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Articial Intelligence Impacts on Higher Education
Yizhi Ma
Missouri University of Science and Technology*!3*/0#"1
Keng L. Siau
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Ma et al. Artificial Intelligence Impacts on Higher Education
Proceedings of the Thirteenth Midwest Association for Information Systems Conference, Saint Louis, Missouri May 17-18, 2018 1
Artificial Intelligence Impacts on Higher Education
Yizhi Ma
Missouri University of Science and Technology
Ymcy2@mst.edu
Keng L. Siau
Missouri University of Science and Technology
siauk@mst.edu
ABSTRACT
Artificial intelligence (AI) will change the world and higher education is no exception. AI will change the way we work, the
way we learn, and the way we live. This study analyzes the impact of artificial intelligence on higher education. Specifically,
this qualitative research will study the changes in higher education caused by AI. This study will also look at how higher
education can contribute to AI development. Further, this research will examine the use of AI in higher education delivery
and support. As a pioneering research in this field, this study will provide insightful information for educators and detailed
knowledge for academic theory building.
Keywords
Artificial Intelligence, Robotics, Automation, Higher Education
INTRODUCTION
Artificial intelligence (AI) is defined as the ability and development of an information technology-based computer systems or
other machines to complete the tasks that usually require human intelligence and logical deduction. Even though AI can
make the world a better place, AI comes with its own issues (Siau, 2018). Take the example of driverless vehicles. Driverless
vehicles open a new era of technology advancement in transportation. It brings huge benefit to both the car industry and the
customers from both economic and practical aspects. The usage of driverless vehicles frees the drivers from the mundane
task of driving and reduces accident rates (e.g., fatigue driving). Nevertheless, driverless vehicles will replace taxi, truck, and
Uber drivers!
Researchers from MIT, Daron Acemoglu, and Boston University's Pascual Restrepo, found out that each additional robot
takes over 5.6 workers' workload in the US, which means almost 6 people are losing their jobs with each robot
implementation (Gray, 2017). Another research conducted by scholars in Oxford University (Grace, Salvatier, Dafoe, Zhang,
& Evans, 2017) estimated that at least 47% of the current jobs in the United States are at a very high risk of being taken over
by AI. More than 54% of the current jobs in Europe are facing the same threat from machines, not in the coming 100 years,
but within the next 20 years. Facing such a severe threat from AI, robotics, and automation, what should people do to stay
competitive in the job market has become the new million-dollar question? Further, how should higher education react to
help their students compete in the AI age?
This nascent study will research on the AI impact on higher education, and the proactive and reactive changes made in the
higher education. This will be a longitudinal action research as one of the researchers is an administrator and will be
formulating curriculum and policy changes to react to and take advantages of the upheavals caused by AI.
LITERATURE REVIEW
Artificial Intelligence (AI)
Ma et al. Artificial Intelligence Impacts on Higher Education
Proceedings of the Thirteenth Midwest Association for Information Systems Conference, Saint Louis, Missouri May 17-18, 2018 2
Artificial intelligence (AI) can be classified into Weak and Strong AI. Weak AI, also known as artificial narrow intelligence,
is designed to be focused on a narrow task. One example of Weak AI is the self-driving vehicle. It is specialized for a specific
task. Another category is the Strong AI, also known as artificial general intelligence. Strong AI is capable of most (if not all)
cognitive functions that a human may have and can apply intelligence to more than one specific problem (Kurzweil, 2005;
Voss, 2017). Strong AI is considered by many prominent researchers and industrialists such as Stephen Hawking, Bill Gates,
and Elon Musk as an existential threat to human civilization. In this research, we focus on Weak AI and the use of the term
AI subsequently in this article means Weak AI.
Impact of AI
Forbes Technology council predicts that by 2030, the potential of artificial intelligence will reach $15.7 trillion in the global
economy. The use of AI is not limited to Amazon and Youtube advertisement applications. AI has also been applied to
recommending new stylish clothing or filtering spam emails. Virtual assistant has been a new trend globally such as Siri,
Googles Assistant, and Cortana. These virtual assistants are now part of people's life. AI is also playing an important role in
the Finance sector such as securing bank accounts and monitoring transaction requests. Another application of AI is the self-
driving vehicles. A number of countries have already put the self-driving vehicles on the road and start experimenting with
driverless trucks for delivering goods.
These AI advancements, however, come at a cost (Siau and Wang, 2018; Siau and Yang, 2017). Researchers from MIT
estimate that the usage of automated transportations could threaten 2.2-3.1 million existing jobs in the U.S. (Rotman, 2017).
University of Oxford's Future of Humanity Institute estimates that there is a 50% chance that machines will be able to take
over all types of human jobs in 120 years. The research surveyed 352 scientists from different areas and their answers were
compiled to predict how long it might take for machines to replace human on job positions. The collected result indicates that
there is a good chance that more than 70% of the job functions will be replaced by machines in 50 years (Gray, 2017).
AI Effects on Higher Education
With the job replacements and displacements generated by AI, future job market and required skillsets would be significantly
different from now (Siau, 2017, 2018; Rainie & Anderson, 2017). Multiple studies concluded jobs that involve tasks that are
routine and structured are easier to automate and will be replaced by AI soon. On the contrary, job tasks that are more
unstructured and involved managing people are harder to be replaced by AI. Higher education needs to be adaptive and
evolve continuously.
Higher education will be impacted by AI in many ways and the two major areas are curricula and enrollment. First, AI will
have a sweeping impact on curriculum in higher education. The strength of AI is its speed, accuracy, and consistency. It is a
lost cause to compete with AI on these dimensions. On the other hand, AI is still weak in soft skill such as creativity,
innovation, critical-thinking, problem-solving, socializing, leadership, empathy, collaboration, and communication. This is
not to say that we should ignore the hard skills such as science, math, and engineering. Higher education should still train the
students in the fundamentals of science and math, and at the same time provides opportunities and training for students to
enhance their soft skills. Some universities are already offering AI and Machine Learning courses to not only computer
science students, but also business students as business managers and executives need to understand the capabilities,
limitations, and implications of AI in the business world.
The other impact of AI in higher education is enrollment. Liberal arts and humanities majors may become more popular as
these areas are less susceptible to “AI-invasion.” Areas such as accounting and financial analysis that may be hit hard by AI
may see a drastic drop in enrollment. Also, with the wealth gap and potentially millions (if not billions) out of jobs, higher
education may no longer be affordable to many.
Other possibilities include the use of AI assistants and AI instructors in teaching. Below are some examples of the use of AI
applications in education:
Ma et al. Artificial Intelligence Impacts on Higher Education
Proceedings of the Thirteenth Midwest Association for Information Systems Conference, Saint Louis, Missouri May 17-18, 2018 3
AI Application
Function
Reference
Title of Article
Virtual AI
Teaching
Assistant
Be able to
answer
frequently asked
questions without
the help of
humans
http://www.news.gatech.edu/2017/01/09/jill-watson-
round-three
Jill Watson, Round Three
Intelligent
tutoring systems
Using cognitive
science and AI
technologies to
provide
personalized
tutoring in real-
time
https://elearningindustry.com/intelligent-tutoring-
systems-what-happened
Intelligent Tutoring
Systems: What
Happened?
Smart Education
Using AI
technology to
make education
more effective,
efficient,
flexible, and
comfortable
Zhu, Z. T., Yu, M. H., & Riezebos, P. (2016). A
research framework of smart education. Smart learning
environments, 3(1), 4.
A research framework of
smart education
Theoretical Foundation
Organizational Change
Organizational change studies how an organization changes its structure, strategies, operational methods, technologies, or
organizational culture to affect change within the organization, and investigates the effects of these changes on the
organization (Hussain, Lei, Akram, Haider, Hussain, & Ali, 2016). Organizational change can be continuous, active, and
evolving (Weick & Quinn, 1999). As AI is expected to result in organizational change in higher education, the following
discusses some of the organizational change theories and models that can form the conceptual and theoretical foundation to
understand such changes.
Lewin’s Change Management Model
Kurt Lewin (1946) concluded that a successful change happens with a three-step process -- unfreezing stage, changing stage,
and freezing stage. In the unfreezing stage, people must be open and encouraged to evaluate their current situations
objectively. This can be the hardest step as one needs to break open the shell of complacency and self-righteousness. When
people have accepted that changes are necessary, then it comes to the changing stage. To implement this step, a long-term
view and positive attitude are necessary. This is particularly true for AI impacts on higher education as the future can be
complicated and unpredictable. After the transition stage is over, the freezing stage takes place to ensure that the changes stay
rather than switching back to the original status.
Kotter’s 8 Step Change Model
Kotter’s 8 step change model is proposed by John Kotter in 1995 (Kotter, 1995). After observing and studying countless
leaders and organizations from the beginning of transformation to how they executed their strategies, and till they completed
the whole transformation successfully, he summarized 8 steps for a successful organizational transition:
1. Increase the urgency for change
Ma et al. Artificial Intelligence Impacts on Higher Education
Proceedings of the Thirteenth Midwest Association for Information Systems Conference, Saint Louis, Missouri May 17-18, 2018 4
2. Build a team dedicated to change
3. Create the vision for change
4. Communicate the need for change
5. Empower staff with the ability to change
6. Create short-term goals
7. Stay persistent
8. Make the change permanent
The focus of this model is on preparing and accepting the change itself and how to get people and employees on board rather
than the actual change.
RESEARCH METHODOLOGY
In this research study, a qualitative longitudinal action research will be conducted. Action research focuses on solving an
immediate problem and providing a reflective process of progressive problem solving led by individuals working with others
(Fals-Borda, & Rahman, 1991). It is also defined as a part of a "community of practice" to discover potential issues and
resolve them.
Action research involves actively participating in a change situation and simultaneously conducting research. It is often
designed to be in an existing, long-term organization so as to ensure the continuity of the whole research. Action study can
help to create a better understanding of the research questions and provide supportive evidence to address the research focus.
One of the researchers in this study is an administrator of a college. The administrator is interacting with other administrators
and faculty within and outside his college and institution to formulate policies and plans to better prepare his college for the
AI age. Action research is an appropriate research methodology in this case. Action research enables the researcher to
examine his own plans and policies systematically and carefully, using a scientific and known research method.
EXPECTED THEORETICAL AND PRACTICAL CONTRIBUTIONS
AI will be impacting higher education in a significant way. Many jobs will become obsolete and new skill sets will be
required. Higher education needs to rise to the challenge to prepare students for the AI revolution and equip students with the
necessary skill sets to compete in the AI age. This nascent research aims to shed light on the higher education evolution and
revolution as AI advances.
REFERENCES
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much-longer-before-our-first-ai-catastrophe-464043243
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research
4. Grace, K., Salvatier, J., Dafoe, A., Zhang, B., & Evans, O. (2017). When will AI exceed human performance? Evidence
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Proceedings of the Thirteenth Midwest Association for Information Systems Conference, Saint Louis, Missouri May 17-18, 2018 5
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