A Systematic Literature Review on AI Safety: Identifying Trends, Challenges, and Future Directions
Artificial intelligence (AI) is revolutionizing many aspects of our lives, except it raises fundamental safety and ethical issues. In this survey paper, we review the current state of research on safe and trustworthy AI. This work provides a structured and systematic overview of AI safety. In which,...
Saved in:
| Main Authors: | Wissam Salhab, Darine Ameyed, Fehmi Jaafar, Hamid Mcheick |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10630784/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Learning unbiased risk prediction based algorithms in healthcare: A case study with primary care patients
by: Vibhuti Gupta, et al.
Published: (2025-01-01) -
Establishing and evaluating trustworthy AI: overview and research challenges
by: Dominik Kowald, et al.
Published: (2024-11-01) -
Exploration and practice of human-machine trustworthy mechanism in XAI
by: LUO Zhongyan, et al.
Published: (2025-01-01) -
Exploration and practice of human-machine trustworthy mechanism in XAI
by: LUO Zhongyan, et al.
Published: (2025-07-01) -
Metrics and Algorithms for Identifying and Mitigating Bias in AI Design: A Counterfactual Fairness Approach
by: Dongsoo Moon, et al.
Published: (2025-01-01)