{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreifeahdlu3eqzgwyy4aakjabx74hd52yodzkgu4iqq4m7c4vkrdcdq",
    "uri": "at://did:plc:mxzzpugn7bprjjrszwkbez3u/app.bsky.feed.post/3mikgnvkz5kz2"
  },
  "coverImage": {
    "$type": "blob",
    "ref": {
      "$link": "bafkreiahtv3flhen6qji26qd7i4dbkbaaenoh22awlgg43rzmot54367jq"
    },
    "mimeType": "image/jpeg",
    "size": 769085
  },
  "path": "/news/2026-04-empower-people-ai-expertise-trustworthy.html",
  "publishedAt": "2026-04-02T19:30:02.000Z",
  "site": "https://techxplore.com",
  "tags": [
    "Machine learning & AI"
  ],
  "textContent": "Involving people without AI expertise in the development and evaluation of artificial intelligence applications could help create better, fairer, and more trustworthy automated decision-making systems, new research suggests. After enlisting members of the public to evaluate the potential impacts of two real-world applications, researchers from UK universities will present a paper at a major international computing conference which suggests how \"participatory AI auditing\" could improve AI decision-making in the future.",
  "title": "New research could empower people without AI expertise to help create trustworthy AI applications"
}