The Power of Treating AI Like a Colleague
Source: AI Goes to College
Author: Craig Van Slyke
Original source: https://aigoestocollege.substack.com/p/the-power-of-treating-ai-like-a-colleague
Private backup: the full article text is archived in the private repository at archives/articles/aigoestocollege-substack-com-the-power-of-treating-ai-like-a-colleague.source.md. It is not published on the public Quartz site.
Summary
The article argues that treating AI like a human colleague can produce better results, not because AI is actually human, but because social framing prompts users to provide clearer context, better instructions, and more iterative dialogue. It recommends using anthropomorphic framing as a practical mental model while staying calibrated: AI should be treated as role-playing an intern, expert reviewer, editor, or collaborator, not as possessing beliefs or consciousness. The article offers a framework for making this work, including targeted personas, clear expectations, rich context, explicit scaffolding, and independent verification. A reflective section explains that the piece itself was mostly AI-generated, noting both the promise of AI-assisted writing and its current generic feel, tonal mismatch, and “AI tells.”
Big ideas
- Students need to bring the purpose; AI should not supply it for them
- Students need to check AI answers against real evidence
- Treating AI like a person can help only when students know it is role-play
Claims
- Prompting AI is a literacy practice, not just a technical trick
- Treating AI like a person can help if students know the limits
Key evidence and examples
- The article references research on people treating computers as social actors, including Clifford Nass’ work.
- It contrasts a thin prompt about exam questions with a richer colleague-style prompt focused on critical thinking and application.
- Role-play frames include intern, expert reviewer, editor, and collaborative colleague.
- The author stresses calibration: AI is a pattern-matching system, not a conscious being, and important claims should be verified independently.
Education relevance
Highly relevant for faculty development, student AI literacy, prompt design, writing pedagogy, assessment design, and responsible classroom use.