Concern over AI’s effects has led to the emergence of the discipline of artificial intelligence (AI) ethics. It can be viewed as a relatively young field and a subset of the larger field of digital ethics, which deals with issues raised by the creation and application of new digital technologies like blockchain, artificial intelligence, and big data analytics.
What is AI ethics?
The exploration of AI ethics, frequently called machine ethics, represents a novel, interdisciplinary field centered around ethical dilemmas associated with artificial intelligence. The concept of “AI ethics” encompasses the ethical principles that direct the actions of AI systems. AI ethics promotes the development and utilization of AI in manners that enhance societal welfare. It considers a broad spectrum of elements, including fairness, responsibility, openness, confidentiality, safety, and potential societal repercussions.
Why need for AI ethics?
In recent years, there have been numerous cases where AI has produced undesirable outcomes. A notable incident occurred in 2016 when a Tesla driver tragically perished in a traffic accident due to the vehicle’s Autopilot feature failing to recognize an oncoming truck. Microsoft’s AI chatbot, Tay.ai, was taken offline less than a day after its launch on Twitter for displaying racist and misogynistic behavior. Such instances highlight various flaws, fairness issues, biases, privacy concerns, and other ethical dilemmas surrounding AI systems. More alarmingly, criminals have begun exploiting AI technologies for malicious purposes. For example, hackers utilized AI-driven software to imitate a CEO’s voice and fraudulently demanded the transfer of $243,000. Consequently, it is crucial and urgent to address the ethical challenges and risks related to AI to foster its responsible development, application, and creation.
Ethical Issues and Risks of AI
The phrase ‘ethical issues of AI’ generally concerns the morally objectionable or problematic implications associated with AI (i.e., the risks and concerns arising from the creation, deployment, and utilization of AI) that necessitate attention. Various applications and studies have identified multiple ethical issues such as transparency deficits, privacy and accountability concerns, bias and discrimination, safety and security challenges, potential for harmful and illegal activities, and more. Being responsible indicates that the AI system adheres to societal norms and expected obligations.
Yet, determining the degree of autonomy, intention, and accountability an AI system should possess poses a complex question and problem. Designers, software developers, and others involved in AI system creation and usage should receive education on human rights law. Without such training, they risk inadvertently violating fundamental human rights. The public’s trust and acceptance of AI technology will ultimately diminish due to the misrepresentation of reality caused by unethical AI practices.
Principles for AI Ethics
- Transparency: In the discussion over AI ethics, transparency is one of the most talked-about concepts. The two primary components of AI transparency are the technology itself and the openness of its development and implementation. The AI system’s decision-making or behavior, as well as its design and implementation process, must be transparent and logical.
- Objectivity & Justice: In alignment with the principles of justice and equity, AI should be created, executed, and utilized in a manner that is fair and impartial to avert prejudice or discrimination towards particular individuals, communities, or groups.
- Accountability and Responsibility: Creators, programmers, and operators of AI systems are all concerned with the ethical implications of its application, misuse, and behavior, and they hold the ability and responsibility to shape these implications.
- Nonmaleficence: In general, the nonmaleficence concept of AI states that AI systems shouldn’t injure, worsen, or negatively impact people. This includes safeguarding mental and bodily integrity in addition to human dignity.
- Privacy: The privacy principle seeks to guarantee data security and privacy when utilizing AI technologies. AI systems ought to secure and uphold data security, privacy rights, and data protection.
- Beneficence: According to the beneficence principle, AI will help humans and advance humanity. According to this theory, AI technology ought to be applied to improve people’s lives, society, and the environment.
- Freedom and Autonomy: The use of AI must neither impair nor restrict our freedom and autonomy.
- Solidarity: AI systems need to be able to coexist while preserving the boundaries of intergenerational and interpersonal solidarity. In other words, AI shouldn’t endanger social ties and relationships; rather, it should strengthen social stability and cohesiveness.
- Sustainability: According to the sustainability principle, AI development, management, and application must be environmentally friendly and sustainable.
- Trust: Since trust is a fundamental tenet of social interaction and AI adoption, people and societies must be trustworthy before embracing AI.
- Dignity: The dignity of end users or other members of society must not be violated by AI. Therefore, upholding human dignity is a crucial ethical premise that AI ethics should take into account.
Challenges in AI Ethical Guidelines and Principles
There is currently no agreement on the ethics of AI, and it is unclear what universal standards and ideals AI should adhere to. Additionally, when AI is used in various contexts, distinct ethical standards can be needed. Therefore, it is essential and required that the fundamental and universal ethical standards of AI be defined through dialogue and collaboration amongst various organizations, regions, and governments. Each discipline can then refine these ideas further to make them broadly applicable in that particular field based on the fundamental and shared concepts.
References
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature machine intelligence, 1(9), 389-399.
https://www.unesco.org/en/artificial-intelligence/recommendation-ethics
Kazim, E., & Koshiyama, A. S. (2021). A high-level overview of AI ethics. Patterns, 2(9).
Huang, C., Zhang, Z., Mao, B., & Yao, X. (2022). An overview of artificial intelligence ethics. IEEE Transactions on Artificial Intelligence, 4(4), 799-819.
Whittlestone, J., Nyrup, R., Alexandrova, A., & Cave, S. (2019, January). The role and limits of principles in AI ethics: Towards a focus on tensions. In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society (pp. 195-200).
