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Exploring the dynamica virtus of Machine Learning (ML) in Human Resource Management - A Critical Analysis of IT industry

Malathi Sriram1 , L. Gandhi2

  1. Shri Dharmasthala Manjunatheshwara Institute for Management Development (SDMIMD), Mysore, India.
  2. Shri Dharmasthala Manjunatheshwara Institute for Management Development (SDMIMD), Mysore, India.

Correspondence should be addressed to: gandhi@sdmimd.ac.in.

Section:Review Paper, Product Type: Journal Paper
Volume-5 , Issue-12 , Page no. 173-180, Dec-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i12.173180

Online published on Dec 31, 2017

Copyright © Malathi Sriram, L. Gandhi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Malathi Sriram, L. Gandhi, “Exploring the dynamica virtus of Machine Learning (ML) in Human Resource Management - A Critical Analysis of IT industry,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.173-180, 2017.

MLA Style Citation: Malathi Sriram, L. Gandhi "Exploring the dynamica virtus of Machine Learning (ML) in Human Resource Management - A Critical Analysis of IT industry." International Journal of Computer Sciences and Engineering 5.12 (2017): 173-180.

APA Style Citation: Malathi Sriram, L. Gandhi, (2017). Exploring the dynamica virtus of Machine Learning (ML) in Human Resource Management - A Critical Analysis of IT industry. International Journal of Computer Sciences and Engineering, 5(12), 173-180.

BibTex Style Citation:
@article{Sriram_2017,
author = {Malathi Sriram, L. Gandhi},
title = {Exploring the dynamica virtus of Machine Learning (ML) in Human Resource Management - A Critical Analysis of IT industry},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2017},
volume = {5},
Issue = {12},
month = {12},
year = {2017},
issn = {2347-2693},
pages = {173-180},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1599},
doi = {https://doi.org/10.26438/ijcse/v5i12.173180}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i12.173180}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1599
TI - Exploring the dynamica virtus of Machine Learning (ML) in Human Resource Management - A Critical Analysis of IT industry
T2 - International Journal of Computer Sciences and Engineering
AU - Malathi Sriram, L. Gandhi
PY - 2017
DA - 2017/12/31
PB - IJCSE, Indore, INDIA
SP - 173-180
IS - 12
VL - 5
SN - 2347-2693
ER -

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Abstract

“A breakthrough in machine learning would be worth ten Microsofts”- -Bill Gates, Chairman, Microsoft The fact that humans have been progressing to reach a point where machine does most, if not all the mechanical labor is not new. What is new is the use of machines that is intelligent enough to replace humans in analyzing situations, portraying situations and scenarios, and then taking the (presumably) right decisions. This paper focuses on the use of machine learning that has replaced certain functions related to Human Resources Management, specifically in the IT industry. The paper is sectioned into five parts. In the first section the topic on hand is introduced, evolution of Machine Learning, introducing congruence of Machine Learning with HR functions such as Recruitment, Performance Management, Training & Development, Managing Attrition, Compensation Management etc. Section two, does a literature review that outlines the work previous written in this area i.e review of literature is done on this aspect. Section three takes a case study approach to highlight select IT companies that are using AI/ML for their HR functions. The fourth section attempts to design a simple Model from the literature review done. The fifth section presents the authors’ conclusion of the findings, and draws a futuristic picture.

Key-Words / Index Term

Machine Learning (ML), Replacing HR with ML, AI and HRM

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