1. What faculty across fields are noticing

Across early American literature, film and feminism, game studies, and narrative theory, faculty are describing the same phenomenon with increasing confidence: students are producing work, sometimes fluent and sometimes even sophisticated-sounding, without clear evidence that they have actually read the text, watched the film, or played the game in question.

  • This is not limited to one medium or discipline.
  • It appears in seminars as well as lecture courses.
  • It affects discussion, writing, and interpretive confidence.

What is striking is not ignorance, but detachment—a sense that students are operating adjacent to the work rather than inside it.

2. What COVID changed—and what never fully returned

The pandemic did not simply interrupt instruction; it reshaped the conditions under which effort and attention made sense.

  • Attention became intermittent, fragmented, and increasingly negotiated rather than assumed.
  • Emergency flexibility softened deadlines and expectations in ways that, for understandable reasons, were never fully reversed.
  • Presence—being there, staying with difficulty, finishing something—lost its status as a prerequisite rather than an optional virtue.

When in-person instruction returned, the infrastructure of obligation did not.

3. What AI did to this landscape (without causing it)

AI did not create these conditions, but it stabilized them.

  • It made it possible to sound like one had read, watched, or played without having done so.
  • It rewarded coherence, tone, and confidence more reliably than lived encounter.
  • It collapsed the difference between knowing about something and knowing through it.

This is why the problem cannot be reduced to cheating. What has eroded is the visibility of encounter itself.

Why Most Institutional Responses Miss the Problem

4. Why bans, policing, and exhortation fail

  • Banning AI addresses tools, not attention.
  • Policing cheating assumes bad faith rather than structural drift.
  • Motivational rhetoric cannot substitute for environments that make effort legible.
  • Lowering standards accelerates disengagement while preserving appearances.

What’s missing is not enforcement, but design.

What Agora-AI / ACP Changes at the Level of Environment

5. A different premise: encounter before performance

Agora does not begin by asking whether a student can produce the “right” interpretation, summary, or analysis. It begins by asking whether the student has actually encountered the work in a way that generates friction.

  • Claims are required before conclusions.
  • Interpretations must be anchored in moments, mechanics, or scenes.
  • Vague fluency is treated as a prompt for pressure, not acceptance.

The system does not accuse non-engagement; it makes it difficult to hide.

6. AI as a pressure mechanism rather than a shortcut

Within ACP, AI does not fill gaps or smooth over thin understanding.

  • Generic responses trigger increasingly specific requests: where, when, which passage, which choice.
  • Overconfident summaries invite competing interpretations rather than validation.
  • Absence becomes visible not through grading, but through interactional breakdown.

AI becomes an adversary of superficiality rather than its enabler.

Video Games as a Clear Example of the Model

7. Games treated as procedural texts, not content

Video games reveal the value of this approach because they cannot be meaningfully engaged without time, participation, and consequence.

  • Students are not asked what a game is “about,” but what it makes them do.
  • Mechanics, constraints, repetition, boredom, and failure become interpretive objects.
  • Meaning emerges from lived limitation rather than narrative summary.

These are not experiences that can be convincingly simulated by AI or secondary sources.

8. Anti-speed, anti-substitution design choices

Inside ACP, game courses can be structured to resist familiar shortcuts:

  • Assignments anchored to mid-game states rather than completion.
  • Reflection triggered by failure, confusion, or grind.
  • Comparative interpretation of mechanics rather than plot.

The design makes substitution impractical without explicitly forbidding it.

9. Collective interpretation without forced convergence

ACP preserves disagreement and plurality.

  • Multiple interpretations remain visible.
  • Decision trails show how understanding evolved or fractured.
  • AI tracks divergence without collapsing it into consensus.

This mirrors the best seminar dynamics—argument without premature closure.

What This Ultimately Restores (Quietly)

10. Not discipline, but legibility

Agora does not promise to motivate disengaged students or restore a vanished academic culture. Its wager is narrower and more realistic:

  • If encounter becomes the only viable starting point,
  • if effort becomes visible rather than assumed,
  • and if AI stops masking absence and starts exposing it,

then some forms of seriousness return without coercion.

Agora-AI is not a fast solution, and it does not scale in the way platform AI does. But it addresses a problem that speed, fluency, and automation cannot: the slow erosion of what it means to have actually been there.