The 4th Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI)

As computers increasingly make decisions about who gets a loan, a job, or even bail, the expansion of AI algorithms has provoked public concern about ethical issues, and the need to understand what constitutes AI algorithms and how they make decisions becomes ever more pressing. For example, an increasing number of high-profile news reports that widely-used algorithms have unfairly discriminated against some groups of people (e.g., by gender and race) in parole decisions and other major life events. Focusing more attention on ethical bias in learning algorithms is key to unlocking the potential of automated decision systems while ensuring fairness and accountability so that everyone can advance equally in society. Ethical AI has become increasingly important and it has been attracting attention from academia and industry, due to its increased popularity in real-world applications with fairness concerns. It also places fundamental importance on ethical considerations in determining legitimate and illegitimate uses of AI. Organizations that apply ethical AI have clearly stated well-defined review processes to ensure adherence to legal guidelines. Therefore, the wave of research at the intersection of ethical AI in data mining and machine learning has also influenced other fields of science, including computer vision, natural language processing, reinforcement learning, and social science.

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Published
2025-08-03
DOI
https://doi.org/10.1145/3711896.3737859
Primary Topic
Ethics and Social Impacts of AI
Type
article
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article

The 4th Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI)

Haifeng Chen, Xintao Wu, Feng Chen, Chen Zhao
Ethics and Social Impacts of AI
article

The 4th Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI)

Haifeng Chen, Xintao Wu, Feng Chen, Chen Zhao
article en

Abstract

As computers increasingly make decisions about who gets a loan, a job, or even bail, the expansion of AI algorithms has provoked public concern about ethical issues, and the need to understand what constitutes AI algorithms and how they make decisions becomes ever more pressing. For example, an increasing number of high-profile news reports that widely-used algorithms have unfairly discriminated against some groups of people (e.g., by gender and race) in parole decisions and other major life events. Focusing more attention on ethical bias in learning algorithms is key to unlocking the potential of automated decision systems while ensuring fairness and accountability so that everyone can advance equally in society. Ethical AI has become increasingly important and it has been attracting attention from academia and industry, due to its increased popularity in real-world applications with fairness concerns. It also places fundamental importance on ethical considerations in determining legitimate and illegitimate uses of AI. Organizations that apply ethical AI have clearly stated well-defined review processes to ensure adherence to legal guidelines. Therefore, the wave of research at the intersection of ethical AI in data mining and machine learning has also influenced other fields of science, including computer vision, natural language processing, reinforcement learning, and social science.

Baylor University (US), The University of Texas at Dallas (US), Princeton University (US), University of Arkansas at Fayetteville (US)
Openalex Percentile: Top 82%
Ethics and Social Impacts of AI
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The 4th Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI) — Haifeng Chen, Xintao Wu, et al. · (2025) | TGRS Research Map | TGRS