Towards Explainable Public Sector AI: An Exploration of Neuro-Symbolic AI and Enterprise Modeling (Short Paper)
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-61003-5_10
Reference22 articles.
1. Di Vaio, A., Hassan, R., Alavoine, C.: Data intelligence and analytics: A bibliometric analysis of human–Artificial intelligence in public sector decision-making effectiveness. Technological Forecasting and Social Change. 174, (2022). https://doi.org/10.1016/j.techfore.2021.121201
2. van Noordt, C., Misuraca, G.: Artificial intelligence for the public sector: results of landscaping the use of AI in government across the European Union. Gov. Inf. Q. 39, 101714 (2022). https://doi.org/10.1016/j.giq.2022.101714
3. Mehdiyev, N., Houy, C., Gutermuth, O., Mayer, L., Fettke, P.: Explainable Artificial Intelligence (XAI) Supporting Public Administration Processes – On the Potential of XAI in Tax Audit Processes. In: Ahlemann, F., Schütte, R., and Stieglitz, S. (eds.) Innovation Through Information Systems. pp. 413–428. Springer International Publishing, Cham (2021). https://doi.org/10.1007/978-3-030-86790-4_28
4. Leaver, T., Srdarov, S.: ChatGPT Isn’t Magic: The Hype and Hypocrisy of Generative Artificial Intelligence (AI) Rhetoric. M/C J. 26, (2023). https://doi.org/10.5204/mcj.3004
5. Jobin, A., Ienca, M., Vayena, E.: The global landscape of AI ethics guidelines. Nat Mach Intell. 1, 389–399 (2019). https://doi.org/10.1038/s42256-019-0088-2
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