Ethical Considerations in Using Artificial
Intelligence and Integrating Al
Technologies for Personalised Health
Care.
The incorporation of artificial intelligence (AI) into personalized medicine
is a topic at the forefront of innovation and ethical research. As Al systems
become more advanced, they have great potential to revolutionize
personalized medicine by providing treatments and interventions.
However, this potential includes a variety of ethical considerations that
must be carefully explored to ensure that the deployment of Al
technologies benefits all stakeholders without violating individual rights
and exacerbating existing inequalities.
One of the main ethical considerations is data privacy and consent
issues. The effectiveness of Al in healthcare depends on the availability of
personal health data. Ensuring the confidentiality of this data and
obtaining patient consent for its use is of utmost importance. This
requires strong data protection and clear information about the use,
storage and sharing of patient data (Mittelstadt, 2019).
Fraud and fairness in Al algorithms represent another important ethical
issue. Al systems tend to reflect or amplify social networks in the data
they are trained on, which can make a difference in health outcomes.
Addressing these vulnerabilities and ensuring that Al technologies are
developed and deployed in a way that promotes justice is essential to the
ethical integration of Al into health care (Rajkomar et al., 2018).
In the context of Al in healthcare, accountability raises important ethical
questions. The complexity of Al systems and the sometimes impossible
decision-making process complicates accountability, especially when Al-
driven decisions lead to adverse patient outcomes. It is important to
establish a clear framework for responsibilities, including how decisions
are made and who is responsible when problems arise (Luxton, 2014).
Additionally, the potential for reduced generosity in the age of Al is also a
major concern. Al can improve the efficiency and accuracy of healthcare delivery, but there is a risk that an over-reliance on technology will
undermine the human care element at the core of the patient-provider
relationship. It is important to ensure that Al acts as a tool to enhance,
rather than replace, human judgment and empathy (Blease et al., 2019).
Navigating the ethical terrain of integrating Al into
personalized medicine requires the collaboration of a wide range of
stakeholders, including technologists, medical professionals, ethicists,
and policymakers. By considering these ethical
considerations early on, Al can be used to improve healthcare outcomes
while maintaining high ethical standards.
The basis of Al 's contribution to personalized medicine lies in its ability to
process large amounts of health data to provide personalized treatment.
But this requires careful consideration of data privacy and informed
consent. According to Mittelstadt (2019), strong encryption methods and
early data management models are needed to ensure that patients are
fully informed about the use, storage and sharing of their data.
Implementing comprehensive data protection laws and ethical guidelines
is critical to maintaining patient trust and privacy in the digital age. For
example, Europe's GDPR is a benchmark for data privacy law,
emphasizing the need for clear consent and giving individuals control over
their personal data (European Commission, 2018).
Compromises in Al algorithms raise serious ethical issues and may even
pose health risks. Rajkomar et al. (2018) argue that to reduce these risks,
it is important to develop Al systems with appropriate reasoning
integrating diverse data sets that reflect a broad patient population.
Algorithms must be continuously monitored and adjusted to ensure that
current settings are not maintained or new ones are introduced.
Collaborative and multidisciplinary efforts can help define and refine
algorithmic settings, thereby promoting equitable health outcomes for all
individuals, regardless of background.
The opaque nature of Al algorithms undermines accountability, especially
when decisions affect health. Luxton (2014) highlights the need to define
responsibilities between Al developers, healthcare providers and
regulators. Establishing clear protocols for Al decision-making processes
and ensuring that people are present to interpret and reject Al recommendations when necessary is critical to maintaining accountability.
In addition, the development of ethical standards and legal frameworks
will help clarify responsibility and professional liability in the event of
adverse consequences arising from Al interventions.
As Al technologies become more integrated into healthcare delivery, it
becomes increasingly difficult to maintain the human touch in patient-
provider interactions. Blase et al. (2019) highlight the importance of
ensuring that Al tools enhance, rather than replace, the love and
compassion at the heart of healthcare. Teaching healthcare professionals
to properly integrate Al insights while focusing on patient care can
preserve the human element in the digital age. This approach ensures
that Al acts as a support tool, improving diagnostic accuracy and
personalizing treatment without compromising human judgment and
human value.
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- References
Mittelstadt, B. (2019). Principles alone cannot guarantee ethical Al.
Nature Machine Intelligence, 1, 501–507.
Rajkomar, A., Hardt, M., Howell, M. D., Corrado, G., & Chin, M. H.
(2018). Ensuring fairness in machine learning to advance health
equity. Annals of Internal Medicine, 169(12), 866–872.
Luxton, D. D. (2014). Artificial intelligence in psychological practice:
Current and future applications and implications. Professional
Psychology: Research and Practice, 45(5), 332–339.
Blease, C., Kaptchuk, T. J., Bernstein, M. H., Mandl, K. D., Halamka,
J. D., & DesRoches, C. M. (2019). Artificial intelligence and the
future of primary care: Exploratory qualitative study of UK general
practitioners' views. Journal of Medical Internet Research, 21(3),
e12802. European Commission. (2018). Regulation (EU) 2016/679 of the
European Parliament and of the Council of 27 April 2016 on the
protection of natural persons with regard to the processing of
personal data and on the free movement of such data (General Data
Protection Regulation)./n 1.0 Introduction
With the rapid development of social media and the internet, celebrities and stars
I have gained unprecedented influence and appeal. Through social media platforms,
celebrities can engage in direct interaction with their fans, sharing their lives, product
recommendations, and personal opinions (Chung & Cho, 2017). For example, the
well-known American singer Taylor Swift has 92.47 million followers on Twitter are her
fans (Dixon, 2023). This close interactive relationship provides fans with more
opportunities for engagement and consumption, thereby fueling the rapid growth of
the fan economy. In support of this argument, Liang (2022, p.332) said the 'fan
economy' is, in its broadest sense, referring to the value and revenue generated via
interactions between individual fans (especially “super fans") and fan communities,
with the artists/stars (and their production studios and programs) that they follow."
The North American fan economy is deeply rooted in the entertainment and sports
industries, with fans following their favorite celebrities, movies, TV shows and sports
teams (Campo & Ryan, 2008). This passionate fan culture translates into a huge
economic impact, with fans buying merchandise, attending live events, and actively
participating in fan communities through social media platforms. Blockbuster films, TV
shows, and musical performers have benefited from the North American fan economy,
which has also encouraged expansion in sectors including merchandising, event
planning, and digital content creation (Johnson, 2013).
Likewise, China's enormous population and developing digital environment support its
fan economy (Li, 2022). Chinese fans have formed a huge fan community around
stars, idol groups and popular TV series. These enthusiastic fans actively support
their idols by purchasing related merchandise, attending fan mee Al: Good paraphrasing
and participating in various fan events (Li, 2022). The Chinese fan economy has become a powerful market force, shaping the success of entertainment companies
and influencing product endorsements and brand partnerships (Hou, 2019).
While there are some similarities between the fan economies in North America and
China in the area of fan culture and economic influence, there are also some obvious
distinctions. Lucas (2020) points out that there are some notable differences between
the fan economies in the US and China in terms of market size. With a historical
tradition and a solid star culture, the North American fan economy has an
unbreakable relationship to the developed entertainment industry (Sternheimer, 2011)
that started long before China's fan economy began. In contrast, the Chinese fan
economy is thriving in the digital age, using social media platforms and influencer
marketing to expand fan engagement and drive economic growth (Jia, hung, & Zhang,
2018). This report aims to compare the North American fan economy with the
Chinese fan economy, and analyze their similarities and differences in terms of
development background, market size, business model, and cultural influence.
41
It will do this by answering the next three research questions:
1) What are the similarities and differences between the fan economy business
models in the North America and China?
2) How do the fan economies of the North America and China differ in terms of
marketing size? What causes this discrepancy, and why?
3) To what extent has the growing fan economy positively affected the mindset of
citizens of the North America and China in the last decade?
2.0 Comparison of the Impact of the Northern
American Fan Economy and the Chinese Fan
Economy 2.1 What are the main similarity and difference
between the fan economy business models in
the North America and China?
2.1.1: Similarities
date
To data, a number of studies have indicated that "Star-centric" is a major common
feature of the fan economy in North America and China (eg. Chung & Cho, 2017;
Liang, 2022; Dixon, 2023). This may mean that the core of the fan economy revolves
around well-known stars, artists and public figures, whose popularity and influence
play an important role in fan enthusiasm and participation.
Pop music icons like Taylor Swift draw throngs of devoted followers in North America.
Her audience regularly purchases her CDs, goes to her shows, and promotes her
music on social media. Taylor Swift engages with fans through brand collaborations,
the release of limited-edition items, and other activities that further stoke their passion
and support (Junes, 2023).
Uos - Critical Analysis
UOS: Add synthesising
In China, Mi Yang (5) is a high-profile film and television star. Her popularity and
influence have attracted a large number of fans and become an important driving
force for the fan economy. Fans of Yang Mi actively participate in the promotion of her
works, buy her peripheral products, and share her updates on social media. Her fans
also expressed their support for her through online and offline activities, such as
organizing movie viewing events and voting for her (Ban, 2023).
Therefore, the celebrity's popularity and influence not only attract a large number of
fans, but also bring business opportunities and growth space for the fan economy. At
the same time, the interaction and relationship between celebrities and fans also
promotes the development of the fan economy, forming an economic model of interaction, support, and common growth.
2.1.2: Differences
S: Good INTERPRETATION
40
There are differences in the profit model between the fan economy in North America
and China. In North America, the main sources of income for the fan economy include
merchandise sales, concert tours, and endorsement partnerships. At the same time,
Schaefer, Parker, & Kent, (2010) propose that the sports industry has huge
UOS: Good synthesising
North America, attracting a large number of passionate fans. Likewise, Mocarski &
Billings (2014) hold the view that sports stars realize profits by signing sponsors,
selling peripheral products for fans, and selling event tickets.
Supporting this view, Mocarski & Billings (2014) write that LeBron James, a basketball
player for the NBA, gets money through endorsement deals with well-known
companies in addition to displaying excellent abilities on the court. While supporting
his squad, his supporters may purchase basketball shoes, jerseys, and other
memorabilia.
In China, the profit model of fan economy pays more attention to e-commerce live
broadcasts, social media advertisements and digital rewards. E-commerce live
broadcasting is a rising profit method in China's fan economy. Celebrities sell
products live on e-commerce platforms, attracting fans to buy and earn commissions
from them (Lucas, 2020). For example, Chinese internet celebrity Jiaqi Li (*) has
attracted a large number of followers by sharing beauty product recommendations
and shopping tips on Taobao which is a Chinese online shopping platform similar to
Amazon, and earns income through brand partnerships and endorsements. In
addition, Wong & Dobson (2019) point out that digital rewards are also a common profit
method in the Chinese fan economy. Fans can provide financial support to stars by
purchasing virtual gifts and rewarding stars for live broadcasts. It can be concluded that these different profit methods reflect the differences in
business models between North American and Chinese fan economies. North
America pays more attention to physical merchandise sales and concert tours, while
China pays more attention to digital methods such as e-commerce live S: Good INTERPRETATION
social media advertisements and digital rewards. The choice of these models is
related to the market environment, cultural background and consumer habits,
providing more opportunities for the sustainable development of the fan economy.
2.2 How do the fan economies of North America
and China differ in terms of marketing size and
cultural differences?
2.2.1: Population size and spending power
The fan economy is larger in China than it is in the USA. A likely explanation is that
35
China's huge population base provides fans with greater market p
| Al: Paraphrasing: similarity rate too|
consumer groups. China has the largest population in the world, about 1.4 billion
people (Fang et al., 2023), while the population of the USA is about 330 million
(Buchholz, 2022). Despite the comparatively high per capita income in the United
States, China's recent economic growth and consumption improvements have caused
Chinese consumers' purchasing capacity to keep rising (Figure 1).
What this evidence indicates is that, although the Gross domestic product (GDP) of
the United States is higher than that of China before 2025, the gap between them is
decreasing year by year. And China's GDP will be more than the GDP of the United
States between 2025 and 2030. With the growth of China's GDP, the purchasing
power of Chinese fans will also increase, thereby driving the growth of the fan
economy.
