scholarly journals Artificial intelligence in human factors and ergonomics: an overview of the current state of research

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Deborah Petrat
Keyword(s):  
Artificial Intelligence ◽  
Human Factors ◽  
Work Processes ◽  
Research Gaps ◽  
Corporate Education ◽  
Current State ◽  
Human Factors And Ergonomics ◽  
Literature Reviews ◽  
State Of Research ◽  
Efficient Work

AbstractThe development of artificial intelligence (AI) technologies continues to advance. To fully exploit the potential, it is important to deal with the topics of human factors and ergonomics, so that a smooth implementation of AI applications can be realized. In order to map the current state of research in this area, three systematic literature reviews with different focuses were conducted. The seven observation levels of work processes according to Luczak and Volpert (1987) served as a basis. Overall n = 237 sources were found and analyzed. It can be seen that the research critically deals with human-centered, effective as well as efficient work in relation to AI. Research gaps, for example in the areas of corporate education concepts and participation and voice, identify further needs in research. The author postulates not to miss the transition between forecasts and verifiable facts.

Human Factors Considerations for Teaming between Construction Workersand Voice-based Intelligent Virtual Agent (VIVA)

2021 ◽  
Vol 65 (1) ◽  
pp. 72-76
Author(s):  
Maryam Rahimi Movassagh ◽  
Nazila Roofigari-Esfahan ◽  
Sang Won Lee ◽  
Carlos Evia ◽  
David Hicks ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Human Factors ◽  
Research Agenda ◽  
Task Environment ◽  
Virtual Agent ◽  
Work Processes ◽  
Construction Sites

Construction sites experience low productivity due to particular characteristics such as unique designs in each project, sporadic arrival of projects, and complexity of the process. Another contributing factor to low productivity is poor communication among workers, supervisors, and a site’s centralized knowledge hub. Research shows that introducing advanced artificial intelligence (AI) technology in construction can tackle these problems. In this paper, we analyzed human factors considerations–user, task, environment, and technology and identified their characteristics and challenges to design an interactive AI system to facilitate communication between workers and other stakeholders. Based on the analysis, we propose a voice-based intelligent virtual agent (VIVA) as a multi-purpose AI system on construction sites with a further research agenda. We hope that this effort can guide the design of construction-specific AI systems and that this worker-AI teaming can improve overall work processes, enhance productivity, and promote safety in construction.

scholarly journals Corporate entrepreneurship: a systematic literature review and future research agenda

2022 ◽  
Author(s):  
David Urbano ◽  
Andreu Turro ◽  
Mike Wright ◽  
Shaker Zahra
Keyword(s):  
Research Agenda ◽  
State Of The Art ◽  
Corporate Entrepreneurship ◽  
Global Perspective ◽  
Future Research ◽  
Future Research Agenda ◽  
Current State ◽  
Literature Reviews ◽  
Antecedents And Consequences ◽  
State Of Research

AbstractThis article analyzes the state of the art of the research on corporate entrepreneurship, develops a conceptual framework that connects its antecedents and consequences, and offers an agenda for future research. We review 310 papers published in entrepreneurship and management journals, providing an assessment of the current state of research and, subsequently, we suggest research avenues in three different areas: corporate entrepreneurship antecedents, dimensions and consequences. Even though a significant part of the overall corporate entrepreneurship literature has appeared in the last decade, most literature reviews were published earlier. These reviews typically cover a single dimension of the corporate entrepreneurship phenomenon and, therefore, do not provide a global perspective on the existing literature. In addition, corporate entrepreneurship has been studied from different fields and there are different approaches and definitions to it. This limits our understanding of accumulated knowledge in this area and hampers the development of further research. Our review addresses these shortcomings, providing a roadmap for future research.

scholarly journals A Review of Literature on Human Behaviour and Artificial Intelligence: Contributions Towards Knowledge Management

2021 ◽  
Vol 19 (2) ◽  
pp. pp165-179
Author(s):  
Elizabeth Real de Oliveira ◽  
Pedro Rodrigues
Keyword(s):  
Artificial Intelligence ◽  
Predictive Analytics ◽  
Human Behaviour ◽  
Academic Journal ◽  
Organizational Behaviour ◽  
Current State ◽  
Emerging Trends ◽  
R Programming ◽  
State Of Research ◽  
Meta Analyses

The main purpose of this research paper is to understand how artificial intelligence and machine learning applied to human behaviour has been treated, both theoretically and empirically, over the last twenty years, regarding predictive analytics and human organizational behaviour analysis. To achieve this goal, the authors performed a systematic literature review, as proposed by Tranfield, Denyer and Smart (2003), on selected databases and followed the PRISMA framework (Preferred Reporting Items for Systematic reviews and Meta-Analyses). The method is particularly suited for assessing emerging trends within multiple disciplines and therefore deemed the most suitable method for the purposes of this paper, which intends to survey and select papers according to their contribute towards theory building. By mapping what is known, this review will lay the groundwork, providing a timely insight into the current state of research on human organisational behaviour and its applications. A total of 17795 papers resulted from the application of the search equations. The papers’ abstracts were screened according to the inclusion / exclusion criterions which resulted in 199 papers for analysis. The authors have analysed the papers through VOSviewer software and R programming statistical computing software. This review showed that 60% of the research undertaken in the field has been done in the last three and a half years and there is no prominent author or academic journal, showing the emergence and the novelty of this research. The other key finds of the research relate to the evolution of the concept, from data-driven (hard) towards emotions-driven (soft) organisations.

scholarly journals Overview of current state of research on the application of artificial intelligence techniques for COVID-19

2021 ◽  
Vol 7 ◽  
pp. e564
Author(s):  
Vijay Kumar ◽  
Dilbag Singh ◽  
Manjit Kaur ◽  
Robertas Damaševičius
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Drug Interaction ◽  
Future Research ◽  
Rapid Testing ◽  
Learning Models ◽  
Open Area ◽  
Current State ◽  
State Of Research ◽  
Novel Drug

Background Until now, there are still a limited number of resources available to predict and diagnose COVID-19 disease. The design of novel drug-drug interaction for COVID-19 patients is an open area of research. Also, the development of the COVID-19 rapid testing kits is still a challenging task. Methodology This review focuses on two prime challenges caused by urgent needs to effectively address the challenges of the COVID-19 pandemic, i.e., the development of COVID-19 classification tools and drug discovery models for COVID-19 infected patients with the help of artificial intelligence (AI) based techniques such as machine learning and deep learning models. Results In this paper, various AI-based techniques are studied and evaluated by the means of applying these techniques for the prediction and diagnosis of COVID-19 disease. This study provides recommendations for future research and facilitates knowledge collection and formation on the application of the AI techniques for dealing with the COVID-19 epidemic and its consequences. Conclusions The AI techniques can be an effective tool to tackle the epidemic caused by COVID-19. These may be utilized in four main fields such as prediction, diagnosis, drug design, and analyzing social implications for COVID-19 infected patients.

Ethics Education of Human Factors Engineers for Responsible AI Development

2021 ◽  
Vol 65 (1) ◽  
pp. 1034-1038
Author(s):  
Esa M. Rantanen ◽  
John D. Lee ◽  
Katherine Darveau ◽  
Dave B. Miller ◽  
James Intriligator ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Human Factors ◽  
Data Science ◽  
Ethics Education ◽  
Panel Discussion ◽  
Technical Skills ◽  
The Past ◽  
Human Factors And Ergonomics ◽  
Educational Challenges ◽  
Societal Impacts

This panel discussion is third in a series examining the educational challenges facing future human factors and ergonomics professionals. The past two panels have focused on training of technical skills in data science, machine learning, and artificial intelligence to human factors students. This panel discussion expands on these topics and argues for a need of new and broader training curricula that include ethics for responsible development of AI-based systems that will touch lives of everybody and have widespread societal impacts.

scholarly journals Human factors: bridging artificial intelligence and patient safety

2020 ◽  
Vol 9 (1) ◽  
pp. 211-215
Author(s):  
Avishek Choudhury ◽  
Onur Asan
Keyword(s):  
Artificial Intelligence ◽  
Patient Safety ◽  
Human Factors ◽  
Human Performance ◽  
Complex Nature ◽  
Clinical Workflow ◽  
Human Factors And Ergonomics ◽  
Interacting Components

The recent launch of complex artificial intelligence (AI) in the domain of healthcare has embedded perplexities within patients, clinicians, and policymakers. The opaque and complex nature of artificial intelligence makes it challenging for clinicians to interpret its outcome. Incorrect interpretation and poor utilization of AI might hamper patient safety. The principles of human factors and ergonomics (HFE) can assist in simplifying AI design and consecutively optimize human performance ensuring better understanding of AI outcome, their interaction with the clinical workflow. In this paper, we discuss the interactions of providers with AI and how HFE can influence these interacting components to patient safety.

scholarly journals A review of the current state of research on China’s international image management

2019 ◽  
Vol 4 (1) ◽  
pp. 68-81
Author(s):  
Falk Hartig
Keyword(s):  
Knowledge Production ◽  
Mixed Methods Research ◽  
Management Practices ◽  
Image Management ◽  
Research Gaps ◽  
Communicative Practices ◽  
Current State ◽  
International Image ◽  
State Of Research ◽  
The Impact

Image Management is a crucial aspect of China’s engagement with the world, and the related scholarship has already produced high-quality learned analyses. This article, however, identifies a certain stagnation in knowledge production. This stagnation, I argue, is first due to a tendency to focus research on a few recurring themes and second due to three contested areas and related research gaps. These contestations concern (1) the question how to describe and conceptualize image management practices, (2) the question what instruments belong to image management practices, and (3) most importantly the question of audiences and how to measure the impact of these practices. By mapping out these areas, this article provides avenues for further research and argues in favor of interdisciplinary mixed-methods research in this field. Taking those contested areas and the existing research gaps more seriously into consideration is imperative to understand China’s communicative practices which increasingly become a major component of China’s overall behavior on the global stage.

scholarly journals Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review (Preprint)

2021 ◽  
Author(s):  
Onur Asan ◽  
Avishek Choudhury
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Human Factors ◽  
Ecological Validity ◽  
Human Cognition ◽  
User Centered Design ◽  
Sociotechnical System ◽  
Human Factors And Ergonomics ◽  
Mapping Review ◽  
User Centered

BACKGROUND Despite advancements in artificial intelligence (AI) to develop prediction and classification models, little research has been devoted to real-world translations with a user-centered design approach. AI development studies in the health care context have often ignored two critical factors of ecological validity and human cognition, creating challenges at the interface with clinicians and the clinical environment. OBJECTIVE The aim of this literature review was to investigate the contributions made by major human factors communities in health care AI applications. This review also discusses emerging research gaps, and provides future research directions to facilitate a safer and user-centered integration of AI into the clinical workflow. METHODS We performed an extensive mapping review to capture all relevant articles published within the last 10 years in the major human factors journals and conference proceedings listed in the “Human Factors and Ergonomics” category of the Scopus Master List. In each published volume, we searched for studies reporting qualitative or quantitative findings in the context of AI in health care. Studies are discussed based on the key principles such as evaluating workload, usability, trust in technology, perception, and user-centered design. RESULTS Forty-eight articles were included in the final review. Most of the studies emphasized user perception, the usability of AI-based devices or technologies, cognitive workload, and user’s trust in AI. The review revealed a nascent but growing body of literature focusing on augmenting health care AI; however, little effort has been made to ensure ecological validity with user-centered design approaches. Moreover, few studies (n=5 against clinical/baseline standards, n=5 against clinicians) compared their AI models against a standard measure. CONCLUSIONS Human factors researchers should actively be part of efforts in AI design and implementation, as well as dynamic assessments of AI systems’ effects on interaction, workflow, and patient outcomes. An AI system is part of a greater sociotechnical system. Investigators with human factors and ergonomics expertise are essential when defining the dynamic interaction of AI within each element, process, and result of the work system.

scholarly journals Dealing with deepfakes – an interdisciplinary examination of the state of research and implications for communication studies

2021 ◽  
Vol 10 (1) ◽  
pp. 72-96
Author(s):  
Alexander Godulla ◽  
Christian P. Hoffmann ◽  
Daniel Seibert
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
English Language ◽  
Communication Studies ◽  
Video Content ◽  
Research Gaps ◽  
Research Topics ◽  
User Perceptions ◽  
Naked Eye ◽  
State Of Research

Using artificial intelligence, it is becoming increasingly easy to create highly realistic but fake video content - so-called deepfakes. As a result, it is no longer possible always to distinguish real from mechanically created recordings with the naked eye. Despite the novelty of this phenomenon, regulators and industry players have started to address the risks associated with deepfakes. Yet research on deepfakes is still in its infancy. This paper presents findings from a systematic review of English-language deepfake research to identify salient discussions. We find that, to date, deepfake research is driven by computer science and law, with studies focusing on deepfake detection and regulation. While a number of studies address the potential of deepfakes for political disinformation, few have examined user perceptions of and reactions to deepfakes. Other notable research topics include challenges to journalistic practices and pornographic applications of deepfakes. We identify research gaps and derive implications for future communication studies research.

Metadata evaluation criteria in respect to archival maps description

2020 ◽  
Vol 38 (1) ◽  
pp. 1-27 ◽  
Author(s):  
Marta Kuźma ◽  
Albina Mościcka
Keyword(s):  
Digital Libraries ◽  
Full Text ◽  
Design Methodology ◽  
Evaluation Criteria ◽  
Research Gaps ◽  
Content Type ◽  
Current State ◽  
Metadata Quality ◽  
State Of Research ◽  
Practical Implications

Purposes This paper aims to present an objective summary of the current state of research concerning the evaluation criteria of map metadata. The undertaken research identifies which authors and to what extent the discussed issues related to the metadata of objects collected in digital libraries, with particular emphasis on cartographic materials. Design/methodology/approach Independent reviewers analysed the basic articles data. Selected papers were subject to quality assessment, based on the full text and 12 questions. Finally, iterative backward reference search was conducted. Findings The results demonstrate that there are no universal criteria for metadata evaluation. There are no works that would assess the metadata of cartographic studies, although numerous publications point to the need for this type of work. Practical implications Metadata evaluation allows users to obtain knowledge whether objects found in the library are relevant for their needs. Originality/value The criteria and methods most often used for assessing metadata quality which can be adopted to map metadata evaluation have been identified. The authors identified the existing research gaps and proved that there is a need for research contributions in the field of evaluating map metadata.

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