive Production Engineering by de Giorgio et al.

2020 ◽  
Author(s):  
Andrea de Giorgio ◽  
Mauro Onori
Keyword(s):  
Virtual Reality ◽  
Industry 4.0 ◽  
Scientific Work ◽  
Research Direction ◽  
Research Area ◽  
Future Research ◽  
The Future ◽  
New Research ◽  
The Impact ◽  
The Given

This article argues that despite a citation review is a rarely used research tool, this can be very useful to assess the impact of new research topics, both from the future research direction and the bibliometric perspectives. An explorative study is presented around the research area marked as Industry 4.0 with the conference paper mentioned in the title of this citation review. Even though the given reference paper is relatively recent, there are already twenty-seven citations listed among three different scholar databases. These are Google Scholar, ResearchGate and Semantic Scholar. In light of this, the article provides a bibliometric confirmation and analysis for the progression of the line of research adopted by de Giorgio et al. in the exploration of non-traditional methods using virtual reality technology and human-robot collaboration for adaptive applications in Industry 4.0. Furthermore, it represents a model for the authors’ self-development and an example of an unconventional approach to scientific work that may help improve related bibliometric research and scholar database strategies to index new articles and topics in the future.

scholarly journals Sociology on the Way to New Social Analytics: The Crisis in Sociology and the Problem of Artificial Intelligence

2021 ◽  
Vol 20 (3) ◽  
pp. 280-301
Author(s):  
Andrey Rezaev ◽  
Natalia Tregubova
Keyword(s):  
Social Sciences ◽  
Artificial Intelligence ◽  
21St Century ◽  
Technological Development ◽  
Contemporary Sociology ◽  
Social Analytics ◽  
The Future ◽  
Research Questions ◽  
The Way

At the turn of the 21st century, sociology as a science has become an object of criticism both from inside and outside the discipline. At the same time, the late-20th and early 21st centuries endorse an unprecedented splash of technological development, specifically the advancement of artificial intelligence technologies. The paper tries to show a relation between these two tendencies. For the authors, two questions are in the spotlight: (1) how have evaluations of the professional sociologists on what is happening to the discipline changed over the last 20 years? and (2) how could these evaluations be related to the research questions that the development of AI technologies brings to social sciences? In the first part of the paper, the authors examine and compare the participants' positions in the discussion about the future of sociology organized by the journal Contemporary Sociology in 2000. The second part of the paper examines two articles published in 2019 where it was proclaimed “the end of sociology.” The paper discusses why the debates about the crisis of sociology have shifted towards radical criticism during these years and how new arguments refine and supplement the previous discussions. In conclusion, the authors propose one way out of the crisis in sociology. They suggest the radical renewal of sociological science into a-typical and anti-disciplinary social analytics with the central orientation into “artificial sociality” inquiries.

The Impact of Digitalisation on Future Audits

2021 ◽  
Author(s):  
Lazarus Elad Fotoh ◽  
Johan Ingemar Lorentzon
Keyword(s):  
General Public ◽  
Research Agenda ◽  
Business Models ◽  
Empirical Studies ◽  
Digital Technologies ◽  
Future Research ◽  
Empirical Testing ◽  
The Future ◽  
Research Questions ◽  
The Impact

This study examines the future impact of digitalisation on auditing by synthesising empirical studies, relating them to surveys conducted by accounting bodies, and analysing these findings in relation to extant literature. Based on the synthesis, this study proposes a transitional framework to enable the audit profession to remain competitive. The results show that digitalisation may significantly affect the audit profession in the future. However, the impact is likely to be incremental rather than radical. To remain competitive, the audit profession needs to adopt new metrics, capabilities, skills and evolve its business models to incorporate digital technologies.  The contribution of this study is multi-faceted. The propositions and research agenda presented in this study will be beneficial to academics, practitioners, audit regulators, and the general public as they have the potential to form a foundation for addressing future research questions and for the theorisation and empirical testing of audit digitalisation.

What We Know and Don’t Know About Passion at Work

2019 ◽  
pp. 505-528
Author(s):  
Kim Cameron
Keyword(s):  
Levels Of Analysis ◽  
Causal Relationships ◽  
Important Research ◽  
Harmonious Passion ◽  
Obsessive Passion ◽  
The Future ◽  
Research Questions ◽  
Different Levels ◽  
Contextual Differences

This chapter addresses the question: What do we know, and what don’t we know about passion at work? One key objective of this final chapter is to provide a brief synopsis of the key findings reported by the various authors in this volume. The chapter summarizes the consensual definitions that have emerged regarding passion and its two major forms—obsessive passion and harmonious passion. It highlights factors that produce passion as well as those that result from passion. Especially, the differences associated with obsessive passion and harmonious passion are highlighted. Different predictors and different outcomes are associated with each form of passion. In addition, findings associated with individual, organizational, and macro levels of analysis are summarized. Different relationships with these two forms of passion are manifest across different levels of analysis. A second objective is to articulate some of what we do not yet know about passion. The chapter highlights some of the important research questions that can help guide research on passion in the future. This discussion includes issues regarding the development of passion, causal relationships between passion and certain outcomes, forms and manifestations of passion, and individual and contextual differences associated with passion.

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