Kharagpur, India

Indian Institute of Technology Kharagpur (IIT-KGP)

Indian Institute of Technology Kharagpur (IIT-KGP) is listed as QS 2026 rank =215. Indian Institute of Technology Kharagpur (IIT-KGP) has 3 source-backed AI policy claim records from 2 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Short answer

v1 public contract

Indian Institute of Technology Kharagpur (IIT-KGP) is listed as QS 2026 rank =215. Indian Institute of Technology Kharagpur (IIT-KGP) has 3 source-backed AI policy claim records from 2 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.

Citation-ready summary

As of this public record, University AI Policy Tracker lists Indian Institute of Technology Kharagpur (IIT-KGP) as an agent-reviewed AI policy record last checked on May 15, 2026 and last changed on May 15, 2026. The record contains 3 source-backed claims, including 3 reviewed claims, from 2 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/indian-institute-of-technology-kharagpur.json. The entity-level confidence is 88%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.

Claim coverage3 reviewedSource languageenPublic JSON/api/public/v1/universities/indian-institute-of-technology-kharagpur.json

Policy signals in this record

  • Evidence includes Teaching claims.
  • No specific AI service name is highlighted by the current public claim text.
  • Teaching, assessment, coursework, or syllabus-related language appears in the public claim text.
  • Privacy, sensitive-data, or security language appears in the public claim text.
Policy statusReviewed evidence-backed recordReview: Agent reviewedEvidence-backed claims3Reviewed3Candidate0Official sources2

This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.

This page 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.

Policy profile

Deterministic source-backed dimensions derived from this record's public claims.

Coverage score60/100Coverage labelmoderate public coverageReview: Machine candidateAnalysis confidence73%

Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.

Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.

Policy presence

Indian Institute of Technology Kharagpur (IIT-KGP) has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.

UnclearMachine candidateConfidence71%Evidence1Sources1

AI disclosure

No source-backed public claim about AI disclosure or acknowledgement is present in this profile.

The current public tracker record does not contain claim evidence about disclosing, acknowledging, citing, or declaring AI use.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Privacy and data entry

Indian Institute of Technology Kharagpur (IIT-KGP) has 1 source-backed public claim for privacy and data entry; deterministic analysis status: restricted.

RestrictedMachine candidateConfidence75%Evidence1Sources1

Academic integrity

No source-backed public claim about academic-integrity treatment of AI use is present in this profile.

The current public tracker record does not contain claim evidence about AI use under academic integrity, misconduct, dishonesty, plagiarism, or cheating rules.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Approved tools

No source-backed public claim identifying approved or licensed AI tools is present in this profile.

The current public tracker record does not contain claim evidence that identifies institutionally approved, licensed, procured, or enterprise AI tools.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Named AI services

No source-backed public claim naming a specific AI service is present in this profile.

The current public tracker record does not contain claim evidence naming a specific AI service.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Research guidance

No source-backed public claim about research AI use is present in this profile.

The current public tracker record does not contain claim evidence about research use, publication ethics, research data, grants, or human-subjects compliance.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Security and procurement

Indian Institute of Technology Kharagpur (IIT-KGP) has 1 source-backed public claim for security and procurement; deterministic analysis status: restricted.

RestrictedMachine candidateConfidence75%Evidence1Sources1

Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.

Evidence-backed claims

3 reviewed evidence-backed public claim

Teaching

IIT Kharagpur's B.Tech. in AI curriculum includes a core course titled Responsible and Trustworthy AI covering responsible AI, bias and risk assessment, privacy-aware learning, model safety, and accountability.

Review: Agent reviewedConfidence88%

Normalized value: responsible_trustworthy_ai_core_course

Original evidence

Evidence 1
Responsible and Trustworthy AI ... This course will be a core subject for BTech program in AI ... Introduction to responsible AI; Model agnostic interpretable methods; Neural network interpretation; Algorithmic bias and Risk assessment; Privacy aware learning and Model robustness; Model safety and accountability; Application of Responsible AI.

Teaching

IIT Kharagpur Senate recommended a B.Tech. in Artificial Intelligence from Admission Year 2024, subject to the related departmental approval process.

Review: Agent reviewedConfidence86%

Normalized value: btech_ai_recommended_2024

Original evidence

Evidence 1
After thorough discussion and deliberations, the Senate recommended to the BoG for consideration and approval of the UG Program "B. Tech. in Artificial Intelligence" with a sanctioned strength of 30 (Thirty) students from the Admission Year 2024 subject to the approval of conversion of the Centre of Excellence in Artificial Intelligence (CoEAI) to the Department of Artificial Intelligence.

Teaching

IIT Kharagpur's 2025 UG guidance states that studying at least one AI/ML elective will be mandatory for all students.

Review: Agent reviewedConfidence84%

Normalized value: ai_ml_elective_mandatory_all_ug_students

Original evidence

Evidence 1
Considering the rapid developments in "Artificial Intelligence and Machine Learning (AI/ML)" and its huge potential for the nation, studying at least one AI/ML elective will be made mandatory for all the students along with several other electives being offered in areas such as Linguistics, Happiness and Well-Being, Indian Knowledge Systems, Performing Arts etc.

Candidate claims

0 machine or needs-review claim

Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.

Official sources

2 source attribution

Change log

Source-check timeline and diff-style claim/evidence preview.

View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.

Last checkedMay 15, 2026Last changedMay 15, 2026Open change log

Corrections and missing evidence

Corrections create review tasks and do not directly change this public record.

If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.

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