Evidence over vibe
Claims in computer science are supposed to survive contact with data, texts, materials or clients — not only enthusiasm.
Every major smuggles a theory of what counts as knowledge. Computer Science is no exception: its values show up in what can be submitted for a grade.
Ethics sections are not decoration. Fields that touch bodies, money, infrastructures or stories carry duties that outlast the degree.
Core values
Craft under constraint
Budgets, codes, deadlines and safety rules are part of the discipline, not interruptions to creativity.
Public accountability
Work affects strangers: patients, users, readers, cities. The major trains (or fails to train) that awareness.
Revision culture
Drafts, critiques and failed experiments are normal; hiding error is the professional risk.
Cumulative mastery
Later courses assume earlier ones. Skipping foundations creates silent debt that surfaces in capstones.
Ways of knowing
Primary engagement
Texts, datasets, specimens, sites or clients — second-hand summaries are not enough.
Explicit method
Students must say how they know, not only what they conclude.
Peer critique
Work is improved in public among people who share standards.
Documentation
If it is not recorded, the field treats it as rumour.
Ethical commitments
Do not fabricate
Data, citations and client stories are not props for a grade.
Consent & privacy
Human subjects, communities and users are not free raw material.
Safety & harm
Labs, clinics, sites and stages have non-negotiable rules.
Credit honestly
Collaboration is normal; plagiarism and ghost work are not.
Live tensions
Prestige vs practice
Rankings reward research signals; employers often want practised judgement.
Speed vs rigor
Deadline cultures can train cutting corners unless assessment punishes it.
Local vs global canons
Whose authors, cases and sites count as "core" remains contested.
If a department cannot say what it would fail a student for, its values are marketing.
Keep exploring
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