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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, [2] automated decision-making, accountability, privacy, and regulation.
The Pan-Canadian Artificial Intelligence Strategy (2017) is supported by federal funding of Can $125 million with the objectives of increasing the number of outstanding AI researchers and skilled graduates in Canada, establishing nodes of scientific excellence at the three major AI centres, developing 'global thought leadership' on the economic ...
Ethical considerations focus on reducing bias in AI systems, preventing discrimination based on race, gender, or other protected characteristics. By developing fair and accountable AI solutions, engineers contribute to the creation of technologies that are both technically sound and socially responsible.
Technoethics (TE) is an interdisciplinary research area that draws on theories and methods from multiple knowledge domains (such as communications, social sciences, information studies, technology studies, applied ethics, and philosophy) to provide insights on ethical dimensions of technological systems and practices for advancing a technological society.
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. [155]
Artificial intelligence in education (AIEd) [1] is the application of AI in educational settings. The field combines elements of generative AI , data-driven decision-making , AI ethics , data-privacy and AI literacy . [ 2 ]
In order to develop an AI policy report tailored to India and assess the country's AI ecosystem's strengths and future prospects, UNESCO and MeitY began consulting on AI Readiness Assessment Methodology under Safety and Ethics in Artificial Intelligence from 2024. It is to encourage the ethical and responsible use of AI in industries.
The technology adoption lifecycle is a sociological model that describes the adoption or acceptance of a new product or innovation, according to the demographic and psychological characteristics of defined adopter groups. The process of adoption over time is typically illustrated as a classical normal distribution or "bell curve".
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