The Ethics of AI Decision-Making: Balancing Automation, Explainable AI, and Human Oversight

Artificial Intelligence (AI) has become an integral part of decision-making processes across various sectors, including healthcare, finance, criminal justice, and autonomous vehicles. While AI offers significant advantages in terms of efficiency, accuracy, and scalability, it also raises critical ethical concerns, particularly regarding the balance between automation and human oversight. This research article explores the ethical implications of AI-driven decision-making, focusing on the need for a balanced approach that leverages the strengths of both AI and human judgment. We present a detailed analysis of the ethical challenges, propose a framework for balancing automation and human oversight, and provide empirical data to support our arguments. The findings suggest that a hybrid model combining AI automation with human oversight is essential to ensure fairness, transparency, and accountability in AI-driven decisions.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-30
DOI
https://doi.org/10.5281/zenodo.17007842
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

The Ethics of AI Decision-Making: Balancing Automation, Explainable AI, and Human Oversight

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

The Ethics of AI Decision-Making: Balancing Automation, Explainable AI, and Human Oversight

article en

Abstract

Artificial Intelligence (AI) has become an integral part of decision-making processes across various sectors, including healthcare, finance, criminal justice, and autonomous vehicles. While AI offers significant advantages in terms of efficiency, accuracy, and scalability, it also raises critical ethical concerns, particularly regarding the balance between automation and human oversight. This research article explores the ethical implications of AI-driven decision-making, focusing on the need for a balanced approach that leverages the strengths of both AI and human judgment. We present a detailed analysis of the ethical challenges, propose a framework for balancing automation and human oversight, and provide empirical data to support our arguments. The findings suggest that a hybrid model combining AI automation with human oversight is essential to ensure fairness, transparency, and accountability in AI-driven decisions.

Zenodo (CERN European Organization for Nuclear Research)
Lamar University (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 58%
Geochemistry and Geologic Mapping
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