THE USE OF ARTIFICIAL INTELLIGENCE IN HUMAN RESOURCES DEVELOPMENT

Electrical Engineering: An International Journal (EEIJ) Vol.8, No.1/2/3, September 2021
DOI: 10.5121/eeij.2021.8301 1
THE USE OF ARTIFICIAL INTELLIGENCE IN HUMAN
RESOURCES DEVELOPMENT
Yew Kee Wong
School of Information Engineering, HuangHuai University, Henan, China.
ABSTRACT
Artificial intelligence has been an eye-popping word that is impacting every industry in the world. With the
rise of such advanced technology, there will be always a question regarding its impact on our social life,
environment and economy thus impacting all efforts exerted towards continuous development. From the
definition, the welfare of human beings is the core of continuous development. Continuous development is
useful only when ordinary people’s lives are improved whether in health, education, employment,
environment, equality or justice. Securing decent jobs is a key enabler to promote the components of
continuous development, economic growth, social welfare and environmental sustainability. The human
resources are the precious resource for all nations. The high unemployment and underemployment rates
especially in youth is a great threat affecting the continuous economic development of many countries and
is influenced by investment in education, and quality of living.
KEYWORDS
Artificial Intelligence, Conceptual Blueprint, Continuous Development, Human Resources, Learning and
Employability
1. INTRODUCTION
Continuous development is defined as the development that meets the needs of the present
without compromising the ability of future generations to meet their own needs [1]. The primary
cause of the high unemployment rates is the inefficient education systems that fail to equip young
people with the required skills for the labour market. In this research, we propose the use of
artificial intelligence (AI) to enhance the relationship between education and employment.
Many studies were published on how to improve education curricula to enhance the
employability of students; frameworks were designed to facilitate the work of teachers, mentors,
career advisers and faculty to guide students through their career exploration and preparation.
Numerous papers were published on the impact of AI on education and its impact on
employment. However it seems there is a gap in connecting the three important areas of research,
1: education for employment, 2: AI in education and 3: AI in employment. Further investigations
are needed to evaluate and assess how AI can fit in the current learning and employability
blueprint and to evaluate what can innovation and entrepreneurship bring to promote better
education for employment systems.
2. USING AI TO BUILD A CONCEPTUAL BLUEPRINT
The study is assessing new blueprint for learning and employability and how AI can fit in and
foster the process, so further experiments should be carried out to ensure the effectiveness of the

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blueprint and the accuracy of results of the AI application on the learning and employability
process.
After reviewing literature regarding the impact of AI and its potential on both education and
employment, as well as reviewing different education for employment blueprints, theories and
case studies, this paper attempts to close the gap in the research related to specific scope which is
the impact of AI on education for employment. Young people can’t find jobs. Yet employers
can’t find people with the required skill set. This mismatch between the supply and demand in the
labour market might witness a bigger gap in the future with the growth of AI technologies.
There are a few frameworks for education for employment or in other words “Learning and
Employability”. However the existing model didn’t address the potential of AI whether in terms
of deployment of such technology within the model or in terms of the implications of AI on the
learning models or the employment models. So there is a need to find a practical frame for
learning and employability that incorporate the advancements of AI to facilitate the university to
work transition. This paper seeks to figure out the room for AI potentials through mapping
innovative startups that embraced AI capabilities to play a role in the education for employment
ecosystem.
2.1. The Use of AI in Education
AI may become a type of meta-science, like mathematics; it will be used as a tool to solve
problems in many scientific and technical domains. It was argued that video-connected AI
systems can be used in classrooms to monitor student emotions and attention in real time and use
such data with data from social media and Internet of things (IoT) platforms to help teachers and
students [2].
Another disruptive AI technology to traditional teaching is Teacherbots. Teacherbots are defined
as any machine-based software or hardware that assumes the role traditionally performed by a
teacher assistant in organizing information and providing fast answers to a wide set of predictable
questions; it can be facilitating, monitoring, assessing, and managing student learning within the
online learning space [3]. Bayne [4] explored how the association of teacher-student-code might
be pedagogically productive by using teacherbot and that teacher automation does not have to be
about rationalism as teacherbot was not intended to replace teachers or solve any productivity
issues.
One of the advancements that AI will bring in education is differentiation and individualization
of intelligent tutoring systems (ITS) which provides personalized electronic tutoring customized
to students’ learning styles and preferences. Through ITS, curriculum can be organized around
students' progress, combined with real-time feedback. The current educational systems
overwhelm teachers with administrative and mechanical tasks. A favourite benefit of using AI is
that educational institutions can streamline work processes such as grading of essays or
measuring student responses. Such workload can require valuable time from lecturers and
teachers and they would rather spend this time in 1:1 guidance with students or lesson planning
[5].
2.2. The Use of AI in Employment
Machines and automation have been replacing humans at work gradually ever since the Industrial
Revolution. It started in agriculture and handicrafts, then in mass manufacturing and currently in
many administrative tasks. But with the technology advancements, smart machines that are

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powered by AI and robotics, could potentially replace a larger proportion of existing human jobs
than before. It is observed that this replacement will on the other hand create new jobs as in the
past, but the concern is the percentage of jobs created will be relatively less than the replaced
ones [6]. Andrews [7] predicts that 40% of customer-servicing employees and government
workers will be assisted by virtual agents powered by AI to help them in decision- making or
process-related support.
Outsourcing companies that provide services such as call centres or manufacturing may suffer
since large corporates with advanced economies and technology, who outsource services to
emerging countries such as India due to cost, will be able to maximize their AI’s capabilities
hence they will no longer have the need to pay for outsourcing services as overhead costs will be
reduced and accordingly they might stop outsourcing of services and build in-house AI tools or
robots [8]. Workers who perform office and administrative support and others who work in the
transportation and logistics field as well as production labours are somewhat vulnerable or at risk.
With such employment concern, many studies refined such concern and the general consensus
now is that AI will generate major transformations in the labour market. According to many
researchers, AI will create 2.3 million jobs in 2020, while eliminating 1.8 million and by 2025 AI
related job creation will reach two million net-new jobs. Moreover, according to a new report
from the World Economic Forum (WEF); 75 million jobs are estimated to be displaced, while
133 million new roles may emerge due to machines and algorithms [9]. The study has argued that
this transition to technology should result in favourable unemployment that will allow human
labour to better perform activities they were never able to do in their current heavy duty jobs. AI
programs will probably be utilized for applications where hiring humans would be too expensive
or really dangerous.
AI programs will take over computer tasks allowing humans to dedicate their time to other kinds
of tasks including personal services. Service sector companies are optimistic about big data and
enthusiastic about AI and robotics deployment as it will have direct impact on productivity
improvement that eventually reflects on economic growth. On the other hand, it was realized that
AI can positively impact employment if it is utilized properly within the business model [10]. AI
uses in creating effective recruitment systems is seen as an inevitable opportunity to make best
use of. Still this will stay challenging until firms management pay attention to the importance of
allocating budgets to finance the required technology for hiring process.
3. LEARNING AND EMPLOYABILITY BLUEPRINT
Aside from the impact of AI in creating new jobs, replacing jobs or even shifting the job and
labour market, there are two global employment crises that already exist away from the
implications of AI; high levels of youth unemployment and a shortage of talents who possess
critical job skills. Mourshed, Farrell, & Barton [11] argued that if young people graduating from
schools and universities, after exerting lots of efforts, cannot secure decent jobs and observe that
sense of respect that comes with such degrees, society may witness outbreaks of anger or even
violence. There is an information gap in what works and what does not in preparing young people
during their school to employment transition. We summarized this information gap and it clearly
shows there is a clear disconnect and misperception about youth job readiness from the point of
view of employers vs youth vs educational institutions.

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Figure 1. Blueprint for exploring the education to employment system.
3.1. Institutions Registration
A. Information Sharing
All institutions are recommended to develop a comprehensive occupations database and
educational/training opportunities and provide information, advice and guidance to help job
seekers to make decisions on learning, training and work. The comprehensive occupation
database and website allows users to explore different career options including jobs profile,
salaries, industry trends and offer webchats with career advisors beside their skills health check
assessment that help users to find out what kind of jobs that best suits his/her skills. Users can
also find training opportunities.
B. Dealing with Social Perception
It seems that a perception is widespread that getting a decent job with good salary requires being
a college graduate. So this puts social pressure on youth to go to college and influence others'
choice away from the vocational tracks [12]. Brunello and Rocco [13] argued that youth who
graduated from vocational education have a higher likelihood of being not employed and with no
education or training within the past 12 months. They also found that vocational education is
associated with poorer labour market returns. This as a result impacted on the perception about
vocational education.
C. Dealing with Education Affordability
Schultz [14] and Becker [15] introduced individual choice model of human capital investment in
which they presented individual’s education choice as an investment decision. Individuals
sacrifice economically in order to acquire knowledge, referred to as ‘human capital’, that will
enable them to get better rewards in the future. If young people have no access to credit or
savings, this may limit their choices and they will not be able to enrol in study.
3.2. Learning Skills
A. Effective Content and Curriculum Design
Mourshed et al. [11] proposed that in order to design relevant curriculum to the employers’
requirements, close engagement between, industry leaders and educational providers is needed.
Such engagement to succeed, intensive collaboration should exist while defining the core

5
requirements on a very detailed level to ensure that the aspired learning outcomes will be
achieved.
B. Effective Delivery Methods
Effective delivery requires still close engagement between employers and educational providers.
Mourshed et al. [11] explored two main ways to do so - (1): Classrooms within workplaces. The
common model to bring vocational and technical training within the workplaces is through
internships or apprenticeships. (2): Workplaces within classrooms. Internships and
apprenticeships are types of hands-on learning experiences that are most admired by students,
however the number of opportunities are limited to accommodate certain capacities of students.
3.3. Recruitment
A. Assessment for Qualifications and Certifications
Finding a job is a painful process for job seekers. Job seekers strive to market their skills, but
can’t find a credible way to prove their talents, and Employers can’t trust the educational degree
as a main reference validating youth skills and knowledge. So both employers and candidates
suffer in the hiring and talent acquisition process. One of the well known processes to show one’s
credentials and prove his skills and knowledge in a credible way is the international professional
certifications such as PMP (Project Management Professional) or CPA (Certified Public
Accountant) which could be obtained by Individuals after passing standardized tests. Another
innovative solution for the assessment and credentials that crossed countries boundaries is the
digital badges which introduce much entertainment for online educational activities and
experiences.
B. Match Making
Based on their survey that covered more than 100 initiatives in 25 countries, Mourshed et al.
[11] observed that there are many cases that educational providers have built strong relationships
with employers so that they can hire their graduates immediately after graduation based on the
matchmaking and recommendation process that is being done by the educational providers
themselves. With current technological advancement, matchmaking could be a game changer in
the employment scene.
Flanagan [16] also agreed that Tinder-style matchmaking is beneficial in the job market as well
and shed the light on a similar app called “Emjoyment” which allow job seekers to swipe job
posts which includes major highlights about the company, location and only one sentence job
description and once the job seeker find a good post, he just hits “like”. On the other side,
employers start to see job seekers who liked their opportunity in a form of cards including
resumes main highlights and if the recruiter found an interesting profile, he also hits “like” and at
that moment both parties connect together at a push of a button. This kind of matchmaking
innovations could decrease the time lost in job applications and finding a good candidate and
create direct engagement between employers and job seekers.
4. ARTIFICIAL INTELLIGENCE SYSTEM
The conceptual blueprint using artificial intelligence system include several components which
can be integrated as one complete artificial intelligence system [17]. These are the standard
components [18]:-

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• Reasoning − It is the set of processes that empowers us to provide basis for judgement,
making decisions, and prediction.
• Learning − It is the activity of gaining information or skill by studying, practising, being
educated, or experiencing something. Learning improves the awareness of the subjects of
the study.
• Problem Solving − It is the procedure in which one perceives and tries to arrive at a desired
solution from a current situation by taking some path, which is obstructed by known or
unknown hurdles.
• Perception − It is the way of acquiring, interpreting, selecting, and organizing sensory
information.
• Linguistic Intelligence − It is one’s ability to use, comprehend, talk, and compose the
verbal and written language. It is significant in interpersonal communication.
The potential of online learning system include 4 factors of accessibility, flexibility, interactivity,
and collaboration of online learning afforded by the technology. In terms of the challenges to
online learning, 6 are identified: defining online learning; proposing a new legacy of
epistemology-social constructivism for all; quality assurance and standards; commitment versus
innovation; copyright and intellectual property; and personal learning in social constructivism.
Figure 2. The artificial intelligence online learning system components.
5. CONCLUSIONS
This research was proposed by understanding the inter-relation between education and
employment, what blueprints and systems that worked, and how AI can impact in the education
for employment process whether by introducing new innovations that foster students learning
process and placement in the job market or by harming the process and introducing unintentional
bias, privacy breach, escalating power consumption and replacing human in workplaces. This
paper is assessing new blueprints for learning and employability and how AI can fit in and foster
the process, so further studies and experiments should be carried out to ensure the effectiveness
of the blueprint and the accuracy of results of the AI application on the learning and
employability process.
REFERENCES
[1] World Commission on Environment and Development (1987). Our Common Future. Oslo.
[2] Tuomi, I. (2018). The Impact of Artificial Intelligence on Learning, Teaching, and Education.
Publications Office of the European Union.

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[3] Popenici, S., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and
learning in higher education. Research and Practice in Technology Enhanced Learning.
[4] Bayne, S. (2015). Teacherbot: interventions in automated teaching. Teaching in Higher Education,
455-467.
[5] Schmidt, A. (2017). How AI Impacts Education. Retrieved February 2019, from
Forbes:https://www.forbes.com/sites/theyec/2017/12/27/how-ai-impacts- education/#22edd83f792e.
[6] Hawksworth, J. (2018). AI and robots could create as many jobs as they displace. Retrieved 2019,
from World Economic Forum: https://www.weforum.org/agenda/2018/09/ai-and-robots-could-create-
as-many-jobs-as-they- displace/.
[7] Andrews, W. (2018). Craft an Artificial Intelligence Strategy: A Gartner Trend Insight Report.
Gartner, Inc.
[8] Khakurel, J., Penzenstadler, B., Porras, J., Knutas, A., & Zhang, W. (2018). The Rise of Artificial
Intelligence under the Lens of Sustainability. Technologies , 6(4), 100.
[9] The Future of Jobs (2018). Centre for the New Economy and Society.
[10] Martens, B., & Tolan, S. (2018). Will this time be different? A review of the literature on the Impact
of Artificial Intelligence on Employment, Incomes and Growth. Digital Economy Working Paper
2018-08; JRC Technical Reports.
[11] Mourshed, M., Farrell, D., & Barton, D. (2019). Education to employment: Designing a system that
works. Retrieved April 1, 2019, from McKinsey Center for Government:
https://www.mckinsey.com/industries/social-sector/our-insights/education-to-employment-
designing-a-system-that-works.
[12] Boyer, R. H., Peterson, N. D., Arora, P., & Caldwell, K., (2016). Five Approaches to Social
Sustainability and an Integrated Way Forward. Sustainability, 8(9), MDPI AG.
[13] Brunello, G., & Rocco, L. (2017). The effects of vocational education on adult skills, employment
and wages: What can we learn from PIAAC? Springer Link, 8-315.
[14] Schultz, T. W. (1961). Investment in Human Capital. The American Economic Review, 1-17.
[15] Becker, G. S. (1962). Investment in Human Capital: A Theoretical Analysis. Journal of Political
Economy , 9-49.
[16] Flanagan, J. (2014). Tinder-style matchmaking helps you bag your next job. Retrieved from New
Scientists: https://www.newscientist.com/article/dn25172-tinder-style-matchmaking- helps-you-bag-
your-next-job/.
[17] Gus Bekdash, (2019). Using Human History, Psychology, and Biology to Make AI Safe for Humans,
Chapman & Hall/CRC.
[18] The Student Circles.com, Artificial Intelligence Study Notes
https://www.thestudentcircle.com/quickguide.php?url=artificial-intelligence
AUTHOR
Prof. Yew Kee Wong (Eric) is a Professor of Artificial Intelligence (AI) &
Advanced Learning Technology at the HuangHuai University in Henan, China. He
obtained his BSc (Hons) undergraduate degree in Computing Systems and a Ph.D.
in AI from The Nottingham Trent University in Nottingham, U.K. He was the
Senior Programme Director at The University of Hong Kong (HKU) from 2001 to
2016. Prior to joining the education sector, he has worked in international
technology companies, Hewlett- Packard (HP) and Unisys as an AI consultant. His
research interests include AI, online learning, big data analytics, machine learning,
Internet of Things (IOT) and blockchain technology.

THE USE OF ARTIFICIAL INTELLIGENCE IN HUMAN RESOURCES DEVELOPMENT

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THE USE OF ARTIFICIAL INTELLIGENCE IN HUMAN RESOURCES DEVELOPMENT