Navigating AI Ethics Through the Lens of Personality Traits and Well‐Being: Policy Recommendations for Young People in the UAE

The main purpose of this study is to explore the relationship between HEXACO personality traits and well‐being, using ethical AI as a mediator among young adults in the UAE, aiming to develop policy recommendations that support ethical AI practices in educational settings. Utilizing a quantitative cross‐sectional design, the study involved 204 university students in the UAE, aged 18 and above (M = 23.8, SD = 5.64), with 71 (34.8%) being males and 133 (65.2%) being females. The findings reveal the significant role of AI ethical use in mediating the relationship between certain HEXACO personality traits (honesty–humility, emotionality, and agreeableness) and well‐being. Additionally, well‐being measures (emotional, social, and psychological) are positively correlated with ethical AI engagement. The mediation model showed strong predictive accuracy, particularly for psychological well‐being ( R 2 = 0.503), highlighting the model’s robustness in explaining how ethical AI use enhances the influence of personality traits on well‐being outcomes. The study’s results indicate that fostering responsible AI behavior and utilizing specific personality traits can enhance well‐being, aligning with the UAE’s strategic goals for digital literacy and ethical AI development. These insights inform comprehensive policy recommendations for integrating ethical AI principles into education, ultimately promoting a culture of ethical AI use among young adults and enhancing their well‐being.

Authors

Institutions

Publication Details

Journal
Human Behavior and Emerging Technologies
Published
2025-01-01
DOI
https://doi.org/10.1155/hbe2/5597545
Primary Topic
Personality Traits and Psychology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Navigating AI Ethics Through the Lens of Personality Traits and Well‐Being: Policy Recommendations for Young People in the UAE

Areej ElSayary
Human Behavior and Emerging Technologies
Personality Traits and Psychology
article

Navigating AI Ethics Through the Lens of Personality Traits and Well‐Being: Policy Recommendations for Young People in the UAE

Areej ElSayary
article en

Abstract

The main purpose of this study is to explore the relationship between HEXACO personality traits and well‐being, using ethical AI as a mediator among young adults in the UAE, aiming to develop policy recommendations that support ethical AI practices in educational settings. Utilizing a quantitative cross‐sectional design, the study involved 204 university students in the UAE, aged 18 and above (M = 23.8, SD = 5.64), with 71 (34.8%) being males and 133 (65.2%) being females. The findings reveal the significant role of AI ethical use in mediating the relationship between certain HEXACO personality traits (honesty–humility, emotionality, and agreeableness) and well‐being. Additionally, well‐being measures (emotional, social, and psychological) are positively correlated with ethical AI engagement. The mediation model showed strong predictive accuracy, particularly for psychological well‐being ( R 2 = 0.503), highlighting the model’s robustness in explaining how ethical AI use enhances the influence of personality traits on well‐being outcomes. The study’s results indicate that fostering responsible AI behavior and utilizing specific personality traits can enhance well‐being, aligning with the UAE’s strategic goals for digital literacy and ethical AI development. These insights inform comprehensive policy recommendations for integrating ethical AI principles into education, ultimately promoting a culture of ethical AI use among young adults and enhancing their well‐being.

Human Behavior and Emerging TechnologiesVol. 2025(1)
Zayed University (AE)
Quality Education
Openalex Percentile: Top 71%
Personality Traits and Psychology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.