Campus AI Development Use case scenarios

Use case scenarios Discussion case 05 of 06

Discussion case 05

The week one group used most of the budget

The campus pools a single AI license across schools. In the first week of term, one research group’s agents, stuck in retry loops, consumed most of the month’s shared budget. Teaching assistants and student services lose access for the rest of the month.

A hypothetical composite for discussion, not an account of a real institution.

The tension

One viewCap every groupHard per-group budgets would have stopped this. Shared resources need enforced limits, not trust.
Another viewCaps penalize real researchResearch workloads are bursty by nature. Rigid caps slow the work the license was bought to support, and most groups never come close.

Questions for discussion

  1. 01Who should have been alerted, and when?
  2. 02Should teaching and student services have protected capacity?
  3. 03Is it fair to bill the group that caused the overrun?
  4. 04What is the right balance between alerts, soft limits and hard caps?
  5. 05Who decides priorities when the pool runs low mid-term?
What the framework suggests
  • This is the shared-pool failure described in the governance chapter.
  • Monitoring and access controls, not documentation, are the tiers that matter here.
  • Equity of access is one of the stakes: who loses first when the pool runs dry?
Where reasonable people disagree
  • Hard caps versus alerts and soft limits
  • Whether teaching gets priority over research
  • Who pays for overruns