Subject 02 / Public-review draft

Campus AI should protect learning, authorship, and a real say.

AI can support learning, research, accessibility, advising, and campus services. The rules should still protect student work, explain consequential decisions, limit surveillance, respect workers, and give affected people authority before deployment.

Public review only. This draft does not certify a campus, approve a vendor, or imply student, worker, or reviewer endorsement.

Four campus interests meet one shared decision gate before an AI use changes learning or campus life.

In plain language

The campus compact in one minute

A campus should not treat people as passive users of systems chosen elsewhere. Before AI influences learning, access, work, discipline, or data, the campus should publish the rules and give affected people notice, protection, review, and appeal rights.

01 / Explain

Make the rules visible

State when AI is allowed, prohibited, disclosed, evaluated, and subject to human review.

02 / Protect

Limit data and surveillance

Control training reuse, hidden monitoring, profiling, retention, and disciplinary automation.

03 / Govern

Give people decision rights

Students and workers should help review procurement, deployment, correction, and appeal.

04 / Account

Show effects over time

Track learning, access, workload, service quality, data use, and who receives verified gains.

Interactive campus-use test

Choose where AI enters campus life.

Use the lens you know best. The test identifies the risk, proof, people who need protection, and the condition that should make the use pause.

01

Authorship + grading

Can students understand the rules and preserve ownership of their work?

What could go wrong?
Unclear rules can punish students inconsistently, blur original work, or let automated judgments replace explanation.
What proof is needed?
Published course rules, disclosure expectations, human grading responsibility, and evidence that learning goals are preserved.
Who needs protection?
Students need notice, a chance to explain their work, consistent standards, and a human appeal path.
When should it pause?
When a student cannot learn what rule applied, challenge an automated judgment, or preserve authorship and learning integrity.

Your focused review question

What authorship or appeal right must exist before AI is used in grading or academic-integrity decisions?
Answer on this site

Formal public draft

Campus commitments under review

Status: public-review one-pager. The compact is a governance proposal, not a final campus policy, certification, vendor approval, or claim of adoption.

Core principle

AI may support learning, research, accessibility, civic planning, and public benefit, but it must not replace human authorship, human judgment, student agency, worker dignity, or democratic governance.

01

Human authorship

Students must know when AI is allowed, prohibited, disclosed, or evaluated.

02

Learning integrity

AI tools must strengthen explanation, reasoning, debate, and original work.

03

Student data trust

Prompts, submissions, learning, advising, and telemetry data cannot be reused for training without explicit governance.

04

No-surprise automation

Students and workers must know when AI affects grading, advising, admissions, hiring, support, or surveillance.

05

Anti-surveillance

AI adoption must not expand hidden monitoring, profiling, proctoring, or disciplinary automation.

06

Worker dignity

AI should reduce burden and improve services, not hide staff cuts or degrade teaching and support.

07

Benefit clause

Verified savings should support students, workers, tuition relief, emergency aid, training, or community benefit.

08

Student governance seat

Students must have review or voting authority in campus AI procurement and deployment.

Human authorship

People can show, explain, and remain responsible for their own reasoning and original work.

No-surprise automation

People receive clear notice before AI influences a consequential decision or service.

Student data governance

Students have defined rights over access, reuse, retention, deletion, and model training.

One focused contribution

Which campus AI use most needs a stronger right, rule, or appeal path?

Use a real or plausible campus situation. Name who is affected and the minimum protection the compact should require.

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