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Academic Publication Ethical and Bias Considerations in Artificial Intelligence/Machine Learning
Correlated Market Trend: Adaptive Learning
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Ethical and Bias Considerations in Artificial Intelligence/Machine Learning
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The effects of over-reliance on AI dialogue systems on students' cognitive abilities: a systematic review
AbstractThe growing integration of artificial intelligence (AI) dialogue systems within educational and research settings highlights the importance of learning aids. Despite examination of the ethi...
Transparency and accountability in AI systems: safeguarding wellbeing in the age of algorithmic decision-making
The rapid integration of artificial intelligence (AI) systems into various domains has raised concerns about their impact on individual and societal wellbeing, particularly due to the lack of trans...
Exploring the impact of artificial intelligence on higher education: The dynamics of ethical, social, and educational implications
AbstractThe increasing prevalence of Artificial Intelligence (AI) in higher education underscores the necessity to explore its implications on ethical, social, and educational dynamics within the s...
Fairness in Machine Learning: A Survey
When Machine Learning technologies are used in contexts that affect citizens, companies as well as researchers need to be confident that there will not be any unexpected social implications, such a...
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