Artificial Intelligence in HRM

2022 ◽  
pp. 1-18
Author(s):  
Esra Sipahi ◽  
Erkin Artantaş
Keyword(s):  
Artificial Intelligence ◽  
Literature Review ◽  
Performance Measurement ◽  
Routine Activities ◽  
Career Management ◽  
Innovative Work ◽  
Management Approaches ◽  
Employee Experience ◽  
Research World ◽  
Recruitment Performance

Artificial intelligence's ability to enhance the applicant and employee involvement by automating routine, low-value responsibilities, and freeing up time to concentrate on the more planned, innovative work that teams need and want to do has been a burning topic in the research world for years. The technology may lead to improved recruitment, performance evaluations, training, and career management approaches. This literature review looks at artificial intelligence in HRM in terms of recruitment, performance measurement, training and coaching, and career management operations. It allows HR departments to enhance the applicant and employee experience by automating low-value, routine activities, allowing resources to concentrate on more strategic, disruptive work.

Perceived Effectiveness of Artificial Intelligence based Decision Support System in a Clinical Setting: A Systematic Literature Review (Preprint)

2020 ◽  
Author(s):  
Avishek Choudhury
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Decision Support ◽  
Literature Review ◽  
Decision Support System ◽  
Support System ◽  
Clinical Setting ◽  
Clinical Decision Making ◽  
Theoretical Perspective ◽  
Care Providers

UNSTRUCTURED Objective: The potential benefits of artificial intelligence based decision support system (AI-DSS) from a theoretical perspective are well documented and perceived by researchers but there is a lack of evidence showing its influence on routine clinical practice and how its perceived by care providers. Since the effectiveness of AI systems depends on data quality, implementation, and interpretation. The purpose of this literature review is to analyze the effectiveness of AI-DSS in clinical setting and understand its influence on clinician’s decision making outcome. Materials and Methods: This review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta- Analyses reporting guidelines. Literature will be identified using a multi-database search strategy developed in consultation with a librarian. The proposed screening process consists of a title and abstract scan, followed by a full-text review by two reviewers to determine the eligibility of articles. Studies outlining application of AI based decision support system in a clinical setting and its impact on clinician’s decision making, will be included. A tabular synthesis of the general study details will be provided, as well as a narrative synthesis of the extracted data, organised into themes. Studies solely reporting AI accuracy an but not implemented in a clinical setting to measure its influence on clinical decision making were excluded from further review. Results: We identified 8 eligible studies that implemented AI-DSS in a clinical setting to facilitate decisions concerning prostate cancer, post traumatic stress disorder, cardiac ailment, back pain, and others. Five (62.50%) out of 8 studies reported positive outcome of AI-DSS. Conclusion: The systematic review indicated that AI-enabled decision support systems, when implemented in a clinical setting and used by clinicians might not ensure enhanced decision making. However, there are very limited studies to confirm the claim that AI based decision support system can uplift clinicians decision making abilities.

scholarly journals Human-Centered Artificial Intelligence for Designing Accessible Cultural Heritage

2021 ◽  
Vol 11 (2) ◽  
pp. 870
Author(s):  
Galena Pisoni ◽  
Natalia Díaz-Rodríguez ◽  
Hannie Gijlers ◽  
Linda Tonolli
Keyword(s):  
Artificial Intelligence ◽  
Literature Review ◽  
Cultural Heritage ◽  
Conceptual Framework ◽  
Interaction Design ◽  
Participatory Design ◽  
Future Directions ◽  
Heritage Sites ◽  
Review Analysis

This paper reviews the literature concerning technology used for creating and delivering accessible museum and cultural heritage sites experiences. It highlights the importance of the delivery suited for everyone from different areas of expertise, namely interaction design, pedagogical and participatory design, and it presents how recent and future artificial intelligence (AI) developments can be used for this aim, i.e.,improving and widening online and in situ accessibility. From the literature review analysis, we articulate a conceptual framework that incorporates key elements that constitute museum and cultural heritage online experiences and how these elements are related to each other. Concrete opportunities for future directions empirical research for accessibility of cultural heritage contents are suggested and further discussed.

scholarly journals The Applications of Artificial Intelligence in Chest Imaging of COVID-19 Patients: A Literature Review

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1317
Author(s):  
Maria Elena Laino ◽  
Angela Ammirabile ◽  
Alessandro Posa ◽  
Pierandrea Cancian ◽  
Sherif Shalaby ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Literature Review ◽  
Diagnostic Imaging ◽  
Clinical Work ◽  
Rapid Expansion ◽  
Chest Imaging ◽  
Imaging Data ◽  
Prognostic Information ◽  
Quantitative Ct ◽  
Work Up

Diagnostic imaging is regarded as fundamental in the clinical work-up of patients with a suspected or confirmed COVID-19 infection. Recent progress has been made in diagnostic imaging with the integration of artificial intelligence (AI) and machine learning (ML) algorisms leading to an increase in the accuracy of exam interpretation and to the extraction of prognostic information useful in the decision-making process. Considering the ever expanding imaging data generated amid this pandemic, COVID-19 has catalyzed the rapid expansion in the application of AI to combat disease. In this context, many recent studies have explored the role of AI in each of the presumed applications for COVID-19 infection chest imaging, suggesting that implementing AI applications for chest imaging can be a great asset for fast and precise disease screening, identification and characterization. However, various biases should be overcome in the development of further ML-based algorithms to give them sufficient robustness and reproducibility for their integration into clinical practice. As a result, in this literature review, we will focus on the application of AI in chest imaging, in particular, deep learning, radiomics and advanced imaging as quantitative CT.

scholarly journals Applications of artificial intelligence to improve patient flow on mental health inpatient units - Narrative literature review

Heliyon ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. e06626
Author(s):  
Paulina Cecula ◽  
Jiakun Yu ◽  
Fatema Mustansir Dawoodbhoy ◽  
Jack Delaney ◽  
Joseph Tan ◽  
...  
Keyword(s):  
Mental Health ◽  
Artificial Intelligence ◽  
Literature Review ◽  
Patient Flow ◽  
Narrative Literature ◽  
Narrative Literature Review ◽  
Inpatient Units ◽  
Improve Patient

How and where is artificial intelligence in the public sector going? A literature review and research agenda

2019 ◽  
Vol 36 (4) ◽  
pp. 101392 ◽  
Author(s):  
Weslei Gomes de Sousa ◽  
Elis Regina Pereira de Melo ◽  
Paulo Henrique De Souza Bermejo ◽  
Rafael Araújo Sousa Farias ◽  
Adalmir Oliveira Gomes
Keyword(s):  
Artificial Intelligence ◽  
Public Sector ◽  
Literature Review ◽  
Research Agenda ◽  
The Public

Ambiguity in public sector performance measurement: a systematic literature review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chiara Oppi ◽  
Cristina Campanale ◽  
Lino Cinquini
Keyword(s):  
Public Sector ◽  
Literature Review ◽  
Performance Measurement ◽  
Systematic Literature Review ◽  
Field Research ◽  
Future Research ◽  
Academic Journal ◽  
Content Type ◽  
The Public ◽  
Study Results

PurposeThis paper presents a systematic literature review aiming at analysing how research has addressed performance measurement systems’ (PMSs) ambiguities in the public sector. This paper embraces the ambiguity perspective that PMSs in public sector coexist with and cope with existing ambiguities.Design/methodology/approachThe authors conducted a literature review in Scopus and ScienceDirect, considering articles published since 1985, and the authors selected articles published in the journals included in the Association of Business Schools' Academic Journal Guide (Chartered ABS, 2018). Of the 1,278 abstracts that matched the study’s search criteria, the authors selected 131 articles for full reading and 37 articles for the final discussion.FindingsThe study's key findings concern the elements of ambiguity in PMSs discussed in the literature. The study’s results suggest that ambiguity is still a relevant problem in performance measurement, as a problem that is impossible to be solved and therefore needs to be better understood by researchers and public managers. The analysis allows us to summarize the antecedents and consequences of ambiguity in the public sector.Research limitations/implicationsThe key findings of the study concern the main sources of ambiguity in PMSs discussed in the literature, their antecedents and their consequences. The study results suggest that ambiguity exists in performance measurement and that is an issue to be handled with various strategies that can be implemented by managers and employees.Practical implicationsManagers and researchers may benefit from this research as it may represent a guideline to understand ambiguities in their organizations or in field research. Researchers may also benefit from a summary list of the key issues that have been analysed in the empirical cases provided by this research. Social implicationsThis research may provide insights to limit ambiguity and thus contribute to improve performance measurement in the public sector.Originality/valueThis research presents a comprehensive review on the topic. It provides insight that suggests what future research should attend to in helping to interpret ambiguity, considering also what should be done to influence ambiguity.

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