AI Ethics
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A AI Ethics is a branch of ethics that deals with the moral implications and responsibilities associated with the development, deployment, and use of artificial intelligence (AI) technologies.
- Context:
- It can range from being an Abstract AI Ethics Framework to a Personal AI Ethics Perspective, reflecting the different levels of theoretical and individual ethical considerations.
- It can range from adopting a Consequentialist AI Ethics Approach, focusing on the outcomes and impacts of AI decisions, to a Deontological AI Ethics Framework, which emphasizes duty and adherence to ethical principles in AI systems.
- It can range from focusing on Applied AI Ethics in real-world contexts, such as healthcare or law, to engaging with Meta-Ethical AI Questions that explore foundational ethical concepts and their relevance to AI.
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- It can examine Ethical Risks associated with AI, including Misinformation, Opinion Manipulation, and Erosion of Trust, proposing Technical and Policy Solutions to mitigate these risks.
- It can emphasize the importance of robust Evaluation Practices for AI systems, covering aspects like Capabilities, Robustness, and Impact.
- It can introduce frameworks for Value Alignment, involving multiple stakeholders such as AI Agents, Users, Developers, and Society.
- It can stress the importance of addressing Well-Being in AI design, leveraging insights from various Disciplines to ensure alignment with user well-being while navigating Technical and Normative Challenges.
- It can guide the development of Ethical AI Design, focusing on creating AI systems that align with human values.
- It can provide frameworks for AI Accountability, ensuring that there are mechanisms for holding AI systems and their developers responsible for their actions.
- It can involve debates on Autonomous Weapon Systems, examining the moral implications of AI in warfare.
- It can call for ongoing Research, Policy Development, and Public Discussion to support the responsible Development and Governance of AI technologies.
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- Example(s):
- AI Ethics in Bias explores the ethical concerns surrounding unfair treatment of certain groups based on biased data in machine learning algorithms.
- AI Ethics in Data Privacy addresses the importance of protecting individual privacy in AI-driven applications and systems.
- AI Ethics in Criminal Justice highlights the ethical implications of using AI for predictive policing, sentencing, and other legal processes.
- AI Ethics in Surveillance examines the balance between security and privacy in AI-driven surveillance technologies.
- AI Ethics in Autonomous Vehicles discusses the ethical dilemmas related to decision-making processes in autonomous vehicles, such as the trolley problem scenarios.
- AI Ethics in Hiring and Employment focuses on fairness and bias issues in AI-driven recruitment processes, ensuring ethical practices in employment.
- AI Ethics and Human Rights considers the broader human rights implications of AI technologies, including access to AI-driven services and the prevention of AI-driven discrimination.
- AI Development Ethics explores the ethical considerations involved in the development and deployment of AI technologies, ensuring they align with societal values.
- AI Ethics in Healthcare focuses on ethical concerns related to decision-making in medical contexts, ensuring that AI systems in healthcare are aligned with patient rights and well-being.
- Human-Like AI Ethics discusses issues like trust, privacy, anthropomorphism, and the moral limits of personalization in AI systems that exhibit human-like characteristics.
- AI Ethics in Social Cooperation examines the impact of AI on social cooperation and coordination, emphasizing the importance of designing technology that remains accessible and considers the needs of diverse users.
- AI Ethics in Autonomous Systems addresses ethical concerns surrounding the autonomous nature of AI systems, such as AI assistants, ensuring they act in ways that are aligned with ethical standards.
- AI Ethics in Environmental Impact considers the ethical implications of the environmental impact of AI, from computational and systemic effects to the role of AI in climate change mitigation efforts.
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- Counter-Example(s):
- AI Governance focuses on the rules, policies, and regulations governing AI rather than the ethical implications.
- Technical Standards that emphasize performance and efficiency without considering ethical implications.
- Business Ethics that primarily deals with corporate conduct and decision-making, which may not always intersect with AI-specific ethical issues.
- Environmental Ethics, which deals with the moral relationship between humans and the environment rather than technology.
- Medical Ethics, which is centered around ethical principles in healthcare rather than technology or AI.
- See: Ethical AI, Responsible AI, AI Governance, AI Safety
References
2024
- (Wikipedia, 2024) ⇒ https://en.wikipedia.org/wiki/Ethics_of_artificial_intelligence Retrieved:2024-8-24.
- The ethics of artificial intelligence covers a broad range of topics within the field that are considered to have particular ethical stakes.[1] This includes algorithmic biases, fairness, automated decision-making, accountability, privacy, and regulation.
It also covers various emerging or potential future challenges such as machine ethics (how to make machines that behave ethically), lethal autonomous weapon systems, arms race dynamics, AI safety and alignment, technological unemployment, AI-enabled misinformation, how to treat certain AI systems if they have a moral status (AI welfare and rights), artificial superintelligence and existential risks.[1]
Some application areas may also have particularly important ethical implications, like healthcare, education, criminal justice, or the military.
- The ethics of artificial intelligence covers a broad range of topics within the field that are considered to have particular ethical stakes.[1] This includes algorithmic biases, fairness, automated decision-making, accountability, privacy, and regulation.
2023
- (Floridi, 2023) ⇒ Luciano Floridi. (2023). “The Ethics of Artificial Intelligence: Principles, Challenges, and Opportunities.” Journal of XXX.
- NOTE: It provides a detailed exploration of the foundational principles and practices essential to the ethical development of AI technologies.
- (Stahl et al., 2023) ⇒ Bernd Carsten Stahl, Doris Schroeder, and Rowena Rodrigues. (2023). "The Ethics of Artificial Intelligence: An Introduction." In *Ethics of Artificial Intelligence*, 1-13. Cham: Springer International Publishing.
- NOTE: It provides a comprehensive introduction to AI ethics, discussing the foundational concepts and issues in the field.
2021
- (Kazim & Koshiyama, 2021a) ⇒ Emre Kazim, and Adriano Soares Koshiyama. (2021). "A High-Level Overview of AI Ethics." Cell Patterns, 2(9) (September 10): 100314. https://doi.org/10.1016/j.patter.2021.100314
- NOTE: This paper provides an overview of AI ethics, covering various approaches and challenges in ensuring ethical AI practices.
2019
- (Pinto dos Santos et al., 2019) ⇒ Daniel Pinto dos Santos, Lukas Giese, Sebastian Brodehl, Sven Hendricks Chon, Wolfgang Buhmann, and Axel Wehrend. (2019). "Medical Students' Attitude towards Artificial Intelligence: A Multicentre Survey." *European Radiology* 29, no. 4 (April): 1640–46. https://doi.org/10.1007/s00330-018-5601-1
- NOTE: This study explores the attitudes of medical students towards AI, providing insights into the ethical considerations of AI in healthcare.