Resources

Papers

• Longo, L., Brcic, M., Cabitza, F., Choi, J., Confalonieri, R., Del Ser, J., ... & Stumpf, S. (2024). Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions. Information Fusion, 106, 102301.

• Angelopoulos, A. N., & Bates, S. (2023). Conformal prediction: A gentle introduction. Foundations and Trends® in Machine Learning, 16(4), 494-591.

• Narteni, S., Carlevaro, A., Dabbene, F., Muselli, M., Mongelli, M., “CONFIDERAI: CONFormal Interpretable-by-Design score function for Explainable and Reliable Artificial Intelligence” Proceedings of the Twelfth Symposium on Conformal and Probabilistic Prediction with Applications, PMLR 204:485-487, 2023. https://proceedings.mlr.press/v204/narteni23a. html 

• Narteni, S., Carlevaro, A., Guzzi, J., Mongelli, M. (2024). Ensuring Safe Social Navigation via Explainable Probabilistic and Conformal Safety Regions. In: Longo, L., Lapuschkin, S., Seifert, C. (eds) Explainable Artificial Intelligence. xAI 2024. Communications in Computer and Information Science, vol 2156. Springer, Cham. https://doi.org/10.1007/978-3-031-63803-9_22

• Paper Fiorella (tbd)

Standards & guidelines

• High-Level Expert Group on AI. Ethics guidelines for trustworthy AI. Report. Brussels: European Commission, Apr. 2019. https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai 

• Safety Of The Intended Functionality (SOTIF), https://www.iso.org/standard/77490.html

Software

• Explainable Safety Regions: https://github.com/saranrt95/ExplainableSafetyRegions