Introduction
Artificial intelligence (AI) has transformed healthcare, finance, transportation, and entertainment, among other aspects of human lives. Advancements in AI hold great promise for improving efficiency and innovation. However, they raise profound ethical concerns, which must be addressed. AI has the potential to enhance prejudices, infringe on personal privacy, and lack liability, while solutions, such as the use of “human-in-the-loop” systems, setting strict privacy standards, and imposing transparency, must be implemented to address these concerns.
AI and Bias
One of AI’s main concerns is its potential to embed biases. For instance, AI has raised concerns about amplifying societal inequities, such as African Americans being denied loans or receiving longer prison sentences than Caucasians in the United States.1 In this case, AI systems are trained or designed using biased data or algorithms, making unfair or discriminatory decisions toward specific groups of people. To address AI trade-offs, “human-in-the-loop” systems should be used, where a human reviews algorithmic outputs with necessary caveats before making the final choice.2 The system includes human control in AI decision-making, where a special person analyses AI-generated outputs, considers limitations, and makes the last decision. Thus, including human supervision in AI decision-making via “human-in-the-loop” systems can help to reduce the likelihood of AI perpetuating biases.
1. Trishan Panch, Heather Mattie, and Rifat Atun, “Artificial Intelligence and Algorithmic Bias: Implications for Health Systems,” Journal of Global Health 9, no. 2 (2019): 1, https://doi.org/10.7189/jogh.09.020318.
2. Panch, Mattie, and Atun, “Artificial Intelligence,” 3.
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AI Privacy Concerns
Another concern about AI is the potential for it to overstep individual privacy. The Dinerstein v. Google lawsuit and Project Nightingale by Google and Ascension are recent examples of patient privacy concerns in data sharing and AI use.3 The former involves a patient alleging improper sharing of records, while the latter is a data transfer project raising concerns about privacy rights. In solving this matter, AI systems need to adhere to strict privacy standards, while individuals must have control over their data. Therefore, it is crucial to ensure that AI systems comply with rigorous privacy standards, and users must access their data easily to avoid privacy violations.
3. Sara Gerke, Timo Minssen, and Glenn Cohen, “Ethical and Legal Challenges of Artificial Intelligence-Driven Healthcare,” Artificial Intelligence in Healthcare, (2020): 305, https://doi.org/10.1016/B978-0-12-818438-7.00012-5.
Accountability in AI Systems
A third concern about AI is the need for accountability. For example, AI algorithms may make errors in diagnosing and treating patients, and it can be a difficult task to determine who is responsible for these mistakes.4 AI systems’ complexity and involvement of multiple parties, including developers, manufacturers, and users, necessitate accountability mechanisms, such as decision-making transparency and redress avenues for harmed individuals. Hence, implementing accountability mechanisms is vital to address AI errors and ensure their responsible usage.
4. Thomas Davenport and Ravi Kalakota, “The Potential for Artificial Intelligence in Healthcare,” Future Healthcare Journal 6, no. 2 (2019): 97, https://doi.org/10.7861/futurehosp.6-2-94.
Conclusion
AI has transformed many aspects of human daily lives, yet it also presents significant moral dilemmas. These concerns include the possibility of AI when incorporating prejudices, violating personal privacy, and lacking responsibility. In addressing these ethical problems, solutions, such as implementing human-aided computer decision-making, compliance with strict privacy standards, and the assurance of clarity, must be implemented. As a result, people can ensure that AI is developed and utilized ethically by tackling moral issues.
Bibliography
Davenport, Thomas, and Ravi Kalakota. “The Potential for Artificial Intelligence in Healthcare.” Future Healthcare Journal 6, no. 2 (2019): 94–98. https://doi.org/10.7861/futurehosp.6-2-94.
Gerke, Sara, Timo Minssen, and Glenn Cohen. “Ethical and Legal Challenges of Artificial Intelligence-Driven Healthcare.” Artificial Intelligence in Healthcare, (2020): 295–336. https://doi.org/10.1016/B978-0-12-818438-7.00012-5.
Panch, Trishan, Heather Mattie, and Rifat Atun. “Artificial Intelligence and Algorithmic Bias: Implications for Health Systems.” Journal of Global Health 9, no. 2 (2019): 1–5. https://doi.org/10.7189/jogh.09.020318.