Summary of The Role Of Xai in Transforming Aeronautics and Aerospace Systems, by Francisco Javier Cantero Zorita et al.
The Role of XAI in Transforming Aeronautics and Aerospace Systems
by Francisco Javier Cantero Zorita, Mikel Galafate, Javier M. Moguerza, Isaac Martín de Diego, M. Teresa Gonzalez, Gema Gutierrez Peña
First submitted to arxiv on: 23 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper reviews Explainable Artificial Intelligence (XAI) and its applications in aeronautics and aerospace. The concept of XAI aims to bridge the gap between professionals and AI systems by providing insights into model predictions. The review defines XAI, its objectives, and the properties required for transparent models. Post-hoc techniques are discussed as means to understand AI systems after training. The paper also highlights various application areas in aeronautics and aerospace where XAI is used to facilitate understanding of AI systems and models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper talks about how we can make AI more understandable, especially for people working in aviation and space. It’s like trying to figure out why a computer program made a certain decision. The paper explains what this “explainable AI” does and how it works. It also looks at different ways to use this technology in these industries. |
