Did AI Kill My Job?

2021 ◽  
pp. 124-146
Author(s):  
Anabela Mesquita ◽  
Luciana Oliveira ◽  
Arminda Sa Sequeira
Keyword(s):  
Machine Learning ◽  
Human Resources ◽  
Business Growth ◽  
Comfort Zone ◽  
Job Market ◽  
Job Description ◽  
Growth Optimization ◽  
A Current

People and organizations have been witnessing tremendous changes taking place in the job market. Technologies (ex. AI, machine learning, IoT) are pushing individuals away from their comfort zone and forcing them to adapt, to develop new skills and to reinvent their job positions. Reports on the changes in the workplace and on the workforce have been raising concerns about the potential of AI to replace humans in job positions. The current challenges, brought by the 4th IR, have been providing countless opportunities for business growth, optimization and internationalization; however, tremendous concerns are currently raised regarding the sustainability of the human resources which are currently on the market and of those who are being trained to enter it. In this chapter, the authors focus on administrative job positions, which have been pointed out as one of the most prone to be taken over by AI and identify the already available technologies that can perform the job description tasks, as a current diagnose of the profession.

Feasibility study of automatically performing the concrete delivery dispatching through machine learning techniques

2015 ◽  
Vol 22 (5) ◽  
pp. 573-590 ◽  
Author(s):  
Mojtaba Maghrebi ◽  
Claude Sammut ◽  
S. Travis Waller
Keyword(s):  
Machine Learning ◽  
Human Resources ◽  
Design Methodology ◽  
Machine Learning Techniques ◽  
Mixing Process ◽  
Content Type ◽  
Practical Solution ◽  
Learning Techniques ◽  
Ready Mixed Concrete ◽  
Practical Implications

Purpose – The purpose of this paper is to study the implementation of machine learning (ML) techniques in order to automatically measure the feasibility of performing ready mixed concrete (RMC) dispatching jobs. Design/methodology/approach – Six ML techniques were selected and tested on data that was extracted from a developed simulation model and answered by a human expert. Findings – The results show that the performance of most of selected algorithms were the same and achieved an accuracy of around 80 per cent in terms of accuracy for the examined cases. Practical implications – This approach can be applied in practice to match experts’ decisions. Originality/value – In this paper the feasibility of handling complex concrete delivery problems by ML techniques is studied. Currently, most of the concrete mixing process is done by machines. However, RMC dispatching still relies on human resources to complete many tasks. In this paper the authors are addressing to reconstruct experts’ decisions as only practical solution.

scholarly journals ELIMINASI RISIKO OPERASIONAL BMT SRI SEJAHTERA SURABAYA

2020 ◽  
Vol 6 (7) ◽  
pp. 1317
Author(s):  
Yanuar Dharma Putra ◽  
Imron Mawardi
Keyword(s):  
Information Technology ◽  
Human Resources ◽  
Risk Mitigation ◽  
Computer Software ◽  
Mitigation Measures ◽  
Job Description ◽  
Information Risk ◽  
Software And Hardware ◽  
Moral Guidance

The results of this research are risk mitigation measures in the continuity of internal processes, human resources, technology and information. Risk mitigation on the internal processes is done by performing supervision based on employees job description, and implementation of sharia financing agreements with customers. Risk mitigation on human resources is done by providing moral guidance to employees. Risk mitigation in information technology is carried out by performing regular maintenance of computer software and hardware, as well as other devices that support Baitul Maal wa tamwil Sri Sejahtera business activities.

MANAJEMEN REKRUTMEN TENAGA PENDIDIK DI MTs DARUSSALAM MUARA TEMBESI

2021 ◽  
Vol 5 (1) ◽  
pp. 17-22
Author(s):  
Ririn Fadillah ◽  
Mahmud MY ◽  
Riftiyanti Savitri
Keyword(s):  
Data Collection ◽  
Human Resources ◽  
Qualitative Methods ◽  
Recruitment Process ◽  
Job Description ◽  
Academic Fields ◽  
Education Personnel ◽  
The Right ◽  
Job Specification

This research aims to describe the management of recruitment of educators in MTs Darussalam Muara Tembesi. This study uses qualitative methods. Data collection techniques using observations, interviews, and documentation. The results showed that the procurement of well-managed education personnel includes several activities, first, establishing the number of teachers needed. Second, the determination of quality and placement of teachers according to the needs based on job description and job specification. Third, determine the number of teachers received according to the needs of madrasah based on the right man in the right place and the right man in the right job. Fourth, establish teacher welfare and career development so that teachers are always motivated to improve their skills in academic and non-academic fields. A well-managed recruitment process can produce qualified human resources in MTs Darussalam Muara Tembesi.

The Effects of Gamification on Nurse Work Motivation

2022 ◽  
pp. 262-276
Author(s):  
Jaana-Maija Koivisto ◽  
Elina Haavisto ◽  
Antti J. Kaipia ◽  
Ira H. Saarinen ◽  
Jari Multisilta
Keyword(s):  
Human Resources ◽  
Intrinsic Motivation ◽  
Positive Feedback ◽  
Work Motivation ◽  
Hospital Setting ◽  
Surgical Ward ◽  
Key Factor ◽  
Quasi Experimental ◽  
Continuous Feedback ◽  
A Current

A current concern in the medical field is that nurses leave their careers due to low work motivation. Intrinsic motivation is a key factor that influences satisfaction in the workplace. This study aimed to develop a gamification intervention for implementation in a hospital setting and evaluate its effects on nurses' work motivation. It was hypothesized that nurses' work motivation would improve by the end of the intervention. The study was conducted in a surgical ward at a hospital in Finland. The design was descriptive and quasi-experimental. The study found that continuous feedback from gamification interventions influenced nurses' work motivation. The gamified group offered more positive feedback than the non-gamified group. These findings add to our understanding of the effects of gamification interventions on nurses' work motivation in hospital settings. However, more research is needed to demonstrate the potential of gamification to increase the retention of much-needed human resources.

Implementation of an Intelligent Model Based on Machine Learning in the Application of Macro-Ergonomic Methods in a Human Resources Process Based on ISO 12207

2022 ◽  
pp. 251-275
Author(s):  
Edgar Cossio Franco ◽  
Jorge Alberto Delgado Cazarez ◽  
Carlos Alberto Ochoa Ortiz Zezzatti
Keyword(s):  
Machine Learning ◽  
Human Resources ◽  
Decision Trees ◽  
Work Stress ◽  
Selection Process ◽  
Model Based ◽  
Java Language ◽  
Intelligent Model

The objective of this chapter is to implement an intelligent model based on machine learning in the application of macro-ergonomic methods in human resources processes based on the ISO 12207 standard. To achieve the objective, a method of constructing a Java language algorithm is applied to select the best prospect for a given position. Machine learning is done through decision trees and algorithm j48. Among the findings, it is shown that the model is useful in identifying the best profiles for a given position, optimizing the time in the selection process and human resources as well as the reduction of work stress.

Text mining for human resources competencies: Taiwan example

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chih-Hung Chung ◽  
Lu-Jia Chen
Keyword(s):  
Text Mining ◽  
Human Resources ◽  
Success Factors ◽  
Course Design ◽  
Data Sets ◽  
Job Market ◽  
Content Type ◽  
Entry Level ◽  
Critical Success ◽  
Job Advertisements

Purpose The purpose of this study is to explore the capabilities required by entry-level human resources (HR) professionals based on job advertisements by using text mining (TM) technique. Design/methodology/approach This study used TM techniques to explore the capabilities required by entry-level HR professionals based on job advertisements on HR agency 104’s website in Taiwan. Python was used to crawl the advertisements on the website, and 841 posts were collected. Next, the author used TM to explore and understand hidden trends and patterns in numerous data sets. Findings The results of this study revealed four critical success factors (specific skills, educational level, experience and specific capabilities), five clusters and ten classifications. Practical implications The results can aid HR curriculum developers and educators in customizing and improving HR education curricula, such that HR students can develop capabilities required to secure employment in the current HR job market. Originality/value Our results may facilitate the understanding of the current trends in the HR job market and provide useful suggestions to HR curriculum developers for improving training and professional course design, such that students’ competitiveness is enhanced and professional capabilities improved.

Job-Candidate Matching using ESCO Ontology

2019 ◽  
Vol 15 (1) ◽  
pp. 1-13
Author(s):  
Aman Shakya ◽  
Subhash Paudel
Keyword(s):  
Human Resources ◽  
Human Resources Management ◽  
Supply And Demand ◽  
Key Factors ◽  
Similarity Matching ◽  
Job Description ◽  
Web Based ◽  
Demand And Supply ◽  
Resources Management ◽  
Web Based System

 Skills management is one of the key factors to address the increasing competitiveness among different companies. Suitable knowledge representation and approach for matching skills and competences in job vacancies and candidate profiles can support human resources management automation through suitable matching and ranking services. This paper presents an approach for matchmaking between skills demand and supply through skill profiles enrichment and matching supply and demand profiles over multiple criteria. This work builds upon methods for profile modeling, information enrichment and multi-criteria matching. The main contribution of this work is a methodology for harmonization and enrichment of heterogeneous profile models and skill set description by making use of the standard ESCO ontology. Secondly, an algorithm is proposed for similarity matching across multi-criteria for discovering set of profiles that best fits the job description criteria. A prototype web-based system has been developed to implement the proposed approach and deployed online. The system has been tested with real IT jobs related dataset and validated against relevance scores provided by human experts. Experimental results show consistent correspondence between the similarity ranking scores produced by the system and scores provided by the human users.

scholarly journals Hiring Practices and the Occupational Health Nurse Manager

AAOHN Journal ◽  
1993 ◽  
Vol 41 (3) ◽  
pp. 149-151
Author(s):  
Joy E. Wachs
Keyword(s):  
Health Service ◽  
Nurse Manager ◽  
Job Description ◽  
Related Information ◽  
Hiring Process ◽  
New Employee ◽  
Successful Match ◽  
Experience Education ◽  
Occupational Health Nurse ◽  
A Current

In summary, the main purpose of the hiring process is to obtain job related information to match the most qualified applicant with the position. The process is designed to answer specific questions: Does the applicant have the experience, education, and skills necessary to successfully perform the job? Does the applicant share the values, mission, and goals of the health service? The nurse manager must develop and advertise a current job description, review applications, and interview with that job description in mind. An additional goal for the nurse manager is to create a process that is fair, objective, non-biased, and non-discriminatory, and that will result in a successful match between the new employee and the health service.

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