About this Research Topic
Artificial intelligence (AI) has become a ubiquitous presence in our daily lives, and as a result, it is imperative to ensure that AI systems are designed and engineered with fairness in mind. AI is often used in critical environments where it makes decisions that can significantly impact people's lives. Therefore, it is essential to ensure that these decisions are not influenced by any discriminatory behavior towards specific groups or populations.
The primary objective of this Research Topic is to advance the cause of fair AI, with the ultimate goal of enhancing public trust in AI technologies. A critical contribution is to help organizations and individuals assess if their AI applications are fair and ready for deployment. Several countries, including those in Europe and the United States, have introduced comprehensive ethical frameworks for AI, underscoring the importance of fairness in AI. Establishing fairness in AI is crucial to unlocking its full potential and enabling humanity to benefit from its advantages and conveniences.
We welcome submissions (original and review articles) on the following topics, including but not limited to:
• Trustworthy AI Requirements
• Fairness
• Data bias
• Model bias
• Faulty AI
• Explainability
• Acceptance of AI
• Accuracy
• Human Agency and Oversight
• Deep learning
• Machine Learning
The primary objective of this Research Topic is to advance the cause of fair AI, with the ultimate goal of enhancing public trust in AI technologies. A critical contribution is to help organizations and individuals assess if their AI applications are fair and ready for deployment. Several countries, including those in Europe and the United States, have introduced comprehensive ethical frameworks for AI, underscoring the importance of fairness in AI. Establishing fairness in AI is crucial to unlocking its full potential and enabling humanity to benefit from its advantages and conveniences.
We welcome submissions (original and review articles) on the following topics, including but not limited to:
• Trustworthy AI Requirements
• Fairness
• Data bias
• Model bias
• Faulty AI
• Explainability
• Acceptance of AI
• Accuracy
• Human Agency and Oversight
• Deep learning
• Machine Learning
Keywords: Artificial Intelligence, Fairness, Explainability, Accuracy, Human Agency and Oversight
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
