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Machine ethics. Machine ethics (or machine morality) is the field of research concerned with designing Artificial Moral Agents (AMAs), robots or artificially intelligent computers that behave morally or as though moral. [2][3][4][5] To account for the nature of these agents, it has been suggested to consider certain philosophical ideas, like ...
Regulation of artificial intelligence is the development of public sector policies and laws for promoting and regulating artificial intelligence (AI). It is part of the broader regulation of algorithms. [1][2] The regulatory and policy landscape for AI is an emerging issue in jurisdictions worldwide, including for international organizations ...
The popularization of generative artificial intelligence apps in education prompted global reconsiderations of policies and procedures relating to plagiarism and other breaches of academic integrity [25] [26] [27]. The impact of large language models (LLMs) has impacted discussions of plagiarism and what constitutes ethical student learning.
A study of 84 policy guidelines on ethical AI found that fairness and "mitigation of unwanted bias" was a common point of concern, and were addressed through a blend of technical solutions, transparency and monitoring, right to remedy and increased oversight, and diversity and inclusion efforts. [143]
Computer ethics is a part of practical philosophy concerned with how computing professionals should make decisions regarding professional and social conduct. [1]Margaret Anne Pierce, a professor in the Department of Mathematics and Computers at Georgia Southern University has categorized the ethical decisions related to computer technology and usage into three primary influences: [2]
Information ethics has been defined as "the branch of ethics that focuses on the relationship between the creation, organization, dissemination, and use of information, and the ethical standards and moral codes governing human conduct in society". [1] It examines the morality that comes from information as a resource, a product, or as a target. [2]
The Artificial Intelligence Act (AI Act) [a] is a European Union regulation concerning artificial intelligence (AI). It establishes a common regulatory and legal framework for AI within the European Union (EU). [1] It came into force on 1 August 2024, [2] with provisions coming into operation gradually over the following 6 to 36 months.
Fairness in machine learning refers to the various attempts at correcting algorithmic bias in automated decision processes based on machine learning models. Decisions made by computers after a machine-learning process may be considered unfair if they were based on variables considered sensitive. For example gender, ethnicity, sexual orientation ...