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 Work Engagement – A Systematic Review of Polish Research

2017 ◽  
Vol 48 (2) ◽  
pp. 175-187
Author(s):  
Anita Pollak ◽  
Małgorzata Chrupała-Pniak ◽  
Patrycja Rudnicka ◽  
Mateusz Paliga
Keyword(s):  
Systematic Review ◽  
Work Engagement ◽  
Meta Analysis ◽  
Organizational Psychology ◽  
Measurement Methods ◽  
The Past ◽  
Current State ◽  
State Of Research ◽  
Meta Analyses ◽  
Positive Work

Abstract Over the past decade work engagement has gained both business and academia attention. With growing number of studies and meta-analyses the concept of work engagement is one of the pillars of positive work and organizational psychology. This systematic review presents the current state of research on work engagement in Poland. Results confirmed that work-engagement studies have not yet reached the threshold to conduct meta-analysis. The review of measurement methods and synthesis of findings allows to identify strengths and gaps in Polish studies. Discussion of limitations and biases in current research is accompanied with urge to overcome them and develop thriving stream of research on work engagement.

Artificial Intelligence-a Paradigm shift in Health Care Management

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Artificial Intelligence ◽  
Technological Development ◽  
Medical Procedures ◽  
Surgical Robots ◽  
New Developments ◽  
Current State ◽  
Emerging Trends ◽  
Robot Systems ◽  
Operative Planning ◽  
Applications Of Ai

Artificial Intelligence (AI) is gradually changing the practice of surgery with the advanced technological development of imaging, navigation, and robotic intervention. In this article, the recent successful and influential applications of AI in surgery are reviewed from pre-operative planning and intra-operative guidance to the integration of surgical robots. It ends with summarizing the current state, emerging trends, and major challenges in the future development of AI in surgery. Robotic surgery is the use of computer technologies working in conjunction with robot systems to perform medical procedures. The technology is also known as computer-aided surgery and robot-assisted surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new developments in the field of Neuro Surgery.

scholarly journals Predicted Influences of Artificial Intelligence on the Domains of Nursing: Scoping Review (Preprint)

2020 ◽  
Author(s):  
Christine Buchanan ◽  
M Lyndsay Howitt ◽  
Rita Wilson ◽  
Richard G Booth ◽  
Tracie Risling ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health System ◽  
Scoping Review ◽  
Predictive Analytics ◽  
Digital Health ◽  
Shared Responsibility ◽  
Compassionate Care ◽  
Health Technologies ◽  
Emerging Trends ◽  
Research Questions

BACKGROUND Artificial intelligence (AI) is set to transform the health system, yet little research to date has explored its influence on nurses—the largest group of health professionals. Furthermore, there has been little discussion on how AI will influence the experience of person-centered compassionate care for patients, families, and caregivers. OBJECTIVE This review aims to summarize the extant literature on the emerging trends in health technologies powered by AI and their implications on the following domains of nursing: administration, clinical practice, policy, and research. This review summarizes the findings from 3 research questions, examining how these emerging trends might influence the roles and functions of nurses and compassionate nursing care over the next 10 years and beyond. METHODS Using an established scoping review methodology, MEDLINE, CINAHL, EMBASE, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central, Education Resources Information Center, Scopus, Web of Science, and ProQuest databases were searched. In addition to the electronic database searches, a targeted website search was performed to access relevant gray literature. Abstracts and full-text studies were independently screened by 2 reviewers using prespecified inclusion and exclusion criteria. Included articles focused on nursing and digital health technologies that incorporate AI. Data were charted using structured forms and narratively summarized. RESULTS A total of 131 articles were retrieved from the scoping review for the 3 research questions that were the focus of this manuscript (118 from database sources and 13 from targeted websites). Emerging AI technologies discussed in the review included predictive analytics, smart homes, virtual health care assistants, and robots. The results indicated that AI has already begun to influence nursing roles, workflows, and the nurse-patient relationship. In general, robots are not viewed as replacements for nurses. There is a consensus that health technologies powered by AI may have the potential to enhance nursing practice. Consequently, nurses must proactively define how person-centered compassionate care will be preserved in the age of AI. CONCLUSIONS Nurses have a shared responsibility to influence decisions related to the integration of AI into the health system and to ensure that this change is introduced in a way that is ethical and aligns with core nursing values such as compassionate care. Furthermore, nurses must advocate for patient and nursing involvement in all aspects of the design, implementation, and evaluation of these technologies. INTERNATIONAL REGISTERED REPORT RR2-10.2196/17490

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.

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.

The Why and How of the Integrative Review

2020 ◽  
pp. 109442812093550 ◽  
Author(s):  
Matthew A. Cronin ◽  
Elizabeth George
Keyword(s):  
Knowledge Synthesis ◽  
Integrative Review ◽  
Future Research ◽  
Research Directions ◽  
Current State ◽  
Fair Representation ◽  
Organization Science ◽  
Future Research Directions ◽  
State Of Research ◽  
Meta Analyses

An effective integrative review can provide important insight into the current state of research on a topic and can recommend future research directions. This article discusses different types of reviews and outlines an approach to writing an integrative review. It includes guidance regarding challenges encountered when composing integrative reviews, such as fair representation of different perspectives and synthesizing that knowledge to yield new insights. An integrative review is of unique value among other types of knowledge-synthesis vehicles, such as narrative or systematic reviews and meta-analyses. Because each has distinctive but important approaches to synthesizing empirical knowledge, our protocol for writing integrative reviews is designed to complement these other knowledge-synthesis vehicles to best advance organization science.

Unsettled Issues in Vehicle Autonomy, Artificial Intelligence, and Human-Machine Interaction

2021 ◽  
Author(s):  
Chen Fang ◽  
Keyword(s):  
Artificial Intelligence ◽  
Interface Design ◽  
Autonomous Vehicles ◽  
Emotion Detection ◽  
Human Machine Interaction ◽  
Daily Lives ◽  
Current State ◽  
Speech Interaction ◽  
State Of Research ◽  
Machine Interaction

Artificial intelligence (AI)-based solutions are slowly making their way into our daily lives, integrating with our processes to enhance our lifestyles. This is major a technological component regarding the development of autonomous vehicles (AVs). However, as of today, no existing, consumer ready AV design has reached SAE Level 5 automation or fully integrates with the driver. Unsettled Issues in Vehicle Autonomy, AI and Human-Machine Interaction discusses vital issues related to AV interface design, diving into speech interaction, emotion detection and regulation, and driver trust. For each of these aspects, the report presents the current state of research and development, challenges, and solutions worth exploring.

scholarly journals Predicted Influences of Artificial Intelligence on the Domains of Nursing: Scoping Review

JMIR Nursing ◽  
10.2196/23939 ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. e23939
Author(s):  
Christine Buchanan ◽  
M Lyndsay Howitt ◽  
Rita Wilson ◽  
Richard G Booth ◽  
Tracie Risling ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health System ◽  
Scoping Review ◽  
Predictive Analytics ◽  
Digital Health ◽  
Shared Responsibility ◽  
Compassionate Care ◽  
Health Technologies ◽  
Emerging Trends ◽  
Research Questions

Background Artificial intelligence (AI) is set to transform the health system, yet little research to date has explored its influence on nurses—the largest group of health professionals. Furthermore, there has been little discussion on how AI will influence the experience of person-centered compassionate care for patients, families, and caregivers. Objective This review aims to summarize the extant literature on the emerging trends in health technologies powered by AI and their implications on the following domains of nursing: administration, clinical practice, policy, and research. This review summarizes the findings from 3 research questions, examining how these emerging trends might influence the roles and functions of nurses and compassionate nursing care over the next 10 years and beyond. Methods Using an established scoping review methodology, MEDLINE, CINAHL, EMBASE, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central, Education Resources Information Center, Scopus, Web of Science, and ProQuest databases were searched. In addition to the electronic database searches, a targeted website search was performed to access relevant gray literature. Abstracts and full-text studies were independently screened by 2 reviewers using prespecified inclusion and exclusion criteria. Included articles focused on nursing and digital health technologies that incorporate AI. Data were charted using structured forms and narratively summarized. Results A total of 131 articles were retrieved from the scoping review for the 3 research questions that were the focus of this manuscript (118 from database sources and 13 from targeted websites). Emerging AI technologies discussed in the review included predictive analytics, smart homes, virtual health care assistants, and robots. The results indicated that AI has already begun to influence nursing roles, workflows, and the nurse-patient relationship. In general, robots are not viewed as replacements for nurses. There is a consensus that health technologies powered by AI may have the potential to enhance nursing practice. Consequently, nurses must proactively define how person-centered compassionate care will be preserved in the age of AI. Conclusions Nurses have a shared responsibility to influence decisions related to the integration of AI into the health system and to ensure that this change is introduced in a way that is ethical and aligns with core nursing values such as compassionate care. Furthermore, nurses must advocate for patient and nursing involvement in all aspects of the design, implementation, and evaluation of these technologies. International Registered Report Identifier (IRRID) RR2-10.2196/17490

Culturally Responsive Pedagogy in Mathematics

2020 ◽  
Vol 2 ◽  
pp. 145-158
Author(s):  
Kenta Nagasawa
Keyword(s):  
Professional Development ◽  
Teacher Education ◽  
Culturally Responsive ◽  
Latino Students ◽  
Culturally Responsive Pedagogy ◽  
Mathematics Teacher Education ◽  
Development Program ◽  
Current State ◽  
Responsive Pedagogy ◽  
State Of Research

Purpose: This paper is a thematic literature review to examine the current state of research about Culturally Responsive Pedagogy in mathematics. The main themes are students’ perception, teacher education for pre-service teacher and professional development for teachers. Research methods/ approach: Literature was collected from Eric, which is a research engine of the education field. Also, Google Scholar is used to find articles of major scholars introduced by Dr. Rich Milner, who is the instructor of this course. Findings: Students faced microaggressions in mathematics class, which discouraged them to learn mathematics. The effect of teacher education was inconsistent in terms of the awareness of culturally responsive pedagogy and lesson plans. Research of professional development mentioned that mathematics was cultural. Implications for research and practice: It is more interesting to conduct long term or follow-up research to find the teacher’s practice after a taking professional development program. Also, it is critical to expand research scope besides African American and Latino students. Finally, evidence-based research is needed to change the political situation. Keywords: culturally responsive teaching, mathematics, teacher education, professional development, student’s perception

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