{
  "id": "2209.06529",
  "version": "v1",
  "published": "2022-09-14T10:07:44.000Z",
  "updated": "2022-09-14T10:07:44.000Z",
  "title": "Data Privacy and Trustworthy Machine Learning",
  "authors": [
    "Martin Strobel",
    "Reza Shokri"
  ],
  "comment": "Copyright \\copyright 2022, IEEE",
  "journal": "Published in: IEEE Security & Privacy ( Volume: 20, Issue: 5, Sept.-Oct. 2022)",
  "doi": "10.1109/MSEC.2022.3178187",
  "categories": [
    "cs.LG",
    "cs.CR"
  ],
  "abstract": "The privacy risks of machine learning models is a major concern when training them on sensitive and personal data. We discuss the tradeoffs between data privacy and the remaining goals of trustworthy machine learning (notably, fairness, robustness, and explainability).",
  "revisions": [
    {
      "version": "v1",
      "updated": "2022-09-14T10:07:44.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "trustworthy machine learning",
      "data privacy",
      "privacy risks",
      "personal data",
      "machine learning models"
    ],
    "tags": [
      "journal article"
    ],
    "publication": {
      "publisher": "IEEE"
    },
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}