California Institute of Technology (Caltech)

The responding student will be given 7 calendar days to decide which process to follow. As with the full Board of Control process, responding students may seek the advice and support of another member of the Caltech community in navigating the Early Resolution process.

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Any student with a disability involved in any process outlined in the Honor Code

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Handbook has the right to request reasonable accommodation in order to ensure their

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full and equal participation in the process. Students wishing to request reasonable

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accommodations should make those requests directly to Caltech Accessibility

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Services for Students (CASS). Students do not have to disclose information about the

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complaint or charge to CASS to request reasonable accommodation except to the

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extent that it may assist in the determination of reasonable accommodations.

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Accommodations are determined on an individual basis by CASS staff and

Bevisfinner: Continuous extracted-text characters 4018–4088; extracted text SHA256 7e243de8a77f598c4af53899160c05b511705fc1149ed83c8ab9827ae9e482dc; raw source SHA256 59b3c16fc62be458f0fc1448f4fb922a6b9dd3fe109e567140d755ccefb94c5f; Physical pages 2-2; text lines 77-77; Lines 77–77; characters 4018–4088; excerpt offset 0–70

implemented in consultation with the Dean’s office. Examples of reasonable

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accommodation include but are not limited to sign language interpretation, real-time

Bevisfinner: Continuous extracted-text characters 4170–4254; extracted text SHA256 7e243de8a77f598c4af53899160c05b511705fc1149ed83c8ab9827ae9e482dc; raw source SHA256 59b3c16fc62be458f0fc1448f4fb922a6b9dd3fe109e567140d755ccefb94c5f; Physical pages 2-2; text lines 79-79; Lines 79–79; characters 4170–4254; excerpt offset 0–84

1

Bevisfinner: Continuous extracted-text characters 4349–4350; extracted text SHA256 7e243de8a77f598c4af53899160c05b511705fc1149ed83c8ab9827ae9e482dc; raw source SHA256 59b3c16fc62be458f0fc1448f4fb922a6b9dd3fe109e567140d755ccefb94c5f; Physical pages 2-2; text lines 83-83; Lines 83–83; characters 4349–4350; excerpt offset 0–1

communication access during hearings, large print documents, extended time to

Bevisfinner: Continuous extracted-text characters 4357–4434; extracted text SHA256 7e243de8a77f598c4af53899160c05b511705fc1149ed83c8ab9827ae9e482dc; raw source SHA256 59b3c16fc62be458f0fc1448f4fb922a6b9dd3fe109e567140d755ccefb94c5f; Physical pages 3-3; text lines 84-84; Lines 84–84; characters 4357–4434; excerpt offset 0–77

review documents, or assistance with transcribing questions during interviews or

Bevisfinner: Continuous extracted-text characters 4440–4520; extracted text SHA256 7e243de8a77f598c4af53899160c05b511705fc1149ed83c8ab9827ae9e482dc; raw source SHA256 59b3c16fc62be458f0fc1448f4fb922a6b9dd3fe109e567140d755ccefb94c5f; Physical pages 3-3; text lines 85-85; Lines 85–85; characters 4440–4520; excerpt offset 0–80

hearings. Students are responsible for requesting accommodations in a timely manner;

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failure to do so may result in a delay in the process.

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To an advisor who must be a member of the Caltech community (but who may not be an attorney). Student Affairs staff, Board of Control representatives, and Conduct Review Committee members are all trained to serve as advisors to respondents going through conduct processes.

Bevisfinner: Continuous extracted-text characters 5464–5775; extracted text SHA256 7e243de8a77f598c4af53899160c05b511705fc1149ed83c8ab9827ae9e482dc; raw source SHA256 59b3c16fc62be458f0fc1448f4fb922a6b9dd3fe109e567140d755ccefb94c5f; Physical pages 3-3; text lines 106-109; Lines 106–109; characters 5464–5775; excerpt offset 0–311

Incidents that are not handled by the Dean of Graduate Studies include accusations of research misconduct, which are handled by the Office of Research Compliance; grade disputes, which are handled by the office of the provost.

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At present, students submitting work for HSS courses may use generative AI tools only in ways that are explicitly allowed by the course instructor in the course materials. Any usage that is not specifically allowed should be assumed to be disallowed.

Bevisfinner: Continuous extracted-text characters 409–659; extracted text SHA256 99c04c9785a0f8a6b533961c3e57f0220479b8319c55e8026a46722eb445ad2e; raw source SHA256 65981a33980d337c75dff63fda5e9de5625f28527e036e4734903f5dd0200155; HSS Policy lines 13-17; Lines 23–23; characters 409–659; excerpt offset 0–250

This policy applies to all assignments, including major papers and exams as well as smaller assignments like discussion board posts, reflections, and problem sets.

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Students will also be expected to follow specific course guidance for documenting any permitted use of these tools.

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Caltech students, faculty, and staff are guided by the Honor Code and policies of AI use as an academic tool by students will be determined by individual departments and/or individual faculty.

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3.1 Approved Platforms & Connectivity 1. Primary LLM inference for Caltech data must use Amazon Bedrock or other IMSS-approved platforms with no provider training on Caltech prompts/data. 2. Custom training/fine-tuning must be performed on Amazon SageMaker or IMSS-approved secured environments.

Bevisfinner: Continuous extracted-text characters 4123–4449; extracted text SHA256 08419c903b343881417bc45ea170b7e7e614956aa681e0242db84e857f1e2898; raw source SHA256 431ef2c9286a630c09fe9a1b1325cb2b1698bc23e9c6ef4805251641f08582b8; Physical pages 3-3; text lines 118-124; Lines 118–124; characters 4123–4449; excerpt offset 0–326

In our teaching, HSS instructors prioritize student learning, and this commitment drives our policies on the use of generative AI in the classroom. Generative AI may promote learning in some contexts and impede it in others.

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At this time, Caltech's Undergraduate and Graduate Deans, the Center for Teaching, Learning, and Outreach, and the Hixon Writing Center strongly discourage the use of GenAI tools designed to detect GenAI use in student writing. First and foremost, these tools are not reliable. They produce false positives and false negatives, and they are not an aid to investigations into academic dishonesty cases.

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You may not use generative AI tools (e.g. ChatGPT, Copilot, Colab’s built-in AI) in this course. This is not to deny the increasingly important role that LLMs play in the modern practice of programming and research; we merely note that, in an instructional capacity in an introductory course, we generally find them counterproductive. The lone exception is that, on rare occasions, we may explicitly ask you to engage with AI tools on a per-problem basis. These cases will be clearly marked on the respective homework sets.

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Do not enter any restricted or confidential Caltech information into consumer AI tools (ChatGPT Free/Plus, Gemini, Claude, Perplexity, etc.) Examples of restricted or confidential data are: Data covered by FERPA and HIPAA Student data Intellectual property and unpublished research Export‑controlled data Sensitive data from human resources, business and finance Information created, received, stored, or processed as part of academic, research, or administrative activities.

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4. Public, consumer, or unsanctioned GenAI tools are prohibited for Restricted/Confidential data unless IMSS issues a specific exception with compensating controls.

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Exceptions require the Research Compliance Officer, CIO and CISO (or

Bevisfinner: Continuous extracted-text characters 8128–8196; extracted text SHA256 08419c903b343881417bc45ea170b7e7e614956aa681e0242db84e857f1e2898; raw source SHA256 431ef2c9286a630c09fe9a1b1325cb2b1698bc23e9c6ef4805251641f08582b8; Physical pages 5-5; text lines 212-212; Lines 212–212; characters 8128–8196; excerpt offset 0–68

delegate) approval with compensating controls and an agreed sunset date.

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Do not use Generative AI (GenAI) tools as a system of record. GenAI platforms are not approved for long-term storage, official records management, or institutional data retention. Users must ensure that all records requiring retention are stored in approved Caltech systems in accordance with established policies and regulatory requirements.

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3.1 Approved Platforms & Connectivity 1. Primary LLM inference for Caltech data must use Amazon Bedrock or other IMSS-approved platforms with no provider training on Caltech prompts/data. 2. Custom training/fine-tuning must be performed on Amazon SageMaker or IMSS-approved secured environments.

Bevisfinner: Continuous extracted-text characters 4123–4449; extracted text SHA256 08419c903b343881417bc45ea170b7e7e614956aa681e0242db84e857f1e2898; raw source SHA256 431ef2c9286a630c09fe9a1b1325cb2b1698bc23e9c6ef4805251641f08582b8; Physical pages 3-3; text lines 118-124; Lines 118–124; characters 4123–4449; excerpt offset 0–326

4. Public, consumer, or unsanctioned GenAI tools are prohibited for Restricted/Confidential data unless IMSS issues a specific exception with compensating controls.

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3. All AI traffic with Caltech data must use private networking (e.g., VPC Endpoints/PrivateLink, Direct Connect) and encryption in transit and at rest (TLS 1.2+; KMS CMKs).

Bevisfinner: Continuous extracted-text characters 4457–4648; extracted text SHA256 08419c903b343881417bc45ea170b7e7e614956aa681e0242db84e857f1e2898; raw source SHA256 431ef2c9286a630c09fe9a1b1325cb2b1698bc23e9c6ef4805251641f08582b8; Physical pages 3-3; text lines 126-128; Lines 126–128; characters 4457–4648; excerpt offset 0–191

Exceptions require the Research Compliance Officer, CIO and CISO (or

Bevisfinner: Continuous extracted-text characters 8128–8196; extracted text SHA256 08419c903b343881417bc45ea170b7e7e614956aa681e0242db84e857f1e2898; raw source SHA256 431ef2c9286a630c09fe9a1b1325cb2b1698bc23e9c6ef4805251641f08582b8; Physical pages 5-5; text lines 212-212; Lines 212–212; characters 8128–8196; excerpt offset 0–68

delegate) approval with compensating controls and an agreed sunset date.

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3. Agent Controls: Agents must only invoke approved tools with explicit scopes and least-privilege credentials; no arbitrary code execution in production without sandboxing.

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Violations may result in access revocation, removal of workloads, and disciplinary actions per Caltech IMSS. Persistent violations are escalated to the CIO, CISO, OGC and appropriate governance bodies.

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3. Human subjects / sensitive research: Requires IRB approvals and IMSS data-use review before any LLM processing.

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Anthropic Claude Premium Available $600/user/year PTA via access.caltech**

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Anthropic Claude Standard Available $240/user/year PTA via access.caltech**

Bevisfinner: Continuous extracted-text characters 1167–1245; extracted text SHA256 c7b3d909bf52ec66b6963162660e3aa6bd728149ee7b9e296996ad3f9c0a9273; raw source SHA256 1056e32c778f124cc30af82f2c28d9676e25e7c1e11e666900b7b4158c0929fa; IMSS AI Tools Table lines 45-51; Lines 45–51; characters 1167–1245; excerpt offset 0–78

Microsoft Copilot Web Available Free

Bevisfinner: Continuous extracted-text characters 1670–1708; extracted text SHA256 c7b3d909bf52ec66b6963162660e3aa6bd728149ee7b9e296996ad3f9c0a9273; raw source SHA256 1056e32c778f124cc30af82f2c28d9676e25e7c1e11e666900b7b4158c0929fa; IMSS AI Tools Table lines 99-103; Lines 99–103; characters 1670–1708; excerpt offset 0–38

Microsoft 365 Copilot for Windows 11 Available Free

Bevisfinner: Continuous extracted-text characters 1615–1668; extracted text SHA256 c7b3d909bf52ec66b6963162660e3aa6bd728149ee7b9e296996ad3f9c0a9273; raw source SHA256 1056e32c778f124cc30af82f2c28d9676e25e7c1e11e666900b7b4158c0929fa; IMSS AI Tools Table lines 93-97; Lines 93–97; characters 1615–1668; excerpt offset 0–53

Zoom AI Companion Available Free

Bevisfinner: Continuous extracted-text characters 1710–1744; extracted text SHA256 c7b3d909bf52ec66b6963162660e3aa6bd728149ee7b9e296996ad3f9c0a9273; raw source SHA256 1056e32c778f124cc30af82f2c28d9676e25e7c1e11e666900b7b4158c0929fa; IMSS AI Tools Table lines 105-109; Lines 105–109; characters 1710–1744; excerpt offset 0–34

Microsoft 365 Copilot for Education Coming Soon $216/user/year PTA via access.caltech**

Bevisfinner: Continuous extracted-text characters 1523–1613; extracted text SHA256 c7b3d909bf52ec66b6963162660e3aa6bd728149ee7b9e296996ad3f9c0a9273; raw source SHA256 1056e32c778f124cc30af82f2c28d9676e25e7c1e11e666900b7b4158c0929fa; IMSS AI Tools Table lines 85-91; Lines 85–91; characters 1523–1613; excerpt offset 0–90

1. Security & Data Processing Addendum required for any non-AWS LLM vendor; no training on Caltech data clauses is a mandatory requirement.

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As you use GenAI and LLM technologies in your work at Caltech, we ask that you apply these four guiding principles to your practice: disclosure, data and information protection, content responsibility, and Caltech's honor code. Disclosure: When using GenAI, always disclose promptly, or reference the use of GenAI tools and application plug-ins, as applicable.

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What are some examples of unethical uses of AI for Caltech admissions essays? Copying and pasting directly from an AI generator Relying on AI generated content to outline or draft an essay Replacing your unique voice and tone with AI generated content Translating an essay written in another language

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What are some examples of ethical uses of AI for Caltech admissions essays? Using AI tools, like Grammarly or Microsoft Editor, to review grammar and spelling of your completed essays Generating questions or exercises to help kick start the brainstorming process Using AI to research the college application process

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If you are still wondering whether your use of AI in crafting your application is ethical, ask yourself whether it would be ethical to have a trusted adult perform the same task you are asking of ChatGPT. Would a teacher be able to review your essay for grammatical and spelling errors? Of course! Would that same teacher write a draft of an essay for you to tweak and then submit? Definitely not.

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All Fall 2027 applicants must review Caltech's guidelines on the ethical use of AI before submitting their supplemental essays. Failure to comply with the Ethical Use of AI guidelines may result in the rescission of your admission to Caltech.

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