Explainable Reinforcement Learning for assisting Air Traffic Controllers
To effectively integrate AI into high-stakes, critical environments such as healthcare, autonomous driving, and aviation--and to advance toward higher levels of automation and seamless human-AI collaboration--building trust in AI-driven solutions is essential. Trust, in turn, is closely linked to the explainability of AI systems. The rapid advancements in AI across various domains have underscored the challenges of establishing trust, raising increasing interest in AI explainability even more wh
Record details
Published: 24 July 2026
Source: arXiv cs.AI
Category: Research
Topics: Jobs & economy · Healthcare · Transparency · Environment
Retrieved: 27 July 2026
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How to cite this record
ethics.ai (24 July 2026), “Explainable Reinforcement Learning for assisting Air Traffic Controllers,” evidence record 13686, https://ethics.ai/record/13686 (originally published by arXiv cs.AI).
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