Introduction
In the history of the workplace, technology has transformed and advanced, providing benefits and drawbacks to the production process. From the industrial revolution era to the age of the information era, technological developments have aided in improving efficiency and productivity in most sectors. It, however, has displaced employees, created economic inequality, and raised issues related to ethics. Employers have recently integrated AI into the production process, replacing various tasks with automated technology. Complex processes have made it easier to attain optimal outcomes using machines to manage these processes within most firms, which acts as a way to enhance human ability, thus promoting collaboration in the innovation of efficient production processes (Vogel, 2021, p.85). On one hand, adopting AI in the workplace creates employment opportunities where technical skills are required to run the machines, thus improving the economic state of the firm. On the other, the use of AI has led to job unsustainability and increased worker layoff, which risks losing traditional roles of workers to automatic machines; thus, societal inequality rises. This paper aims to analyze the ethical implications of artificial intelligence by examining its negative impacts to give insight into the correct plans, policies and programs that can aid in mitigating these ethical issues to create a beneficial relationship between humans and artificial intelligence.
Ethical Issues Associated with Artificial Intelligence
The use of AI in the production process is associated with several ethical challenges that raise the debate on its efficiency. One consideration is the bias brought by AI facial recognition systems that showed weakness in detecting dark-skinned faces compared to light-skinned faces. A study by Sadfar et al. concluded that the use of AI in automatic facial recognition displayed lower accuracy in seeing dark people, specifically women, which raises a concern about colour discrimination. The bias is a source of social inequality in society as it promotes alienation by colour, as depicted by (Bankins and Formosa, 726). Alienation by colour is a form of systemic injustice which promotes structural inequality in institutions. It challenges transparency and accountability as the developers of these intelligence machines are mandated to give clear guidance on AI’s correct and responsible deployment (Paredes, 1). In addition, AI raises ethical concerns about data privacy and security in cases where the firm lacks a sophisticated data security system. Specifically in the healthcare sector, the patient’s data is compromised when put in the AI with weak security protocol, which may increase the chances of being traced (Safdar).
The worries are further increased by the issues of surveillance and consent, where AI may be used to access an employee’s data without their permission. Bankins and Formosa (729) display concerns about AI changing the workplace experience, thus hindering the five principles of ethics in the workplace. Sadfar supports this argument by raising fears about how using machines can lead to errors as the task force believes the automatic systems are correct and thus pays little attention to the processes. Therefore, using AI socially impacts employees’ lives via job loss, disparities, and change in their work experience; accordingly, there is a need to address these ethical considerations.
Addressing the Opposition
Despite these ethical considerations raised in this paper, AI has varied pros and may contribute to the well-being of people in different sectors. Specifically, AI fosters workforce efficiency in the healthcare sector, where skills are well applied. Machine learning and algorithms increased the accuracy of interventions as the disease can be determined early using AI (Safdar). Also, the workforce can employ AI to make better decisions in the diagnosis process in healthcare facilities. Vogel (84) states that AI compiles vast medical data, giving insight for personalized interventions, thus reducing possible health risks by urgently enabling the diagnosis of infections. The idea is supported by a different study arguing that incorporating human efforts and AI use enables healthcare practitioners to improve the intervention processes, thus improving patient outcomes (Frehywo and Vovides, 2). In addition, AI has aided in amplifying the skills of human power to enhance their skills to perform duties correctly. A study by Bankins and Formosa (726) depicts how AI transforms employee skills via continuous learning; automating specific roles allows employees to focus on different endeavours, thus promoting creativity in the firm.
Discussion: Evidence Supporting the Study’s Position
After addressing both the pros and ethical cons of using AI today, employers must maintain balance by embracing the opportunities created by AI while at the same time understanding the challenges AI implementation faces. On one side, AI promotes efficiency in tasking; Vogel (85) argued that AI gives organizations the tools to optimize operations and thus improve production. Using AI also enables the task force where routines are automated, thus giving the party a chance to engage in extra creative processes. They are further enhanced to make sound decisions via I, which promotes autonomy over outcomes, especially in the health sector (Safdar, Frehywo and Vovides, 2). On the other hand, this technology brings immense challenges, such as the loss of jobs via machines’ replacement of human power. Appointments are also lost as the firms need a new workforce to control the automated devices (Bankins and Formosa, 729). The two authors also portrayed data bias as a challenge that raises ethical questions. Privacy and data security are another concern when using AI as the systems analyze vast amounts of personal data; this calls for a robust data protection system, especially in healthcare sectors where personal information is uploaded to automated machines. Therefore, there is a need to understand the pros and cons of using AI and maintain a balance between the two to ensure the effective use of AI without acting against ethical guidelines.
Conclusion
In conclusion, AI poses significant ethical implications for employers and the task force in the contemporary production process. By addressing these challenges, firms create a strategy for effective interactions between humans and these machines to increase the production process as intended by the AI developers. Firms should develop plans, programs, and regulations that promote the ethical use of AI, and work protocols should come in handy in maintaining the balance between the pros and cons of using AI in various sectors. Also, investing in technological studies is vital to promote efforts to improve the industry, such as data bias and security concerns, to create trusted AI systems. Employing these strategies, the employer empowers the current task force to be more efficient and productive by accepting AI as a partner rather than a competitor trying to replace them; the management should equip the workers with the skills required to use AI effectively to ensure its benefits overshadow the ethical challenges it brings about. To mitigate the ethical difficulties that hinder AI use as an innovative technology, there is a need to have a strategic and creative approach that depicts the advantages of working with machines rather than working against them.
Work Cited
Bankins, Sarah, and Paul Formosa. “The ethical implications of artificial intelligence (AI) for meaningful work.” Journal of Business Ethics (2023): 1-16. https://link.springer.com/article/10.1007/s10551-023-05339-7
Frehywot, Seble, and Yianna Vovides. “An equitable and sustainable community of practice framework to address the use of artificial intelligence for global health workforce training.” Human Resources for Health 21.1 (2023): 45. https://link.springer.com/article/10.1186/s12960-023-00833-5
Safdar, Nabile M., John D. Banja, and Carolyn C. Meltzer. “Ethical considerations in artificial intelligence.” European journal of radiology 122 (2020): 108768. https://www.sciencedirect.com/science/article/pii/S0720048X19304188
Vogel, Kathleen M. “Big data, AI, platforms, and the future of the US intelligence workforce: A research agenda.” IEEE Technology and Society Magazine 40.3 (2021): 84-92. https://ieeexplore.ieee.org/abstract/document/9527344/
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