The ethics of artificial intelligence covers a broad range of topics within the field that are considered to have particular ethical stakes. 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.
Some application areas may also have particularly important ethical implications, like healthcare, education, criminal justice, or the military.
AI Ethics refers to the system of moral principles and guidelines that govern the development, deployment, and use of artificial intelligence technologies. It addresses the ethical implications and societal impacts of AI, aiming to ensure that these technologies are developed and implemented in a manner that is beneficial to individuals and society at large. Key considerations in AI Ethics include:
Current ethical frameworks include the European Commission's AI HLEG Guidelines for Trustworthy AI, which emphasizes trustworthiness.
Other terms include Ethical AI, Trustworthy AI, Explainable AI, Interpretable AI, Meaningful AI, and Transparent AI. Implementing ethical AI principles requires alignment with ethical values, data governance principles and education for all stakeholders.