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Information Structures for Causally Explainable Decisions
For an AI agent to make trustworthy decision recommendations under uncertainty on behalf of human principals, it should be able to explain why its recommended decisions make preferred outcomes more likely and what risks they entail. Such rationales use causal models to link potential courses of acti...
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| Pubblicato in: | Entropy (Basel) |
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| Autore principale: | |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI
2021
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8153020/ https://ncbi.nlm.nih.gov/pubmed/34068183 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e23050601 |
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