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- W4226304672 abstract "Ttraditional safety engineering is coming to a turning point moving from deterministic, non-evolving systems operating in well-defined contexts to increasingly autonomous and learning-enabled AI systems which are acting in largely unpredictable operating contexts. We outline some of underlying challenges of safe AI and suggest a rigorous engineering framework for minimizing uncertainty, thereby increasing confidence, up to tolerable levels, in the safe behavior of AI systems." @default.
- W4226304672 created "2022-05-05" @default.
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- W4226304672 date "2022-01-25" @default.
- W4226304672 modified "2023-09-26" @default.
- W4226304672 title "Safe AI -- How is this Possible?" @default.
- W4226304672 doi "https://doi.org/10.48550/arxiv.2201.10436" @default.
- W4226304672 hasPublicationYear "2022" @default.
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