ABSTRACT
The creation of artificial intelligence in machines that potentially have the capacity to resolve
complex tasks and make major decisions have become a matter of global attention and raised
ethical concerns for the human race and boosted technological advancement.
The essay addresses some of the ethical considerations paid to AI systems as well as examines
potential mitigation modalities and practical solutions to these issues.
INTRODUCTION
The promise of advancement in artificial intelligence in recent years has been honoured through
machine learning, extensive research, and data storage and control. Currently, digital systems
are being adapted to work in symbiosis with AI systems and affect sectors such as
manufacturing, transportation, healthcare, etc. Artificial intelligence is a marvel of human
innovation, and it is technology that could be inherently dangerous if abused in utilization.
Although the progress made by artificial intelligence is significantly useful, there are ethical
challenges for humanity and the environment that this technology introduces. This essay focuses
on those concerns and the possible solutions that could bolster regulation and moderation,
citing case studies and the current literature.
PRIVACY
A key foundation of artificial intelligence is machine learning. This entails receiving large amounts
of data in order for the AI system to assimilate and produce efficient results. Through
advancements in technology, facial recognition and targeted marketing have become staples for
corporate tech companies and global retail giants when interfacing with customers. In the
instance of facial recognition, the technology focuses on face position and detection, image
preprocessing and most importantly identity recognition (Li et al, 2020). Meanwhile, targeted
marketing requires obtaining data from individuals, gaining a deeper understanding of habits and
purchase patterns and then advertising products and services according to the customer profile
built from the analyzed data.
Ethical issues arise in situations where customers’ data are taken without their express
permission. According to Tabassum et al (2020), Amazon’s Alexa was said to be listening in on
private conversations without prior warning to customers. A way to mitigate this is to keep
humans in the loop and ensure global bodies serve as lieutenants for AI system creators and
developers. This will ensure sanctions for data hacks, data mismanagement and nefarious retail
practices.
BIASES
As discussed, data compilation is important for processing and presenting accurate results.
Algorithms are mainly used in making decisions based on data that has been learned by the
machine. However, challenges come when the data presented to these algorithms are one-sided
or myopic in nature. This is because the AI system will be perceived as making biased decisions
after filtering through a database. According to Datta et al (2015), there was an unbalanced
distribution in the advertising of well-paying jobs that favoured men more than women. There
have also been reports of search engines producing western ideas of ‘wedding attire’ while
relegating Indian, African and other wedding attire to ‘performance art’ or ‘costumes’ when
searched (Zhou, 2018). This unfortunately serves as a microcosm of our society and the world.
There needs to be an intentional effort to eliminate biases from algorithms so as to curb these
types of misrepresentations of information. According to Bird et al (2020), AI tools such as
Knockri, Ceridian and Gapjumpers bypass features such as race, gender, age, etc. and give
attention to employees’ job experience and qualifications. It is important that attention is paid to
AI regulatory technology as it could be the key to eliminating bias in the algorithms.
INTELLECTUAL PROPERTY
With AI systems able to create pieces of artwork, compose music and produce written stories,
the challenge brought into focus is ownership. This is another ethical issue because appointing
the owner, from the designer and trainer of the AI system, the creator of the system or the
actual AI system itself, is a delicate decision. Due to these conditions, there is the opportunity for
theft of intellectual property and no adequate apparatus to assign credit and acknowledgement
to creators (Kretschmar, 2022). This could potentially lead to legal action on the grounds of
violation of rights from the perspective of the original creators. Furthermore, according to Naqvi
(2020), AI systems could produce works similar to already existing works. This could lead to
accusations of copyright infringement by creators. The intellectual property issue is complex and
requires delicate regulation and legal substructures to be established. It is also important to
update certain modalities pertaining to intellectual property protection with the new lessons AI
will present.
ENVIRONMENTAL IMPACT
Global warming is an undeniable phenomenon that looms large over our existence as a species,
and it is important to limit further impact as much as possible. Nonetheless, computer centres
are the powerhouses for machine learning and training AI. This is an ethical challenge as they run
cloud infrastructure, and according to Patterson (2021) they are creating over seven times more
carbon emissions a year than the average adult in the United States. Alternatively, AI is used in
developing autonomous vehicles which reduce fuel consumption by about 20 percent and drop
greenhouse gas emission levels. (Iglinski et al., 2017)
POWER AND CONTROL
As previously stated, it takes large amounts of computing power to run the most powerful cloud
and data mining infrastructure. Ostensibly, artificial intelligence is a technology that is managed
by the wealthy and large corporate tech organisations today. According to Wright (2019), AI
systems are being developed and sanctioned by the Chinese and Russian governments. Slowly,
these entities are building a monopoly on AI and taking away the destiny of the technology from
the public. This is a major issue because it keeps power in the hands of the few and may lead to
exploitation through the threat of autonomous weapons and sophisticated espionage. There is a
need to tie inappropriate AI actions to people and nations accordingly and also set up
committees to ensure regulation and decentralise the control of AI.
CONCLUSION
Consequently, artificial intelligence is frontier technology. It has a high ceiling for growth and the
potential is evident. Due to the sheer power of AI systems, there are ethical concerns that
humans are faced with. Challenges such as privacy and security, biased data in algorithms, theft
of intellectual property, environmental impact and monopoly of control are major concerns for
the human race. Nevertheless, solutions, mitigations and regulations including keeping humans
in the loop, AI technology tackling bias, and meticulous legal intellectual property protection
should be implemented as swiftly as possible due to the nature of the expeditious advancement
in technology. It is also important to use AI systems to counterbalance the impact on the
environment through green initiatives, and establish regulatory bodies to ensure even
distribution of the technology.
REFERENCE
Naqvi, Z. (2020). ‘Artificial Intelligence, Copyright, and Copyright Infringement’, Marquette.
Intellectual Property Law Review. 24(1), 4.
Li, L., Mu, X., Li, S. and Peng, H. (2020). ‘A Review of Face Recognition Technology’, IEEE Access.
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Iglinski, H. and Babiak, M. (2017). ‘Analysis of the Potential Autonomous Vehicles in reducing the
Emissions of Greenhouse Gases in Road Transport’, Procedia Engineering. 192, 353-358.
Wright, N. (2019). Artificial Intelligence, China, Russia, and the Global Order.
Bird, E., Fox-SkellyJ., Jenner, N., Larbey, R., Weitkamp, E. and Winfield, A. (2020). ‘The Ethics of
Artificial Intelligence: Issues and Initiatives’, Panel for the Future of Science and Technology.
Zhou, J., & Shen, M. (2018). ‘When Human Intelligence Meets Artificial Intelligence’. PsyCh
Journal, 7(3), 156–157.
Datta, S., Barua, R. and Das, J. (2019). Application of Artificial Intelligence in Modern Healthcare
System. Intechopen
Tabassum, L. (2020). ‘Fundamentals of Artificial Intelligence and Deep Learning Techniques’.
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Patterson, D., Gonzalez, J., Le, Q., Liang, C., Munguia, L., Rothchild, D., So, D., Texier, M. and
Dean, J. (2021) ‘Carbon Emissions and Large Neural Network Training’. Computer and
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