ML Anthology

In Data We Trust: The Logic of Trust-Based Beliefs

Junli Jiang, Pavel Naumov
IJCAI 2022 pp. 2683-2689
doi:10.24963/IJCAI.2022/372 /ijcai/2022/jiang2022ijcai-data/

Abstract

The paper proposes a data-centred approach to reasoning about the interplay between trust and beliefs. At its core, is the modality "under the assumption that one dataset is trustworthy, another dataset informs a belief in a statement". The main technical result is a sound and complete logical system capturing the properties of this modality.

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Text

Jiang and Naumov. "In Data We Trust: The Logic of Trust-Based Beliefs." International Joint Conference on Artificial Intelligence, 2022. doi:10.24963/IJCAI.2022/372

Markdown

[Jiang and Naumov. "In Data We Trust: The Logic of Trust-Based Beliefs." International Joint Conference on Artificial Intelligence, 2022.](https://mlanthology.org/ijcai/2022/jiang2022ijcai-data/) doi:10.24963/IJCAI.2022/372

BibTeX

@inproceedings{jiang2022ijcai-data,
  title     = {{In Data We Trust: The Logic of Trust-Based Beliefs}},
  author    = {Jiang, Junli and Naumov, Pavel},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2022},
  pages     = {2683-2689},
  doi       = {10.24963/IJCAI.2022/372},
  url       = {https://mlanthology.org/ijcai/2022/jiang2022ijcai-data/}
}