{"apiVersion":"v1","generatedAt":"2026-05-12T01:18:37.003Z","canonicalUrl":"https://eduaipolicy.org/universities/cornell-university","license":"CC-BY-4.0","trackerMetadataLicense":"CC-BY-4.0","sourcePolicy":"Tracker metadata is open licensed. Official source documents, page text, PDFs, and other source materials retain their original rights and terms.","sourceRightsPolicy":"Tracker metadata is open licensed. Official source documents, page text, PDFs, and other source materials retain their original rights and terms.","limitations":["Policy analysis profiles are deterministic summaries of public tracker claims and are not final policy conclusions.","Policy Coverage Score measures breadth of public, source-backed coverage; it is not a policy quality score, strictness score, legal adequacy score, safety score, or institutional compliance score.","This tracker is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page."],"citation":{"citationTitle":"Cornell University policy analysis profile","canonicalUrl":"https://eduaipolicy.org/universities/cornell-university","publicJsonUrl":"https://eduaipolicy.org/api/public/v1/analysis/universities/cornell-university.json","suggestedCitation":"University AI Policy Tracker. \"Cornell University policy analysis profile.\" Version v1. https://eduaipolicy.org/universities/cornell-university","sourceRightsPolicy":"Tracker metadata is open licensed. Official source documents, page text, PDFs, and other source materials retain their original rights and terms."},"data":{"schemaVersion":"uapt-policy-analysis-v1","apiVersion":"v1","entityType":"university","entitySlug":"cornell-university","entityName":"Cornell University","canonicalUrl":"https://eduaipolicy.org/universities/cornell-university","publicJsonUrl":"https://eduaipolicy.org/api/public/v1/analysis/universities/cornell-university.json","generatedAt":"2026-05-06T06:15:00.000Z","basedOnClaimIds":["claim-cornell-university-1","claim-cornell-university-10","claim-cornell-university-11","claim-cornell-university-12","claim-cornell-university-13","claim-cornell-university-14","claim-cornell-university-15","claim-cornell-university-16","claim-cornell-university-17","claim-cornell-university-19","claim-cornell-university-2","claim-cornell-university-20","claim-cornell-university-21","claim-cornell-university-25","claim-cornell-university-4","claim-cornell-university-5","claim-cornell-university-7"],"basedOnSourceUrls":["https://it.cornell.edu/ai-strategy/ai-guidelines","https://teaching.cornell.edu/generative-artificial-intelligence","https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","https://teaching.cornell.edu/generative-artificial-intelligence/ai-course-policy-icons","https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education"],"sourceLanguages":["en"],"reviewState":"machine_candidate","confidence":0.799,"coverageScore":{"score":90,"maxScore":100,"label":"broad_public_coverage","components":[{"key":"policy_presence","label":"Central AI policy or guidance source exists","points":15,"maxPoints":15,"status":"unclear","evidenceClaimIds":["claim-cornell-university-16","claim-cornell-university-2","claim-cornell-university-20","claim-cornell-university-25","claim-cornell-university-10"],"reviewState":"machine_candidate"},{"key":"academic_integrity","label":"Academic integrity guidance","points":15,"maxPoints":15,"status":"restricted","evidenceClaimIds":["claim-cornell-university-17","claim-cornell-university-4","claim-cornell-university-7","claim-cornell-university-15","claim-cornell-university-11"],"reviewState":"machine_candidate"},{"key":"ai_disclosure","label":"AI disclosure guidance","points":15,"maxPoints":15,"status":"required","evidenceClaimIds":["claim-cornell-university-16","claim-cornell-university-7","claim-cornell-university-15","claim-cornell-university-20","claim-cornell-university-5"],"reviewState":"machine_candidate"},{"key":"coursework","label":"Coursework guidance","points":10,"maxPoints":10,"status":"restricted","evidenceClaimIds":["claim-cornell-university-14","claim-cornell-university-2","claim-cornell-university-4","claim-cornell-university-15","claim-cornell-university-20"],"reviewState":"machine_candidate"},{"key":"exams","label":"Exam or assessment guidance","points":0,"maxPoints":10,"status":"not_mentioned","evidenceClaimIds":[],"reviewState":"machine_candidate"},{"key":"privacy_data_entry","label":"Privacy or data-entry guidance","points":15,"maxPoints":15,"status":"restricted","evidenceClaimIds":["claim-cornell-university-12","claim-cornell-university-13","claim-cornell-university-14","claim-cornell-university-19","claim-cornell-university-1"],"reviewState":"machine_candidate"},{"key":"approved_tools","label":"Approved tools, procurement, or licensed tools","points":10,"maxPoints":10,"status":"recommended","evidenceClaimIds":["claim-cornell-university-2"],"reviewState":"machine_candidate"},{"key":"teaching_guidance","label":"Teaching or research guidance","points":10,"maxPoints":10,"status":"recommended","evidenceClaimIds":["claim-cornell-university-12","claim-cornell-university-14","claim-cornell-university-2","claim-cornell-university-4","claim-cornell-university-15"],"reviewState":"machine_candidate"}],"reviewState":"machine_candidate","limitations":["Policy Coverage Score measures breadth of public, source-backed coverage; it is not a policy quality score.","This tracker is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page."]},"dimensions":[{"key":"policy_presence","label":"Policy presence","status":"unclear","normalizedValue":"public_policy_or_guidance_source_present:unclear","summary":"Cornell University has 5 source-backed public claims for policy presence; deterministic analysis status: unclear.","explanation":"Whether the public record contains official AI policy or guidance sources. This unclear status was derived from claim type, normalized value, and keyword rules over 5 supporting public claims. Review the basis array before reusing this as a policy conclusion.","evidenceClaimIds":["claim-cornell-university-16","claim-cornell-university-2","claim-cornell-university-20","claim-cornell-university-25","claim-cornell-university-10"],"evidenceSourceUrls":["https://it.cornell.edu/ai-strategy/ai-guidelines","https://teaching.cornell.edu/generative-artificial-intelligence","https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","https://teaching.cornell.edu/generative-artificial-intelligence/ai-course-policy-icons","https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education"],"sourceLanguages":["en"],"reviewState":"machine_candidate","confidence":0.796,"evidenceCount":5,"sourceCount":5,"basis":[{"claimId":"claim-cornell-university-16","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"We recommend instructors consider three kinds of policies either for individual assignments or generally in their courses. To prohibit the use of GAI where it interferes with the student developing foundational understanding, skills, and knowledge needed for future courses and careers. To allow with attribution where GAI could be a useful resource, but the instructor needs to be aware of its use by the student and the student must learn to take responsibility for accuracy and correct attribution of GAI-generated content. To encourage and actively integrate GAI into the learning process where students can leverage GAI to focus on higher-level learning objectives, explore creative ideas, or...","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-2","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence","sourceLanguage":"en","evidenceSnippet":"Cornell's response to generative AI in teaching and learning is built around seven core principles. We invite instructors to consider these principles as they make decisions and talk with their students and colleagues about generative AI and learning: The integrity of the faculty-student relation. A commitment to experimentation, evidence and learning from experience. The centrality of faculty judgment and expertise in the classroom. Responsiveness to real student needs and uses. Recognition of both AI 'goods' and 'harms'. Respect for institutional and disciplinary heterogeneity. The extension and renewal of Cornell's core mission and values.","sourceSnapshotHash":"9e356eb6cdc55b86bb2fe059937e4db6796ecccd6b030574c5dc40bcff74c3b3","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-20","sourceUrl":"https://it.cornell.edu/ai-strategy/ai-guidelines","sourceLanguage":"en","evidenceSnippet":"Cornell encourages a flexible framework in which faculty and instructors can choose to prohibit, to allow with attribution, or to encourage generative AI use.","sourceSnapshotHash":"b1a7c670aa0bf99b4502416ec7c7250135b063b6991367a057f5d2a1ca97251d","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-25","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/ai-course-policy-icons","sourceLanguage":"en","evidenceSnippet":"These icons have been developed to help you clearly and consistently communicate your expectations. They can be used on the syllabus to convey an overall course approach. They can also be used for individual assignments, allowing you to distinguish different policies for different assignments with different learning goals. Icons can be combined to more fully reflect your course policy.","sourceSnapshotHash":"04f6b71ef9ef4fcd47a7d53be6aca3d0929c179dd7a2262df68a5bea184951ad","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-10","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","sourceLanguage":"en","evidenceSnippet":"A set of course policy icons has been developed by the GenAI Advisory Council to help Cornell instructors communicate with students about appropriate AI use for different courses and assignments. They are downloadable and can be incorporated into your syllabus or assignment instructions, to help provide clear guidance to students about course expectations.","sourceSnapshotHash":"dc5bf374079a8450be06eca45adafca010faa27d86c5d2ea70da2fca9a166662","reviewState":"agent_reviewed"}]},{"key":"ai_disclosure","label":"AI disclosure","status":"required","normalizedValue":"ai_use_disclosure_or_acknowledgement_addressed:required","summary":"Cornell University has 5 source-backed public claims for ai disclosure; deterministic analysis status: required.","explanation":"Whether public guidance addresses disclosure, acknowledgement, citation, or declaration of AI use. This required status was derived from claim type, normalized value, and keyword rules over 5 supporting public claims. Review the basis array before reusing this as a policy conclusion.","evidenceClaimIds":["claim-cornell-university-16","claim-cornell-university-7","claim-cornell-university-15","claim-cornell-university-20","claim-cornell-university-5"],"evidenceSourceUrls":["https://it.cornell.edu/ai-strategy/ai-guidelines","https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education"],"sourceLanguages":["en"],"reviewState":"machine_candidate","confidence":0.797,"evidenceCount":5,"sourceCount":3,"basis":[{"claimId":"claim-cornell-university-16","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"We recommend instructors consider three kinds of policies either for individual assignments or generally in their courses. To prohibit the use of GAI where it interferes with the student developing foundational understanding, skills, and knowledge needed for future courses and careers. To allow with attribution where GAI could be a useful resource, but the instructor needs to be aware of its use by the student and the student must learn to take responsibility for accuracy and correct attribution of GAI-generated content. To encourage and actively integrate GAI into the learning process where students can leverage GAI to focus on higher-level learning objectives, explore creative ideas, or...","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-7","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","sourceLanguage":"en","evidenceSnippet":"We currently do not recommend using current automatic detection algorithms for academic integrity violations using generative AI, given their unreliability and current inability to provide definitive evidence of violations.","sourceSnapshotHash":"dc5bf374079a8450be06eca45adafca010faa27d86c5d2ea70da2fca9a166662","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-15","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"The Code of Academic Integrity should be updated with clear and explicit language on the use of GAI, specifically indicating that individual faculty have authority to determine when its use is prohibited, attributed, or encouraged, and that use of GAI on assignments by students is only allowed when expressly permitted by the faculty member.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-20","sourceUrl":"https://it.cornell.edu/ai-strategy/ai-guidelines","sourceLanguage":"en","evidenceSnippet":"Cornell encourages a flexible framework in which faculty and instructors can choose to prohibit, to allow with attribution, or to encourage generative AI use.","sourceSnapshotHash":"b1a7c670aa0bf99b4502416ec7c7250135b063b6991367a057f5d2a1ca97251d","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-5","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","sourceLanguage":"en","evidenceSnippet":"When generative AI is permitted, clarify expectations for documentation and attribution, as well as what aspects of the work should be produced by the students themselves. ... students should attribute directly quoted text to the creator of the generative AI tool used (e.g., cite OpenAI when directly quoting ChatGPT). This attribution should be used for both in-text citations and your reference list.","sourceSnapshotHash":"dc5bf374079a8450be06eca45adafca010faa27d86c5d2ea70da2fca9a166662","reviewState":"agent_reviewed"}]},{"key":"coursework","label":"Coursework","status":"restricted","normalizedValue":"course_or_assignment_dependent:restricted","summary":"Cornell University has 5 source-backed public claims for coursework; deterministic analysis status: restricted.","explanation":"Whether public guidance addresses coursework, assignments, syllabi, papers, homework, or submitted work. This restricted status was derived from claim type, normalized value, and keyword rules over 5 supporting public claims. Review the basis array before reusing this as a policy conclusion.","evidenceClaimIds":["claim-cornell-university-14","claim-cornell-university-2","claim-cornell-university-4","claim-cornell-university-15","claim-cornell-university-20"],"evidenceSourceUrls":["https://it.cornell.edu/ai-strategy/ai-guidelines","https://teaching.cornell.edu/generative-artificial-intelligence","https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education"],"sourceLanguages":["en"],"reviewState":"machine_candidate","confidence":0.801,"evidenceCount":5,"sourceCount":4,"basis":[{"claimId":"claim-cornell-university-14","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"While GAI may have selective utility in assisting in providing feedback for low-stakes formative assessment (for example in practice problems), we currently do NOT recommend it be used in summative evaluation of student work. Evaluation and grading of students is among the most important tasks entrusted to faculty, and the integrity of the grading process is reliant on the primary role of the faculty member.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-2","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence","sourceLanguage":"en","evidenceSnippet":"Cornell's response to generative AI in teaching and learning is built around seven core principles. We invite instructors to consider these principles as they make decisions and talk with their students and colleagues about generative AI and learning: The integrity of the faculty-student relation. A commitment to experimentation, evidence and learning from experience. The centrality of faculty judgment and expertise in the classroom. Responsiveness to real student needs and uses. Recognition of both AI 'goods' and 'harms'. Respect for institutional and disciplinary heterogeneity. The extension and renewal of Cornell's core mission and values.","sourceSnapshotHash":"9e356eb6cdc55b86bb2fe059937e4db6796ecccd6b030574c5dc40bcff74c3b3","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-4","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","sourceLanguage":"en","evidenceSnippet":"To best support student learning and reduce violations of academic integrity, be sure to clearly communicate your policies regarding the use of generative AI in your syllabus, in assignment instructions, and verbally in class.","sourceSnapshotHash":"dc5bf374079a8450be06eca45adafca010faa27d86c5d2ea70da2fca9a166662","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-15","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"The Code of Academic Integrity should be updated with clear and explicit language on the use of GAI, specifically indicating that individual faculty have authority to determine when its use is prohibited, attributed, or encouraged, and that use of GAI on assignments by students is only allowed when expressly permitted by the faculty member.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-20","sourceUrl":"https://it.cornell.edu/ai-strategy/ai-guidelines","sourceLanguage":"en","evidenceSnippet":"Cornell encourages a flexible framework in which faculty and instructors can choose to prohibit, to allow with attribution, or to encourage generative AI use.","sourceSnapshotHash":"b1a7c670aa0bf99b4502416ec7c7250135b063b6991367a057f5d2a1ca97251d","reviewState":"agent_reviewed"}]},{"key":"exams","label":"Exams","status":"not_mentioned","summary":"No source-backed public claim about exam AI use is present in this profile.","explanation":"This is an absence-of-evidence marker for the current tracker profile, not proof that no such policy exists.","evidenceClaimIds":[],"evidenceSourceUrls":[],"sourceLanguages":[],"reviewState":"machine_candidate","confidence":0,"evidenceCount":0,"sourceCount":0,"notMentionedReason":"The current public tracker record does not contain claim evidence about exams, tests, quizzes, or examination conditions.","basis":[]},{"key":"privacy_data_entry","label":"Privacy and data entry","status":"restricted","normalizedValue":"sensitive_or_confidential_data_restricted:restricted","summary":"Cornell University has 5 source-backed public claims for privacy and data entry; deterministic analysis status: restricted.","explanation":"Whether public guidance addresses personal, confidential, sensitive, regulated, or student data entry into AI tools. This restricted status was derived from claim type, normalized value, and keyword rules over 5 supporting public claims. Review the basis array before reusing this as a policy conclusion.","evidenceClaimIds":["claim-cornell-university-12","claim-cornell-university-13","claim-cornell-university-14","claim-cornell-university-19","claim-cornell-university-1"],"evidenceSourceUrls":["https://it.cornell.edu/ai-strategy/ai-guidelines","https://teaching.cornell.edu/generative-artificial-intelligence","https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education"],"sourceLanguages":["en"],"reviewState":"machine_candidate","confidence":0.802,"evidenceCount":5,"sourceCount":3,"basis":[{"claimId":"claim-cornell-university-12","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"GAI tools pose potential privacy risks because data that is shared may be used as training data by the third-party vendor providing the service. Therefore, any information that educators are obligated to keep private, for example, under the Family Educational Rights and Privacy Act (FERPA) or the Health Insurance Portability and Accountability Act (HIPAA), should not be shared with such tools or uploaded to these third party vendors of GAI.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-13","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"GAI tools also have implications for intellectual property rights. Original research or content that is owned by Cornell University, our students, or employees should not be uploaded to these tools, since they can become part of the training data used by the GAI tools.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-14","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"While GAI may have selective utility in assisting in providing feedback for low-stakes formative assessment (for example in practice problems), we currently do NOT recommend it be used in summative evaluation of student work. Evaluation and grading of students is among the most important tasks entrusted to faculty, and the integrity of the grading process is reliant on the primary role of the faculty member.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-19","sourceUrl":"https://it.cornell.edu/ai-strategy/ai-guidelines","sourceLanguage":"en","evidenceSnippet":"If you are using public generative AI tools, you cannot enter any Cornell information, or another person's information, that is confidential, proprietary, subject to federal or state regulations, or otherwise considered sensitive or restricted. Any information you provide to public generative AI tools is considered public and may be stored and used by anyone else.","sourceSnapshotHash":"b1a7c670aa0bf99b4502416ec7c7250135b063b6991367a057f5d2a1ca97251d","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-1","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence","sourceLanguage":"en","evidenceSnippet":"We recommend discussing course policies and expectations around their use, and clearly communicating with your students when and in what ways use of generative AI tools are permitted – or not.","sourceSnapshotHash":"9e356eb6cdc55b86bb2fe059937e4db6796ecccd6b030574c5dc40bcff74c3b3","reviewState":"agent_reviewed"}]},{"key":"academic_integrity","label":"Academic integrity","status":"restricted","normalizedValue":"ai_use_subject_to_academic_integrity_rules:restricted","summary":"Cornell University has 5 source-backed public claims for academic integrity; deterministic analysis status: restricted.","explanation":"Whether public guidance connects AI use to academic integrity, misconduct, dishonesty, plagiarism, or cheating rules. This restricted status was derived from claim type, normalized value, and keyword rules over 5 supporting public claims. Review the basis array before reusing this as a policy conclusion.","evidenceClaimIds":["claim-cornell-university-17","claim-cornell-university-4","claim-cornell-university-7","claim-cornell-university-15","claim-cornell-university-11"],"evidenceSourceUrls":["https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education"],"sourceLanguages":["en"],"reviewState":"machine_candidate","confidence":0.796,"evidenceCount":5,"sourceCount":2,"basis":[{"claimId":"claim-cornell-university-17","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"We currently discourage the use of automatic detection algorithms for academic integrity violations using GAI, given their unreliability and current inability to provide definitive evidence of violations.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-4","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","sourceLanguage":"en","evidenceSnippet":"To best support student learning and reduce violations of academic integrity, be sure to clearly communicate your policies regarding the use of generative AI in your syllabus, in assignment instructions, and verbally in class.","sourceSnapshotHash":"dc5bf374079a8450be06eca45adafca010faa27d86c5d2ea70da2fca9a166662","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-7","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","sourceLanguage":"en","evidenceSnippet":"We currently do not recommend using current automatic detection algorithms for academic integrity violations using generative AI, given their unreliability and current inability to provide definitive evidence of violations.","sourceSnapshotHash":"dc5bf374079a8450be06eca45adafca010faa27d86c5d2ea70da2fca9a166662","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-15","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"The Code of Academic Integrity should be updated with clear and explicit language on the use of GAI, specifically indicating that individual faculty have authority to determine when its use is prohibited, attributed, or encouraged, and that use of GAI on assignments by students is only allowed when expressly permitted by the faculty member.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-11","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","sourceLanguage":"en","evidenceSnippet":"Require that students verify the accuracy of all citations and references they include in their work. Request that students provide verification of references or methods, with a student's response determining whether a formal academic integrity notification is warranted. ... Inform and remind students that they should expect to verbally explain the work they submitted.","sourceSnapshotHash":"dc5bf374079a8450be06eca45adafca010faa27d86c5d2ea70da2fca9a166662","reviewState":"agent_reviewed"}]},{"key":"approved_tools","label":"Approved tools","status":"recommended","normalizedValue":"approved_or_licensed_ai_tools_identified:recommended","summary":"Cornell University has 1 source-backed public claim for approved tools; deterministic analysis status: recommended.","explanation":"Whether public guidance identifies institutionally approved, licensed, procured, or enterprise AI tools. This recommended status was derived from claim type, normalized value, and keyword rules over 1 supporting public claim. Review the basis array before reusing this as a policy conclusion.","evidenceClaimIds":["claim-cornell-university-2"],"evidenceSourceUrls":["https://teaching.cornell.edu/generative-artificial-intelligence"],"sourceLanguages":["en"],"reviewState":"machine_candidate","confidence":0.808,"evidenceCount":1,"sourceCount":1,"basis":[{"claimId":"claim-cornell-university-2","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence","sourceLanguage":"en","evidenceSnippet":"Cornell's response to generative AI in teaching and learning is built around seven core principles. We invite instructors to consider these principles as they make decisions and talk with their students and colleagues about generative AI and learning: The integrity of the faculty-student relation. A commitment to experimentation, evidence and learning from experience. The centrality of faculty judgment and expertise in the classroom. Responsiveness to real student needs and uses. Recognition of both AI 'goods' and 'harms'. Respect for institutional and disciplinary heterogeneity. The extension and renewal of Cornell's core mission and values.","sourceSnapshotHash":"9e356eb6cdc55b86bb2fe059937e4db6796ecccd6b030574c5dc40bcff74c3b3","reviewState":"agent_reviewed"}]},{"key":"named_ai_services","label":"Named AI services","status":"required","normalizedValue":"named_ai_services_present:required","summary":"Cornell University has 1 source-backed public claim for named ai services; deterministic analysis status: required.","explanation":"Whether public guidance names AI services such as ChatGPT, Copilot, Claude, Gemini, Grammarly, or DeepSeek. This required status was derived from claim type, normalized value, and keyword rules over 1 supporting public claim. Review the basis array before reusing this as a policy conclusion.","evidenceClaimIds":["claim-cornell-university-5"],"evidenceSourceUrls":["https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity"],"sourceLanguages":["en"],"reviewState":"machine_candidate","confidence":0.791,"evidenceCount":1,"sourceCount":1,"basis":[{"claimId":"claim-cornell-university-5","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","sourceLanguage":"en","evidenceSnippet":"When generative AI is permitted, clarify expectations for documentation and attribution, as well as what aspects of the work should be produced by the students themselves. ... students should attribute directly quoted text to the creator of the generative AI tool used (e.g., cite OpenAI when directly quoting ChatGPT). This attribution should be used for both in-text citations and your reference list.","sourceSnapshotHash":"dc5bf374079a8450be06eca45adafca010faa27d86c5d2ea70da2fca9a166662","reviewState":"agent_reviewed"}]},{"key":"teaching_guidance","label":"Teaching guidance","status":"recommended","normalizedValue":"instructor_or_teaching_guidance_available:recommended","summary":"Cornell University has 5 source-backed public claims for teaching guidance; deterministic analysis status: recommended.","explanation":"Whether public guidance addresses instructors, teaching, classroom policy, assessment design, or syllabus language. This recommended status was derived from claim type, normalized value, and keyword rules over 5 supporting public claims. Review the basis array before reusing this as a policy conclusion.","evidenceClaimIds":["claim-cornell-university-12","claim-cornell-university-14","claim-cornell-university-2","claim-cornell-university-4","claim-cornell-university-15"],"evidenceSourceUrls":["https://teaching.cornell.edu/generative-artificial-intelligence","https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education"],"sourceLanguages":["en"],"reviewState":"machine_candidate","confidence":0.804,"evidenceCount":5,"sourceCount":3,"basis":[{"claimId":"claim-cornell-university-12","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"GAI tools pose potential privacy risks because data that is shared may be used as training data by the third-party vendor providing the service. Therefore, any information that educators are obligated to keep private, for example, under the Family Educational Rights and Privacy Act (FERPA) or the Health Insurance Portability and Accountability Act (HIPAA), should not be shared with such tools or uploaded to these third party vendors of GAI.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-14","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"While GAI may have selective utility in assisting in providing feedback for low-stakes formative assessment (for example in practice problems), we currently do NOT recommend it be used in summative evaluation of student work. Evaluation and grading of students is among the most important tasks entrusted to faculty, and the integrity of the grading process is reliant on the primary role of the faculty member.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-2","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence","sourceLanguage":"en","evidenceSnippet":"Cornell's response to generative AI in teaching and learning is built around seven core principles. We invite instructors to consider these principles as they make decisions and talk with their students and colleagues about generative AI and learning: The integrity of the faculty-student relation. A commitment to experimentation, evidence and learning from experience. The centrality of faculty judgment and expertise in the classroom. Responsiveness to real student needs and uses. Recognition of both AI 'goods' and 'harms'. Respect for institutional and disciplinary heterogeneity. The extension and renewal of Cornell's core mission and values.","sourceSnapshotHash":"9e356eb6cdc55b86bb2fe059937e4db6796ecccd6b030574c5dc40bcff74c3b3","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-4","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/ai-academic-integrity","sourceLanguage":"en","evidenceSnippet":"To best support student learning and reduce violations of academic integrity, be sure to clearly communicate your policies regarding the use of generative AI in your syllabus, in assignment instructions, and verbally in class.","sourceSnapshotHash":"dc5bf374079a8450be06eca45adafca010faa27d86c5d2ea70da2fca9a166662","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-15","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"The Code of Academic Integrity should be updated with clear and explicit language on the use of GAI, specifically indicating that individual faculty have authority to determine when its use is prohibited, attributed, or encouraged, and that use of GAI on assignments by students is only allowed when expressly permitted by the faculty member.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"}]},{"key":"research_guidance","label":"Research guidance","status":"recommended","normalizedValue":"research_ai_guidance_available:recommended","summary":"Cornell University has 2 source-backed public claims for research guidance; deterministic analysis status: recommended.","explanation":"Whether public guidance addresses research use, publication ethics, research data, grants, or human-subjects compliance. This recommended status was derived from claim type, normalized value, and keyword rules over 2 supporting public claims. Review the basis array before reusing this as a policy conclusion.","evidenceClaimIds":["claim-cornell-university-13","claim-cornell-university-21"],"evidenceSourceUrls":["https://it.cornell.edu/ai-strategy/ai-guidelines","https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education"],"sourceLanguages":["en"],"reviewState":"machine_candidate","confidence":0.786,"evidenceCount":2,"sourceCount":2,"basis":[{"claimId":"claim-cornell-university-13","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"GAI tools also have implications for intellectual property rights. Original research or content that is owned by Cornell University, our students, or employees should not be uploaded to these tools, since they can become part of the training data used by the GAI tools.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"},{"claimId":"claim-cornell-university-21","sourceUrl":"https://it.cornell.edu/ai-strategy/ai-guidelines","sourceLanguage":"en","evidenceSnippet":"The Cornell University Task Force Report, Generative AI in Academic Research: Perspectives and Cultural Norms (December 2023), offers perspectives and practical guidelines to the Cornell community on the use of generative AI in the practice and dissemination of academic research.","sourceSnapshotHash":"b1a7c670aa0bf99b4502416ec7c7250135b063b6991367a057f5d2a1ca97251d","reviewState":"agent_reviewed"}]},{"key":"security_procurement","label":"Security and procurement","status":"recommended","normalizedValue":"security_procurement_or_enterprise_review_addressed:recommended","summary":"Cornell University has 1 source-backed public claim for security and procurement; deterministic analysis status: recommended.","explanation":"Whether public guidance addresses security review, procurement, vendor approval, risk assessment, authentication, SSO, or licensing. This recommended status was derived from claim type, normalized value, and keyword rules over 1 supporting public claim. Review the basis array before reusing this as a policy conclusion.","evidenceClaimIds":["claim-cornell-university-12"],"evidenceSourceUrls":["https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education"],"sourceLanguages":["en"],"reviewState":"machine_candidate","confidence":0.808,"evidenceCount":1,"sourceCount":1,"basis":[{"claimId":"claim-cornell-university-12","sourceUrl":"https://teaching.cornell.edu/generative-artificial-intelligence/cu-committee-report-generative-artificial-intelligence-education","sourceLanguage":"en","evidenceSnippet":"GAI tools pose potential privacy risks because data that is shared may be used as training data by the third-party vendor providing the service. Therefore, any information that educators are obligated to keep private, for example, under the Family Educational Rights and Privacy Act (FERPA) or the Health Insurance Portability and Accountability Act (HIPAA), should not be shared with such tools or uploaded to these third party vendors of GAI.","sourceSnapshotHash":"deeacd6dce5b944ffc00d979b34c83f57677a2f04ceb39c803a701b72d8caab6","reviewState":"agent_reviewed"}]}],"limitations":["Policy analysis profiles are deterministic summaries of public tracker claims and are not final policy conclusions.","Policy Coverage Score measures breadth of public, source-backed coverage; it is not a policy quality score, strictness score, legal adequacy score, safety score, or institutional compliance score.","This tracker is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page."],"suggestedCitation":"University AI Policy Tracker. \"Cornell University policy analysis profile.\" Version v1. https://eduaipolicy.org/universities/cornell-university"}}