Assignment | Artificial Intelligence Opportunities for Enhancing Human

Running head: ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
Artificial Intelligence Opportunities for enhancing human development in Thailand
Name of the Student
Name of the University
Author note

1ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
Abstract
This report is focused over the development of AI supported technologies for the betterment of
livelihood standards in Thailand. The focus of discussion in this report is based on the main
implementation strategies of the project and the various risks that are associated with the
implementation of the project. Risks are defined as highly critical in nature and they might cause
negative impacts towards the project. The primary part of discussion of this report discusses
about the ways in which AI could prove to be beneficial towards the growing standards of
positive impacts over the healthcare sector. The healthcare sector of Thailand currently follows
the traditional method of treatment. In this discussion, it has been discussed about the ways in
which AI could bring in successful changes towards the developmental aspects. After the
discussion over the importance of AI within the healthcare sector, the possible risks that could
approach towards the project have been clearly defined. The top ten risks that could possibly
bring in negative impacts towards the project have been clearly been identified and discussed
appropriately. These risks have been categorised based on their definition. These include
technical risks, cultural acceptance risks, change management risks, inefficiency of project
implementation and budgetary constraints. There are high chances that these risks might put a
negative impact towards the project development phase and might be a major cause for the
downfall of the project. The following parts of the report discusses about the 4 kind of strategies
based on risk management. These strategies are Risk avoidance, Risk acceptance, Risk
transference and Risk mitigation. The definition of these standards would be considered as
highly important as they clearly define some plans based on which the approachable risks could
be avoided. The report further concludes by discussing about the positive impacts that could be
made with the mitigation the risk scenarios.

2ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND

3ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
Table of Contents
1. Introduction..................................................................................................................................3
1.1 Scope of the Project...............................................................................................................3
2. Discussion on Risks and Control Strategies................................................................................4
2.1 The Risk List for the Concerned Project...............................................................................4
2.2 Risk Avoidance Strategies and Methods...............................................................................8
2.3 Risk Acceptance, Transference and Mitigation Plans...........................................................9
3. Conclusion.................................................................................................................................13
References......................................................................................................................................14

4ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
1. Introduction
1.1 Scope of the Project
The use of Big Data and Artificial Intelligence could be defined as an enormous approach
towards the development aspects of the sustainability standards. This discussion would be
focused over presenting various kind of opportunities towards the development of economic
standards, living standards and highly contribute towards the vision of Thailand 4.0. This is
defined as a new based economic model that is primarily driven by creativity, innovation and
technology. With the implementation of AI supported technologies, it would prove to unlock
different benefits and unlocking the challenges faced by the country due to economic challenges
(Jones and Pimdee 2017). One of the core aspect that would be followed with the impact of
Thailand 4.0 is based on the emphasis of their objectives based on the development of new form
of S-Curve industries. The development of AI supported technologies within Thailand 4.0 would
include the investment within robotics, digital technologies and the development framework of a
medical hub.
In the recent times, the digital economy is based on the extensive support from Big Data
and AI supported technological systems. The AI systems have an immense capability of handling
large amount of unprocessed data that are gathered from a vast number of sources. However,
with the proliferation of data being collected, processed, analysed and further generation of
results, there are major challenges that are being faced by the technical experts in dealing with
certain kind of risks that are approaching towards the systems (Ziuziański, Furmankiewicz and
Sołtysik-Piorunkiewicz 2014). This discussion is focused over the various kind of risks that are
being generated with the implementation of AI supported technologies. Different risks based on

5ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
financial constraints, technical difficulties during the process of implementation, project
scheduling and many other highly contribute towards negative aspects growing over the project.
The following sections of the report would thus be focusing over the topmost risks, which
might affect the development systems of AI supported technologies. AI has immense power to
transform the economic condition of Thailand and hence the investor and other stakeholders
involved with the development of the project should make efficient measures (Cutamora 2018).
These measures should be highly focused over discussing the scenarios caused by risks, the
likelihood and impact of risks and the implementable mitigation approaches towards the risks.
There would also be a major consideration of different strategies based on risk avoidance, risk
acceptance, risk transference and risk mitigation. Based on discussing over these aspects, the
development controls would also be need to be focused.
2. Discussion on Risks and Control Strategies
2.1 The Risk List for the Concerned Project
The World Bank has taken the primary responsibility to bring in a sustainable culture
with the use AI in the purposes of human development in various areas of Thailand. With the
implementation of this technology, there would be a massive achievement of business goals
based on decreasing the levels of poverty while also increasing welfare and prosperity in the
livelihood standards (Ongkasuwan and Sookcharoen 2018). On a further in-depth study of the
implementation schemes and the areas in which AI would be implemented, it can be discussed
that the massive technological innovation would be implemented within the public healthcare
sector. This discussion is focused over the implementation of Health Service Prioritization Tool
that would be supported by AI technology in order to bring in massive gains for the outputs.

6ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
However, unlike any other project, the implementation of AI within the healthcare sector
focused over human development would be subjected to several kind of risks. These risks are
discussed as follows:
1. Complete dependency on changing dataset and AI decisions – Total dependency on
evolving datasets, which would be generated on a continuous manner might lead to problems
based on the identification of biasness within the model. Inherent biasness within the data inputs
might be a major factor for unfair or inefficient outcomes in the future.
2. Complete acceptance of technology within existing market – The healthcare sector
of Thailand, which used to follow their existing approaches for solving health problems and thus
cared for human development might resist for the immediate change (Photikitti Dowpiset and
Daengdej 2019). The management team at the human development areas of Thailand might also
fear that the new technology might turn out to be inefficient and cause other serious concerns for
the people.
3. Misuse or Improper approaches to output generated – Improper kind of algorithms
if defined or used within the new system could lead to poor quality of data being generated.
Complex limitations based on AI model would lead to incorrect interpretation of AI based
outputs and further leading to poor results (Sakulkueakulsuk et al. 2018). Data if generated in a
poor quality would result in poor kind of treatment problems and thus would not be able to assist
doctors. Moreover, complex designed algorithms might create a problem for technology experts
to decide about the ways in which a solution had reached up to a decision.
4. Security Vulnerabilities – There might be several open source components that would
not be updated frequently or might not be supported. Lack of latest security patches within the

7ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
software might lead to security vulnerabilities affecting the system and this might cause future
problems for the software engineers in locating the exact issue that has raised (Harini and Rao
2019). Complex algorithms might be a leading factor for malicious manipulation by machines
and humans. There might also be a problem with the immediate risk based on security breaches
within the data collected. The AI algorithms might change their working functionalities
according to the changing scenarios. However, any kind of manipulation within the internal data
would lead to posing of security risks based on which there might be a problem based on
interaction.
5. Change Management Problems – There might be some kind of instances in which
there are existing IT legacy systems infrastructure. These might not be compatible with the
newly defined AI supported infrastructural systems. The existing legacy systems might not be
able to process the data gathered by the internal systems (Kawtrakul and Praneetpolgrang 2014).
There might be some kind of complex AI applications, which would be defined for the
healthcare sector. These might create some complications based on making necessary decisions
within complex form of AI applications. Hidden decision-making layers present within the
neural networks might create a problem for understanding of the quick decisions made by the
systems.
6. Compatibility with Culture and Product Innovation – The deployment of AI
supported technology might not meet with the increasing demands of customers. There are some
kind of major problems, which needs to be addressed at an early phase (He et al. 2019). AI
supported technologies might not be able to provide better outcomes as was expected during the
development of the products.

8ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
7. Ethical and Regulatory Concerns – There might be some kind of ethical and
regulatory concerns based on a wide form of acceptance from the local public and management.
The AI supported technologies might not be able to satisfy the ethical standards. These standards
had been previously defined under the consideration of governance based on human
development standards (Char, Shah and Magnus 2018). The new kind of AI technological
systems might not be able to meet with the pre-defined standards and thus might create several
problems. The new technology would also might not be able to meet with the regulatory systems.
8. Low Budget impacting the full development – AI supported technologies incur a
high number of software packages, complex algorithms and many complexities. Technical
expertise and highly skilled staff would be required for the development purpose (Bates et al.
2014). Hence, this would require a high amount of budget that needs to be distributed across all
kind of departments and use of resources. The human development management team might not
sponsor a high budget for the implementation process of AI technology.
9. Insufficient skills and low expertise – AI supported technologies need a high amount
of skill set that needs to be developed by the technicians working over the project. Insufficient
amount of skills, if been developed might lead to critical implications based on implementing a
highly dependable solution (Awwalu et al. 2015). Continuous engagement of employees and
stakeholders within the project is highly needed. The people currently involved with the
improvement of health standards and human development would need to properly understand the
ways in which the new technology would function. Lack of training and low knowledge over
computerised systems might create problems after the implementation process.
10. Low support from third-party operators and vendors – Over-reliance on the
market standards and on a large number of third-party AI suppliers and vendors could increase

9ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
the chances of concentration risks. They also might have network related effects during
performing one event, which might become insolvent and thus suffer significant form of
operational risks (Abdullah, Albeladi and AlCattan 2014). There might be many new entrants
within the market who would want to provide the valuable services for the human development
standards. However, they might lack control over the governance frameworks. This might create
a problem based on maintenance over failures that might occur within the internal control
systems.

10ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
2.2 Risk Avoidance Strategies and Methods
Risk Types Risk Avoidance Steps
Complete
dependency on
changing dataset and
AI decisions
In order to avoid the complicated situation based on changing
datasets that might affect the generated results, the algorithm should
be properly trained. One such example that could be accompanied is
development of standards that would suit the purpose of
implementing the technology.
Complete acceptance
of technology within
existing market
The technology would be highly accepted in the market as it leads to
significant improvements in human development standards of
Thailand. Hence, this could be avoided by proper education to
people.
Misuse or Improper
approaches to output
generated
This risk could be avoided with the help of a proper documentation
standard (Hengstler, Enkel and Duelli 2016). The proper layout of the
codes should be documented in order to help the technicians to
understand the particular sections in codes that might need
improvement in the future.
Security
Vulnerabilities
Data backup should be a prime concern. Any case of security
vulnerabilities could be avoided by using latest software packages
and latest programming languages.
Change Management
Problems
The areas in which AI implementation might create problems should
be firstly avoided and more areas could be focused upon.
Compatibility with
Culture and Product
Innovation
Employees could be trained with new job skills that would be the
immediate needs of the department (Miller and Brown 2018).
Customer needs should be identified firstly and then proper measures
need to be taken accordingly.
Ethical and
Regulatory Concerns
New ethical standards needs to be planned and implemented based on
acceptability of the new product.
Low Budget
impacting the full
development
Budget should be immediately estimated and planned after an initial
research have been done. Hence, this budget should be approved
before the implementation process.
Insufficient skills and
low expertise
Technical experts who would be working over the project should be
examined and appointed based on their diverse skill sets.
Low support from
third-party operators
and vendors
The third party vendors who would be providing the valuable service
should be ready to deal with the maintenance procedures over the
products (Yu, Beam and Kohane 2018). Any kind of maintenance
related risk should be efficiently dealt with the vendors and thus
treated accordingly.

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12ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
2.3 Risk Acceptance, Transference and Mitigation Plans
Risk Types Risk Acceptance Risk Transference Strategies Risk Mitigation Plans
Complete
dependency on
changing dataset
and AI decisions
Acceptable Risk Risks transferred to technicians and
internal decision management team
Data could be in the form of unstructured and
structured format. Hence, the security specialists
working over the project should determine the
accuracy of the algorithm that would be
implemented within the healthcare system (Scherer
2015). After the determination of the algorithm and
software packages, the pricing model should be
forwarded to the management team. They would
determine the pricing strategies and thus propose
them to the project sponsor for further approval.
Complete
acceptance of
technology within
existing market
Acceptable Risk Risks transferred to management team
of human development
A presentation and workshop should be proposed
and planned in order to educate the management
team about the growing importance of AI supported
technologies in the human development areas (Park
et al. 2018). Each of the stakeholders involved with
this project should be satisfied with the outcomes
and proposed plans. They should readily give their
consent before the technical team so that they could
initiate the project without further delay.
Misuse or
Improper
approaches to
output generated
Unacceptable Risk Not applicable The algorithms, which would be responsible for
processing the data should have a stable control
system. In order to manage this scenario, the
technical specialists and software designing team
should ensure that the training data should be
managed properly (Ransbotham et al. 2017). A
stable form of accuracy should be present in order

13ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
to manage both structured and unstructured data
properly. Insurance should also be supported with
the software packages. Any kind of discrepancy or
failure could be managed if the management would
have a proper legal backup procedure in such cases.
Security
Vulnerabilities
Acceptable Risk Risks transferred to security
specialists
External threats from hackers is a consistent
problem and it affects every sector. In order to
prevent the data from being hacked, the technicians
should imply high encryption standards (Kim and
Park 2017). Periodic re-validation of algorithms
should be done and latest software patches should
be made within the existing code. This would
highly help the technicians to bring in better
measures for the protection of internal data.
Change
Management
Problems
Acceptable Risk Risks transferred to technicians High scale projects such as AI implementation for
human development comprise of different
governance committees. Hence, they should be
efficiently trained for the purpose of identifying
and understanding the risk scenarios. Quality
assurance metrics should be present at each stage
and it should be ensured that every possible
changes that are being taking place be legitimate
and should be able to address any negative issues in
the future.
Compatibility
with Culture and
Product
Innovation
Acceptable Risk Risks transferred to management team The culture of the healthcare department might
follow the traditional standards for treatment and
might resist to change being implemented (Lee et
al. 2018). Hence, the culture of work could be
changed by ensuring a proper training session in

14ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
which they would be trained about the controls that
need to be brought in within the society.
Remediation protocols could also be planned within
the department based on which any reported issue
would be highlighted immediately and it would be
modified properly.
Ethical and
Regulatory
Concerns
Unacceptable Risk Not applicable The proper level of understanding of AI
implications over the healthcare sector is the
primary agenda for supervisors and regulator
maintaining bodies. The existing rules that are set
for the governing bodies over the human
development sector should be revised from time to
time. It should also be ensured that the regulatory
bodies would administer each of the algorithmic
standards (Hamet and Tremblay 2017). They
should also ensure that risks that are subjected
based on inacceptable standards of technology
would be discussed properly with the technical
providers and thus it would be managed efficiently.
Low Budget
impacting the full
development
Acceptable Risk Risks transferred to sponsors and
management team
Budgetary constraints can be the downfall of a high
scale project. Hence, the technical team and
management team should collaborate together in
developing estimates based on understanding the
various causes that could lead to the final budget.
The final budget should be proposed to the
Government of Thailand who would sanction the
budget for the project (Furmankiewicz, Sołtysik-
Piorunkiewicz and Ziuziański 2014). This could be
considered as a serious issue and thus needs to be

15ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
addressed by using proper cost estimates and all
necessary inclusions that would be made during the
ongoing course of the project.
Insufficient skills
and low expertise
Unacceptable Risk Not applicable Technicians should be highly efficient in solving
any major risks or issues that might arise during the
project development phase or after the completion.
Their skills should be checked before appointing
them to the final work over the project.
Low support
from third-party
operators and
vendors
Unacceptable Risk Not applicable Contract should be signed by both third party
service providers and vendors. Under such a
condition, they would be obligated to serve during
their contract period. This would be highly needed
in case any maintenance would be required for any
product.

16ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
3. Conclusion
The report discusses about the growing importance of AI that would be implemented
within the human development projects in Thailand. This project is based on the implementation
of the high-end technology in the healthcare sector. The World Bank in collaboration with the
Government of Thailand has discussed several measures based on implementing of the
technology within the sector for better services to their people and developing a sustainable
livelihood. In the recent past, it has been seen that there have been immense capabilities for AI to
bring in massive changes within the traditional used techniques. The development of Thailand
4.0 would be possible with the development of high standards of living for the people.
However, with the development of such high-end technology for the benefit of the
people, there would be many kind of emerging problems and risks associated with the complete
development purpose. The discussion part of the report discusses about ten different possible risk
scenarios that could affect the outcomes for the project. A proper definition of each kind of risks
have been defined properly. These risks range from several categories such as technical
acceptability, change in management standards, cultural acceptability based on product
innovation, budgetary constraints, low level of expertise skills and many others. These risks have
been defined as highly critical in nature and thus needs to be managed efficiently. The four
strategies of risk management have been defined, which are known as Risk avoidance, Risk
acceptance, Risk transference and Risk mitigation. The various strategies that could be planned
for the mitigation of risk scenarios have been focused clearly and thus a concrete plan for these
have been discussed clearly. Hence, from the above section, it could be concluded that the
application of such kind of measures would be highly be helpful for the development purpose
and ensuring a successful standard of livelihood.

17ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
References
Abdullah, A.L., Albeladi, K.S. and AlCattan, R.F., 2014. Clinical decision support system in
healthcare industry success and risk factors. International Journal of Computer Trends and
Technology, 11(4), pp.188-192.
Awwalu, J., Garba, A.G., Ghazvini, A. and Atuah, R., 2015. Artificial intelligence in
personalized medicine application of AI algorithms in solving personalized medicine
problems. International Journal of Computer Theory and Engineering, 7(6), p.439.
Bates, D.W., Saria, S., Ohno-Machado, L., Shah, A. and Escobar, G., 2014. Big data in health
care: using analytics to identify and manage high-risk and high-cost patients. Health
Affairs, 33(7), pp.1123-1131.
Capone, A., Cicchetti, A., Mennini, F.S., Marcellusi, A., Baio, G. and Favato, G., 2016. Health
Data Entanglement and artificial intelligence-based analysis: a brand new methodology to
improve the effectiveness of healthcare services. La Clinica Terapeutica, 167(5), pp.e102-e111.
Char, D.S., Shah, N.H. and Magnus, D., 2018. Implementing machine learning in health care—
addressing ethical challenges. The New England journal of medicine, 378(11), p.981.
Cutamora, J., 2018. FORECASTING PHILIPPINES PNEUMONIA MORBIDITY UTILIZING
ARTIFICIAL INTELLIGENCE. Malaysian Journal of Medical Research, 2(2), pp.88-90.
Furmankiewicz, M., Sołtysik-Piorunkiewicz, A. and Ziuziański, P., 2014. Artificial Intelligence
and Multi-agent software for e-health Knowledge Management System. Informatyka
Ekonomiczna, 2(32), pp.51-63.

18ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
Hamet, P. and Tremblay, J., 2017. Artificial intelligence in medicine. Metabolism, 69, pp.S36-
S40.
Harini, B. and Rao, N.T., 2019. An Extensive Review on Recent Emerging Applications of
Artificial Intelligence.
He, J., Baxter, S.L., Xu, J., Xu, J., Zhou, X. and Zhang, K., 2019. The practical implementation
of artificial intelligence technologies in medicine. Nature medicine, 25(1), p.30.
Hengstler, M., Enkel, E. and Duelli, S., 2016. Applied artificial intelligence and trust—The case
of autonomous vehicles and medical assistance devices. Technological Forecasting and Social
Change, 105, pp.105-120.
Jones, C. and Pimdee, P., 2017. Innovative ideas: Thailand 4.0 and the fourth industrial
revolution. Asian International Journal of Social Sciences, 17(1), pp.4-35.
Kawtrakul, A. and Praneetpolgrang, P., 2014. A history of AI research and development in
thailand: Three periods, three directions. AI Magazine, 35(2), pp.83-92.
Kim, M.K. and Park, J.H., 2017. Identifying and prioritizing critical factors for promoting the
implementation and usage of big data in healthcare. Information Development, 33(3), pp.257-
269.
Lee, J., Davari, H., Singh, J. and Pandhare, V., 2018. Industrial Artificial Intelligence for
industry 4.0-based manufacturing systems. Manufacturing letters, 18, pp.20-23.
Miller, D.D. and Brown, E.W., 2018. Artificial intelligence in medical practice: the question to
the answer?. The American journal of medicine, 131(2), pp.129-133.

19ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
Ongkasuwan, M. and Sookcharoen, W., 2018, May. Data analytics for service and operation
management improvement in medical equipment industry. In 2018 5th International Conference
on Business and Industrial Research (ICBIR) (pp. 370-375). IEEE.
Park, S.H., Do, K.H., Choi, J.I., Sim, J.S., Yang, D.M., Eo, H., Woo, H., Lee, J.M., Jung, S.E.
and Oh, J.H., 2018. Principles for evaluating the clinical implementation of novel digital
healthcare devices. Journal of the Korean Medical Association, 61(12), pp.765-775.
Photikitti, K., Dowpiset, K. and Daengdej, J., 2019. A Framework for Risk Management in AI
System Development Projects. In Forecasting and Managing Risk in the Health and Safety
Sectors (pp. 1-20). IGI Global.
Ransbotham, S., Kiron, D., Gerbert, P. and Reeves, M., 2017. Reshaping business with artificial
intelligence: Closing the gap between ambition and action. MIT Sloan Management
Review, 59(1).
Sakulkueakulsuk, B., Witoon, S., Ngarmkajornwiwat, P., Pataranutaporn, P., Surareungchai, W.,
Pataranutaporn, P. and Subsoontorn, P., 2018, December. Kids making AI: Integrating Machine
Learning, Gamification, and Social Context in STEM Education. In 2018 IEEE International
Conference on Teaching, Assessment, and Learning for Engineering (TALE) (pp. 1005-1010).
IEEE.
Scherer, M.U., 2015. Regulating artificial intelligence systems: Risks, challenges, competencies,
and strategies. Harv. JL & Tech., 29, p.353.
Yu, K.H., Beam, A.L. and Kohane, I.S., 2018. Artificial intelligence in healthcare. Nature
biomedical engineering, 2(10), p.719.

20ARTIFICIAL INTELLIGENCE OPPORTUNITIES FOR ENHANCING HUMAN DEVELOPMENT IN THAILAND
Ziuziański, P., Furmankiewicz, M. and Sołtysik-Piorunkiewicz, A., 2014. E-health artificial
intelligence system implementation: case study of knowledge management dashboard of
epidemiological data in Poland. International Journal of Biology and Biomedical Engineering, 8,
pp.164-171.