{
  "version": 1,
  "updatedAt": "2026-08-19",
  "canonicalUrl": "https://cognitive-biases.github.io/research/observatory/",
  "methodology": {
    "purpose": "Generate descriptive research briefs only after a topic has enough comparable repeated observations for a useful longitudinal summary.",
    "comparableSeriesRule": "Trend calculations use only one comparable series at a time: the same provider and sampling mode. Other snapshots remain visible but are excluded from the trend calculation.",
    "minimumComparableSnapshots": 6,
    "minimumTotalHeadlines": 120,
    "minimumHeadlinesPerSnapshot": 10,
    "minimumMedianUniqueDomains": 5,
    "directionThreshold": 0.03,
    "warning": "Brief readiness is a publication rule, not a statistical significance test. Observatory samples are provider search samples rather than probability samples, so the briefs report descriptive changes and do not infer population effects, causality, intent or psychological bias."
  },
  "topics": [
    {
      "slug": "ai-and-work",
      "title": "AI and work",
      "description": "How public coverage frames AI-related jobs, hiring, layoffs, workforce change and labor-market uncertainty.",
      "comparisonKey": "curated-public-metadata-pilot::curated-demonstration",
      "provider": "curated-public-metadata-pilot",
      "samplingMode": "curated-demonstration",
      "briefReady": false,
      "readiness": "insufficient-evidence-window",
      "requirements": {
        "comparableSnapshots": {
          "required": 6,
          "actual": 1,
          "met": false
        },
        "totalHeadlines": {
          "required": 120,
          "actual": 6,
          "met": false
        },
        "headlinesPerSnapshot": {
          "required": 10,
          "met": false
        },
        "medianUniqueDomains": {
          "required": 5,
          "actual": 5,
          "met": true
        }
      },
      "reasons": [
        "comparableSnapshots",
        "totalHeadlines",
        "headlinesPerSnapshot"
      ],
      "coverage": {
        "firstDate": "2026-08-19",
        "latestDate": "2026-08-19",
        "snapshotCount": 1,
        "totalHeadlines": 6,
        "medianUniqueDomains": 5,
        "sourceDiversityStart": 0.833,
        "sourceDiversityLatest": 0.833,
        "sourceDiversitySlope": null,
        "nearDuplicatePairsPerHeadlineStart": 0,
        "nearDuplicatePairsPerHeadlineLatest": 0
      },
      "findings": [],
      "metrics": {},
      "canonicalUrl": null,
      "trendUrl": "https://cognitive-biases.github.io/observatory/topics/ai-and-work/"
    },
    {
      "slug": "ai-and-education",
      "title": "AI and education",
      "description": "How public coverage frames AI in schools, universities, teaching, learning and student work.",
      "comparisonKey": null,
      "provider": null,
      "samplingMode": null,
      "briefReady": false,
      "readiness": "insufficient-evidence-window",
      "requirements": {
        "comparableSnapshots": {
          "required": 6,
          "actual": 0,
          "met": false
        },
        "totalHeadlines": {
          "required": 120,
          "actual": 0,
          "met": false
        },
        "headlinesPerSnapshot": {
          "required": 10,
          "met": false
        },
        "medianUniqueDomains": {
          "required": 5,
          "actual": 0,
          "met": false
        }
      },
      "reasons": [
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        "totalHeadlines",
        "headlinesPerSnapshot",
        "medianUniqueDomains"
      ],
      "coverage": {
        "firstDate": null,
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        "snapshotCount": 0,
        "totalHeadlines": 0,
        "medianUniqueDomains": 0,
        "sourceDiversityStart": null,
        "sourceDiversityLatest": null,
        "sourceDiversitySlope": null,
        "nearDuplicatePairsPerHeadlineStart": null,
        "nearDuplicatePairsPerHeadlineLatest": null
      },
      "findings": [],
      "metrics": {},
      "canonicalUrl": null,
      "trendUrl": "https://cognitive-biases.github.io/observatory/topics/ai-and-education/"
    },
    {
      "slug": "misinformation-and-verification",
      "title": "Misinformation and verification",
      "description": "How public coverage frames misinformation, verification, fact-checking, corrections and uncertain claims.",
      "comparisonKey": null,
      "provider": null,
      "samplingMode": null,
      "briefReady": false,
      "readiness": "insufficient-evidence-window",
      "requirements": {
        "comparableSnapshots": {
          "required": 6,
          "actual": 0,
          "met": false
        },
        "totalHeadlines": {
          "required": 120,
          "actual": 0,
          "met": false
        },
        "headlinesPerSnapshot": {
          "required": 10,
          "met": false
        },
        "medianUniqueDomains": {
          "required": 5,
          "actual": 0,
          "met": false
        }
      },
      "reasons": [
        "comparableSnapshots",
        "totalHeadlines",
        "headlinesPerSnapshot",
        "medianUniqueDomains"
      ],
      "coverage": {
        "firstDate": null,
        "latestDate": null,
        "snapshotCount": 0,
        "totalHeadlines": 0,
        "medianUniqueDomains": 0,
        "sourceDiversityStart": null,
        "sourceDiversityLatest": null,
        "sourceDiversitySlope": null,
        "nearDuplicatePairsPerHeadlineStart": null,
        "nearDuplicatePairsPerHeadlineLatest": null
      },
      "findings": [],
      "metrics": {},
      "canonicalUrl": null,
      "trendUrl": "https://cognitive-biases.github.io/observatory/topics/misinformation-and-verification/"
    },
    {
      "slug": "risk-and-extreme-events",
      "title": "Risk and extreme events",
      "description": "How public coverage of high-impact events uses danger, uncertainty, salience and numerical emphasis.",
      "comparisonKey": null,
      "provider": null,
      "samplingMode": null,
      "briefReady": false,
      "readiness": "insufficient-evidence-window",
      "requirements": {
        "comparableSnapshots": {
          "required": 6,
          "actual": 0,
          "met": false
        },
        "totalHeadlines": {
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          "actual": 0,
          "met": false
        },
        "headlinesPerSnapshot": {
          "required": 10,
          "met": false
        },
        "medianUniqueDomains": {
          "required": 5,
          "actual": 0,
          "met": false
        }
      },
      "reasons": [
        "comparableSnapshots",
        "totalHeadlines",
        "headlinesPerSnapshot",
        "medianUniqueDomains"
      ],
      "coverage": {
        "firstDate": null,
        "latestDate": null,
        "snapshotCount": 0,
        "totalHeadlines": 0,
        "medianUniqueDomains": 0,
        "sourceDiversityStart": null,
        "sourceDiversityLatest": null,
        "sourceDiversitySlope": null,
        "nearDuplicatePairsPerHeadlineStart": null,
        "nearDuplicatePairsPerHeadlineLatest": null
      },
      "findings": [],
      "metrics": {},
      "canonicalUrl": null,
      "trendUrl": "https://cognitive-biases.github.io/observatory/topics/risk-and-extreme-events/"
    }
  ]
}