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. . • - 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.

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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 potentia