{
  "schemaVersion": "2.0",
  "generatedAt": "2026-09-12T13:44:57.274Z",
  "compatibility": {
    "legacyMatterFieldsRetained": true,
    "issueDocumentsAreNotTimelineEvents": true
  },
  "matter": {
    "id": "matter-36",
    "slug": "mobley-v-workday",
    "titleZh": "Mobley 诉 Workday AI 招聘歧视案",
    "formalName": "Mobley v. Workday, Inc.",
    "aliases": [
      "Workday AI discrimination case",
      "Mobley v Workday"
    ],
    "summary": "求职者指控 Workday 的算法筛选工具基于种族、年龄和残障产生歧视。法院认定在特定指控下 Workday 可作为雇主的代理承担联邦反歧视法责任，案件继续推进。",
    "professionalSummary": "3:23-cv-00770-RFL 涉及 Title VII、ADEA 与 ADA；2024 年驳回动议裁定只判断起诉是否充分，不等于已认定算法确有歧视。",
    "whyItMatters": "它测试 AI 招聘供应商能否被视作受规制的就业代理，而非只由采购工具的雇主负责。",
    "status": "active",
    "primaryTopic": "discrimination",
    "secondaryTopics": [
      "automated-decision-making",
      "professional-responsibility"
    ],
    "aiRoles": [
      "automated-decision"
    ],
    "jurisdiction": "美国·联邦·加州北区",
    "industries": [
      "招聘",
      "企业软件"
    ],
    "significance": {
      "legalNovelty": 29,
      "impactScope": 24,
      "institutionalLevel": 17,
      "crossBorder": 3,
      "sustainedCoverage": 15,
      "total": 88
    },
    "highProfile": true,
    "featured": true,
    "firstPublishedAt": "2026-07-15",
    "lastUpdatedAt": "2026-07-16",
    "proceedings": [
      {
        "id": "matter-36:proceeding-1",
        "matterId": "matter-36",
        "formalName": "Mobley v. Workday, Inc.",
        "identifier": "3:23-cv-00770-RFL",
        "identifiers": {
          "docketNumber": "3:23-cv-00770-RFL"
        },
        "forum": "U.S. District Court for the Northern District of California",
        "jurisdiction": "美国·联邦·加州北区",
        "type": "civil-litigation",
        "stage": "class-certification",
        "status": "active",
        "startedAt": "2024-07-12",
        "precedentialWeight": "persuasive",
        "officialUrl": "https://cand.uscourts.gov/cases-e-filing/cases/323-cv-00770-rfl/mobley-v-workday-inc"
      }
    ],
    "events": [
      {
        "id": "matter-36:event-1",
        "matterId": "matter-36",
        "proceedingId": "matter-36:proceeding-1",
        "date": "2024-07-12",
        "type": "order",
        "title": "法院部分拒绝 Workday 的驳回动议",
        "summary": "法院认定原告充分主张 Workday 在特定使用关系中可能属于雇主代理；算法是否实际造成歧视仍待证明。",
        "documentIds": [
          "matter-36:document-1"
        ],
        "claimIds": [
          "matter-36:claim-1",
          "matter-36:claim-procedure",
          "matter-36:claim-event"
        ]
      }
    ],
    "documents": [
      {
        "id": "matter-36:document-1",
        "familyId": "matter-36:family-1",
        "matterId": "matter-36",
        "eventId": "matter-36:event-1",
        "title": "Mobley v. Workday, Inc. — official case page",
        "originalTitle": "Mobley v. Workday, Inc. — official case page",
        "url": "https://cand.uscourts.gov/cases-e-filing/cases/323-cv-00770-rfl/mobley-v-workday-inc",
        "kind": "official-document",
        "sourceId": "cand",
        "publishedAt": "2024-07-12",
        "primaryOrSecondary": "primary",
        "relationship": "independent",
        "identifiers": {
          "docketNumber": "3:23-cv-00770-RFL"
        },
        "language": "en"
      }
    ],
    "claims": [
      {
        "id": "matter-36:claim-1",
        "matterId": "matter-36",
        "eventId": "matter-36:event-1",
        "text": "法院认定原告充分主张 Workday 在特定使用关系中可能属于雇主代理；算法是否实际造成歧视仍待证明。",
        "kind": "legal-holding",
        "status": "confirmed",
        "documentIds": [
          "matter-36:document-1"
        ],
        "asOf": "2024-07-12"
      },
      {
        "id": "matter-36:claim-procedure",
        "matterId": "matter-36",
        "eventId": "matter-36:event-1",
        "text": "3:23-cv-00770-RFL 是本站记录的正式程序编号，程序由 U.S. District Court for the Northern District of California 处理。",
        "kind": "procedural-fact",
        "status": "confirmed",
        "documentIds": [
          "matter-36:document-1"
        ],
        "asOf": "2024-07-12"
      },
      {
        "id": "matter-36:claim-event",
        "matterId": "matter-36",
        "eventId": "matter-36:event-1",
        "text": "2024-07-12，案卷记录“法院部分拒绝 Workday 的驳回动议”这一程序节点；该日期与事件由所引直接材料支持。",
        "kind": "procedural-fact",
        "status": "confirmed",
        "documentIds": [
          "matter-36:document-1"
        ],
        "asOf": "2024-07-12"
      }
    ],
    "caseBackground": {
      "narrativeZh": "求职者 Mobley 指控 Workday 的算法筛选工具基于种族、年龄和残障产生歧视，并依据 Title VII、ADEA 与 ADA 起诉。核心程序问题是向雇主提供筛选工具的 Workday 能否在特定使用关系中被视为雇主的代理；加州北区法院于 2024 年 7 月 12 日部分拒绝驳回。",
      "partiesZh": [
        "原告：Mobley",
        "被告：Workday, Inc."
      ],
      "aiSystemZh": "Workday 算法招聘与求职者筛选工具",
      "challengedConductZh": "使用算法筛选求职申请，并据称基于种族、年龄和残障作出不利筛选。",
      "allegedHarmZh": "Mobley 主张自己遭受自动化拒聘和联邦就业反歧视法所禁止的不利影响。",
      "proceduralOriginZh": "Mobley 在加州北区提起 3:23-cv-00770-RFL；法院处理 Workday 的驳回动议后，案件继续进入集体认证阶段。",
      "claimIds": [
        "matter-36:claim-1",
        "matter-36:claim-procedure",
        "matter-36:claim-event"
      ],
      "documentIds": [
        "matter-36:document-1"
      ]
    },
    "issues": [
      {
        "id": "matter-36:issue-vendor-as-agent",
        "matterId": "matter-36",
        "titleZh": "AI 招聘供应商是否属于雇主代理",
        "questionZh": "Workday 在为客户雇主筛选申请人时，是否可能作为 Title VII、ADEA 和 ADA 下的雇主代理承担责任？",
        "contextZh": "若供应商在筛选过程中实际承担传统雇佣职能，就不能仅凭其技术供应商身份排除责任。",
        "topic": "professional-responsibility",
        "status": "partly-resolved",
        "courtTreatmentZh": "法院认定原告已充分主张 Workday 在特定使用关系中可能属于雇主代理，允许相关请求继续；最终代理关系仍待证明。",
        "claimIds": [
          "matter-36:claim-1"
        ],
        "positions": [
          {
            "id": "matter-36:issue-vendor-as-agent:position-1",
            "issueId": "matter-36:issue-vendor-as-agent",
            "sideZh": "Mobley",
            "positionZh": "主张 Workday 实际参与筛选，承担了客户雇主委托的招聘功能。",
            "claimIds": [],
            "documentIds": []
          },
          {
            "id": "matter-36:issue-vendor-as-agent:position-2",
            "issueId": "matter-36:issue-vendor-as-agent",
            "sideZh": "Workday",
            "positionZh": "通过驳回动议否认其应作为受联邦就业法调整的雇主代理。",
            "claimIds": [],
            "documentIds": []
          }
        ]
      },
      {
        "id": "matter-36:issue-actual-disparate-impact",
        "matterId": "matter-36",
        "titleZh": "算法是否实际造成差别影响",
        "questionZh": "Workday 的筛选工具是否确实对特定种族、年龄或残障群体产生不利影响？",
        "contextZh": "诉状充分性裁定允许案件继续，却不能证明模型已经产生统计或个案层面的歧视。",
        "topic": "discrimination",
        "status": "contested",
        "courtTreatmentZh": "法院没有认定算法实际造成歧视；该事实与因果问题仍待证据和后续程序解决。",
        "claimIds": [
          "matter-36:claim-1"
        ],
        "positions": [
          {
            "id": "matter-36:issue-actual-disparate-impact:position-1",
            "issueId": "matter-36:issue-actual-disparate-impact",
            "sideZh": "Mobley",
            "positionZh": "指控筛选工具基于种族、年龄和残障产生歧视。",
            "claimIds": [
              "matter-36:claim-1"
            ],
            "documentIds": [
              "matter-36:document-1"
            ]
          },
          {
            "id": "matter-36:issue-actual-disparate-impact:position-2",
            "issueId": "matter-36:issue-actual-disparate-impact",
            "sideZh": "Workday",
            "positionZh": "反对相关请求；底库未收录其对模型实际影响的完整证据。",
            "claimIds": [],
            "documentIds": []
          }
        ]
      },
      {
        "id": "matter-36:issue-multi-statute-coverage",
        "matterId": "matter-36",
        "titleZh": "同一筛选系统下多部反歧视法的适用",
        "questionZh": "同一算法筛选流程能否同时触发 Title VII、ADEA 和 ADA 的不同保护？",
        "contextZh": "三部法律分别保护种族、年龄和残障利益，但都要求把被诉筛选行为与法律所调整的雇佣关系连接。",
        "topic": "discrimination",
        "status": "open",
        "claimIds": [],
        "positions": [
          {
            "id": "matter-36:issue-multi-statute-coverage:position-1",
            "issueId": "matter-36:issue-multi-statute-coverage",
            "sideZh": "Mobley",
            "positionZh": "依据三部联邦就业法挑战同一算法筛选实践。",
            "claimIds": [],
            "documentIds": []
          },
          {
            "id": "matter-36:issue-multi-statute-coverage:position-2",
            "issueId": "matter-36:issue-multi-statute-coverage",
            "sideZh": "Workday",
            "positionZh": "要求在诉状阶段排除相关请求中的部分内容。",
            "claimIds": [],
            "documentIds": []
          }
        ]
      }
    ],
    "decisions": [
      {
        "id": "matter-36:decision-1",
        "matterId": "matter-36",
        "proceedingId": "matter-36:proceeding-1",
        "eventId": "matter-36:event-1",
        "date": "2024-07-12",
        "outcomeZh": "加州北区法院部分拒绝 Workday 的驳回动议，认定原告已充分主张 Workday 在特定关系中可能作为雇主代理。",
        "holdingsZh": [
          "AI 招聘供应商并非仅因其技术供应商身份就当然排除于联邦就业反歧视法之外。",
          "当前诉状足以支持 Workday 可能承担雇主代理角色的推论。",
          "算法是否实际造成种族、年龄或残障歧视仍未得到事实认定。"
        ],
        "reasoningZh": [
          "责任范围取决于供应商在客户招聘过程中实际承担的职能，而不是合同标签。",
          "驳回阶段接受充分陈述的事实用于判断请求能否继续，不替代证据开示和最终证明。"
        ],
        "reliefZh": "命令只保留部分请求继续审理，没有判给损害赔偿、集体救济或永久禁令。",
        "scopeAndLimitsZh": "裁定限于诉状充分性和潜在代理关系，不是对 Workday 算法存在歧视的实体认定。",
        "precedentialWeight": "persuasive",
        "appealStatusZh": "2024 年 7 月 12 日命令不是终局判决，案件仍在加州北区的集体认证阶段；底库未记录终局上诉裁判。",
        "documentIds": [
          "matter-36:document-1"
        ],
        "claimIds": [
          "matter-36:claim-1"
        ]
      }
    ],
    "issueDocumentLinks": [
      {
        "id": "issue-document-matter-36-matter-36:issue-actual-disparate-impact-knowledge-big-data-disparate-impact",
        "matterId": "matter-36",
        "issueId": "matter-36:issue-actual-disparate-impact",
        "documentId": "knowledge-big-data-disparate-impact",
        "relationship": "doctrinal-context",
        "relevanceSummaryZh": "解释没有主观歧视意图的模型为何仍可能复制结构性差异，以及现有差别影响 doctrine 的适用困难。 本次规则匹配仅使用本争点文本及其引用主张，命中 2 个确定性争点词；AI 作用分面只用于候选召回。",
        "viewpoint": "critical",
        "confidence": 0.9,
        "assignedBy": "rule"
      },
      {
        "id": "news-context-link-matter-36-matter-36:issue-actual-disparate-impact-news-context-hiring-systemic-rejection",
        "matterId": "matter-36",
        "issueId": "matter-36:issue-actual-disparate-impact",
        "documentId": "news-context-hiring-systemic-rejection",
        "relationship": "news-context",
        "relevanceSummaryZh": "以真实招聘部署说明供应商跨雇主筛选、岗位级差别影响和算法单一化如何产生系统性拒绝，同时明确不能外推为个案事实。 本次规则匹配仅使用本争点文本及其引用主张，命中 2 个确定性争点词。",
        "viewpoint": "critical",
        "confidence": 0.9,
        "assignedBy": "rule"
      },
      {
        "id": "issue-document-matter-36-matter-36:issue-multi-statute-coverage-knowledge-big-data-disparate-impact",
        "matterId": "matter-36",
        "issueId": "matter-36:issue-multi-statute-coverage",
        "documentId": "knowledge-big-data-disparate-impact",
        "relationship": "doctrinal-context",
        "relevanceSummaryZh": "解释没有主观歧视意图的模型为何仍可能复制结构性差异，以及现有差别影响 doctrine 的适用困难。 本次规则匹配仅使用本争点文本及其引用主张，命中 1 个确定性争点词；AI 作用分面只用于候选召回。",
        "viewpoint": "critical",
        "confidence": 0.8500000000000001,
        "assignedBy": "rule"
      },
      {
        "id": "issue-document-matter-36-matter-36:issue-multi-statute-coverage-knowledge-fairness-abstraction",
        "matterId": "matter-36",
        "issueId": "matter-36:issue-multi-statute-coverage",
        "documentId": "knowledge-fairness-abstraction",
        "relationship": "technical-context",
        "relevanceSummaryZh": "提醒案件中的公平指标必须放回招聘、信贷、住房或刑事司法的制度流程中评价。 本次规则匹配仅使用本争点文本及其引用主张，命中 1 个确定性争点词；AI 作用分面只用于候选召回。",
        "viewpoint": "critical",
        "confidence": 0.8500000000000001,
        "assignedBy": "rule"
      },
      {
        "id": "news-context-link-matter-36-matter-36:issue-multi-statute-coverage-news-context-hiring-systemic-rejection",
        "matterId": "matter-36",
        "issueId": "matter-36:issue-multi-statute-coverage",
        "documentId": "news-context-hiring-systemic-rejection",
        "relationship": "news-context",
        "relevanceSummaryZh": "以真实招聘部署说明供应商跨雇主筛选、岗位级差别影响和算法单一化如何产生系统性拒绝，同时明确不能外推为个案事实。 本次规则匹配仅使用本争点文本及其引用主张，命中 3 个确定性争点词。",
        "viewpoint": "critical",
        "confidence": 0.95,
        "assignedBy": "rule"
      }
    ]
  },
  "issueDocuments": [
    {
      "link": {
        "id": "issue-document-matter-36-matter-36:issue-actual-disparate-impact-knowledge-big-data-disparate-impact",
        "matterId": "matter-36",
        "issueId": "matter-36:issue-actual-disparate-impact",
        "documentId": "knowledge-big-data-disparate-impact",
        "relationship": "doctrinal-context",
        "relevanceSummaryZh": "解释没有主观歧视意图的模型为何仍可能复制结构性差异，以及现有差别影响 doctrine 的适用困难。 本次规则匹配仅使用本争点文本及其引用主张，命中 2 个确定性争点词；AI 作用分面只用于候选召回。",
        "viewpoint": "critical",
        "confidence": 0.9,
        "assignedBy": "rule"
      },
      "document": {
        "id": "knowledge-big-data-disparate-impact",
        "familyId": "knowledge-family-big-data-disparate-impact",
        "title": "大数据的差别影响",
        "originalTitle": "Big Data’s Disparate Impact",
        "url": "https://doi.org/10.15779/Z38BG31",
        "kind": "academic-research",
        "sourceId": "california-law-review",
        "publishedAt": "2016-06",
        "author": "Solon Barocas; Andrew D. Selbst",
        "primaryOrSecondary": "secondary",
        "relationship": "independent",
        "identifiers": {
          "doi": "10.15779/Z38BG31"
        },
        "language": "en",
        "metadata": {
          "abstractZh": "说明数据挖掘即使没有歧视意图，也可能从历史数据、代理变量和既有排斥结构中产生差别影响，并检验传统反歧视法能否识别和救济这些机制。",
          "venue": "California Law Review 104(3): 671–732",
          "publisher": "California Law Review",
          "publicationState": "published",
          "peerReviewed": false,
          "paywalled": false
        },
        "stableIdentifier": {
          "kind": "doi",
          "value": "10.15779/Z38BG31"
        },
        "legalTopics": [
          "discrimination",
          "automated-decision-making"
        ],
        "aiRoles": [
          "training-data",
          "automated-decision"
        ]
      }
    },
    {
      "link": {
        "id": "news-context-link-matter-36-matter-36:issue-actual-disparate-impact-news-context-hiring-systemic-rejection",
        "matterId": "matter-36",
        "issueId": "matter-36:issue-actual-disparate-impact",
        "documentId": "news-context-hiring-systemic-rejection",
        "relationship": "news-context",
        "relevanceSummaryZh": "以真实招聘部署说明供应商跨雇主筛选、岗位级差别影响和算法单一化如何产生系统性拒绝，同时明确不能外推为个案事实。 本次规则匹配仅使用本争点文本及其引用主张，命中 2 个确定性争点词。",
        "viewpoint": "critical",
        "confidence": 0.9,
        "assignedBy": "rule"
      },
      "document": {
        "id": "news-context-hiring-systemic-rejection",
        "familyId": "news-family-hiring-systemic-rejection",
        "title": "AI 招聘工具可能造成种族偏差与系统性拒绝",
        "originalTitle": "AI Hiring Tools Can Yield Racial Bias and Systemic Rejection",
        "url": "https://hai.stanford.edu/news/ai-hiring-tools-can-yield-racial-bias-and-systemic-rejection",
        "kind": "factual-report",
        "sourceId": "stanford-hai",
        "publishedAt": "2026-05-26",
        "author": "Rishi Bommasani; Sarah H. Bana; Kathleen A. Creel; Dan Jurafsky; Percy Liang",
        "primaryOrSecondary": "secondary",
        "relationship": "independent",
        "identifiers": {},
        "language": "en",
        "metadata": {
          "abstractZh": "机构报道介绍一项对 340 万名求职者、400 万份申请和 150 家雇主的实证研究，显示按岗位评估时会暴露被总体平均掩盖的差别影响，并讨论多家雇主依赖同一供应商造成的系统性拒绝。",
          "venue": "Stanford HAI News",
          "publisher": "Stanford Institute for Human-Centered Artificial Intelligence",
          "publicationState": "published",
          "peerReviewed": false,
          "paywalled": false
        },
        "editorialSummaryZh": "该报道把单一 AI 招聘供应商跨雇主部署与岗位级差别影响联系起来，能为供应商控制力和实际歧视证据提供实证背景；它不证明 Workday 本案产品具有同样结果。",
        "legalTopics": [
          "discrimination",
          "automated-decision-making"
        ],
        "aiRoles": [
          "automated-decision"
        ]
      }
    },
    {
      "link": {
        "id": "issue-document-matter-36-matter-36:issue-multi-statute-coverage-knowledge-big-data-disparate-impact",
        "matterId": "matter-36",
        "issueId": "matter-36:issue-multi-statute-coverage",
        "documentId": "knowledge-big-data-disparate-impact",
        "relationship": "doctrinal-context",
        "relevanceSummaryZh": "解释没有主观歧视意图的模型为何仍可能复制结构性差异，以及现有差别影响 doctrine 的适用困难。 本次规则匹配仅使用本争点文本及其引用主张，命中 1 个确定性争点词；AI 作用分面只用于候选召回。",
        "viewpoint": "critical",
        "confidence": 0.8500000000000001,
        "assignedBy": "rule"
      },
      "document": {
        "id": "knowledge-big-data-disparate-impact",
        "familyId": "knowledge-family-big-data-disparate-impact",
        "title": "大数据的差别影响",
        "originalTitle": "Big Data’s Disparate Impact",
        "url": "https://doi.org/10.15779/Z38BG31",
        "kind": "academic-research",
        "sourceId": "california-law-review",
        "publishedAt": "2016-06",
        "author": "Solon Barocas; Andrew D. Selbst",
        "primaryOrSecondary": "secondary",
        "relationship": "independent",
        "identifiers": {
          "doi": "10.15779/Z38BG31"
        },
        "language": "en",
        "metadata": {
          "abstractZh": "说明数据挖掘即使没有歧视意图，也可能从历史数据、代理变量和既有排斥结构中产生差别影响，并检验传统反歧视法能否识别和救济这些机制。",
          "venue": "California Law Review 104(3): 671–732",
          "publisher": "California Law Review",
          "publicationState": "published",
          "peerReviewed": false,
          "paywalled": false
        },
        "stableIdentifier": {
          "kind": "doi",
          "value": "10.15779/Z38BG31"
        },
        "legalTopics": [
          "discrimination",
          "automated-decision-making"
        ],
        "aiRoles": [
          "training-data",
          "automated-decision"
        ]
      }
    },
    {
      "link": {
        "id": "issue-document-matter-36-matter-36:issue-multi-statute-coverage-knowledge-fairness-abstraction",
        "matterId": "matter-36",
        "issueId": "matter-36:issue-multi-statute-coverage",
        "documentId": "knowledge-fairness-abstraction",
        "relationship": "technical-context",
        "relevanceSummaryZh": "提醒案件中的公平指标必须放回招聘、信贷、住房或刑事司法的制度流程中评价。 本次规则匹配仅使用本争点文本及其引用主张，命中 1 个确定性争点词；AI 作用分面只用于候选召回。",
        "viewpoint": "critical",
        "confidence": 0.8500000000000001,
        "assignedBy": "rule"
      },
      "document": {
        "id": "knowledge-fairness-abstraction",
        "familyId": "knowledge-family-fairness-abstraction",
        "title": "社会技术系统中的公平与抽象",
        "originalTitle": "Fairness and Abstraction in Sociotechnical Systems",
        "url": "https://doi.org/10.1145/3287560.3287598",
        "kind": "academic-research",
        "sourceId": "acm-facct",
        "publishedAt": "2019-01-29",
        "author": "Andrew D. Selbst; danah boyd; Sorelle A. Friedler; Suresh Venkatasubramanian; Janet Vertesi",
        "primaryOrSecondary": "secondary",
        "relationship": "independent",
        "identifiers": {
          "doi": "10.1145/3287560.3287598"
        },
        "language": "en",
        "metadata": {
          "abstractZh": "提出公平机器学习常见的五种抽象陷阱，警告把社会、组织和制度背景排除在系统边界之外，会让形式上的公平修正失效甚至误导。",
          "venue": "Proceedings of FAT* 2019: 59–68",
          "publisher": "Association for Computing Machinery",
          "publicationState": "published",
          "peerReviewed": true,
          "paywalled": true
        },
        "stableIdentifier": {
          "kind": "doi",
          "value": "10.1145/3287560.3287598"
        },
        "legalTopics": [
          "discrimination",
          "automated-decision-making"
        ],
        "aiRoles": [
          "training-data",
          "automated-decision"
        ]
      }
    },
    {
      "link": {
        "id": "news-context-link-matter-36-matter-36:issue-multi-statute-coverage-news-context-hiring-systemic-rejection",
        "matterId": "matter-36",
        "issueId": "matter-36:issue-multi-statute-coverage",
        "documentId": "news-context-hiring-systemic-rejection",
        "relationship": "news-context",
        "relevanceSummaryZh": "以真实招聘部署说明供应商跨雇主筛选、岗位级差别影响和算法单一化如何产生系统性拒绝，同时明确不能外推为个案事实。 本次规则匹配仅使用本争点文本及其引用主张，命中 3 个确定性争点词。",
        "viewpoint": "critical",
        "confidence": 0.95,
        "assignedBy": "rule"
      },
      "document": {
        "id": "news-context-hiring-systemic-rejection",
        "familyId": "news-family-hiring-systemic-rejection",
        "title": "AI 招聘工具可能造成种族偏差与系统性拒绝",
        "originalTitle": "AI Hiring Tools Can Yield Racial Bias and Systemic Rejection",
        "url": "https://hai.stanford.edu/news/ai-hiring-tools-can-yield-racial-bias-and-systemic-rejection",
        "kind": "factual-report",
        "sourceId": "stanford-hai",
        "publishedAt": "2026-05-26",
        "author": "Rishi Bommasani; Sarah H. Bana; Kathleen A. Creel; Dan Jurafsky; Percy Liang",
        "primaryOrSecondary": "secondary",
        "relationship": "independent",
        "identifiers": {},
        "language": "en",
        "metadata": {
          "abstractZh": "机构报道介绍一项对 340 万名求职者、400 万份申请和 150 家雇主的实证研究，显示按岗位评估时会暴露被总体平均掩盖的差别影响，并讨论多家雇主依赖同一供应商造成的系统性拒绝。",
          "venue": "Stanford HAI News",
          "publisher": "Stanford Institute for Human-Centered Artificial Intelligence",
          "publicationState": "published",
          "peerReviewed": false,
          "paywalled": false
        },
        "editorialSummaryZh": "该报道把单一 AI 招聘供应商跨雇主部署与岗位级差别影响联系起来，能为供应商控制力和实际歧视证据提供实证背景；它不证明 Workday 本案产品具有同样结果。",
        "legalTopics": [
          "discrimination",
          "automated-decision-making"
        ],
        "aiRoles": [
          "automated-decision"
        ]
      }
    }
  ],
  "sources": [
    {
      "id": "cand",
      "slug": "cand",
      "name": "U.S. District Court, Northern District of California",
      "homepage": "https://cand.uscourts.gov/",
      "type": "court",
      "grade": "A",
      "primaryOrSecondary": "primary",
      "score": {
        "traceability": 25,
        "corrections": 18,
        "ownershipTransparency": 20,
        "expertise": 20,
        "historicalAccuracy": 15,
        "total": 98
      },
      "rationale": "法院、政府或监管机构自有发布渠道；程序状态以其正式文书与登记信息为准。",
      "methodologyVersion": "1.0",
      "reviewedAt": "2026-07-15"
    },
    {
      "id": "california-law-review",
      "slug": "california-law-review",
      "name": "California Law Review",
      "homepage": "https://www.californialawreview.org/",
      "type": "academic",
      "primaryOrSecondary": "secondary",
      "rationale": "学生编辑法学评论，文章具有作者、卷期、页码和稳定 DOI；观点不作为案件事实。",
      "grade": "A",
      "score": {
        "traceability": 25,
        "corrections": 16,
        "ownershipTransparency": 19,
        "expertise": 18,
        "historicalAccuracy": 12,
        "total": 90
      },
      "methodologyVersion": "1.0",
      "reviewedAt": "2026-07-16"
    },
    {
      "id": "stanford-hai",
      "slug": "stanford-hai",
      "name": "Stanford Institute for Human-Centered Artificial Intelligence",
      "homepage": "https://hai.stanford.edu/",
      "type": "academic",
      "primaryOrSecondary": "mixed",
      "rationale": "大学研究机构发布研究、政策简报与新闻；按具体作者和文类区分一手研究与机构评论。",
      "grade": "A",
      "score": {
        "traceability": 23,
        "corrections": 16,
        "ownershipTransparency": 19,
        "expertise": 20,
        "historicalAccuracy": 12,
        "total": 90
      },
      "methodologyVersion": "1.0",
      "reviewedAt": "2026-07-16",
      "ingestion": {
        "feedEnabled": false,
        "feedUrl": null,
        "verification": "not-verified",
        "allowedUse": "discovery-metadata-and-deep-links"
      }
    },
    {
      "id": "acm-facct",
      "slug": "acm-facct",
      "name": "ACM Conference on Fairness, Accountability, and Transparency",
      "homepage": "https://facctconference.org/",
      "type": "academic",
      "primaryOrSecondary": "secondary",
      "rationale": "同行评审会议论文集，由 ACM 提供 DOI、作者、会议和版本记录。",
      "grade": "A",
      "score": {
        "traceability": 25,
        "corrections": 18,
        "ownershipTransparency": 19,
        "expertise": 20,
        "historicalAccuracy": 14,
        "total": 96
      },
      "methodologyVersion": "1.0",
      "reviewedAt": "2026-07-16"
    }
  ],
  "canonicalUrl": "/cases/mobley-v-workday"
}