Use vs Relationship: What We’re Not Asking About AI
Source: Mike Kentz Substack
Author: Mike Kentz
Original source: https://mikekentz.substack.com/p/use-vs-relationship-what-were-not?utm_source=post-email-title&publication_id=2339597&post_id=178454895&utm_campaign=email-post-title&isFreemail=true&r=1cu5i&triedRedirect=true&utm_medium=email
Private backup: the full article text is archived in the private repository at archives/articles/mikekentz-substack-com-use-vs-relationship-what-were-not.source.md. It is not published on the public Quartz site.
Summary
Mike Kentz uses the historical automation of telephone operators as an analogy for current AI adoption. AT&T’s focus on what customers “used” operators for made invisible the broader relational and community functions operators performed, including emergency coordination and local knowledge-sharing. Kentz warns that today’s AI discourse repeats this pattern when use cases, productivity, and efficiency obscure questions about dependency, judgment, human connection, and informal knowledge systems. He recommends shifting from “use” language to “relationship” language so institutions can see what they are trading away before those losses become irreversible.
Big ideas
- Schools should start with learning values before choosing AI tools
- AI literacy should help people notice how AI changes what counts as knowing
- Students need to bring the purpose; AI should not supply it for them
Claims
- “Use case” language can hide what AI adoption changes
- Students need boundaries for when to use AI and when to step back
Key evidence and examples
- The article recounts AT&T’s automation of telephone switching and the narrow functional definition of operator work.
- Operators connected calls, but also acted as emergency dispatchers, community information hubs, and human interfaces for local knowledge.
- Automation brought benefits such as privacy, speed, reliability, and efficiency, but also erased social infrastructure not captured in job descriptions.
- Kentz proposes questions about dependency, struggle, knowledge, judgment, and human connection.
Education relevance
Strongly relevant for AI policy, school implementation, institutional design, and AI literacy because it asks schools to evaluate relationships with knowledge and judgment, not just workflow efficiency.