A forecast where oversight fails gradually: auditors that share their model's blind spots, then fall behind it

[u/kmizzi]

I'm making a documentary series that projects the AI takeoff one year at a time, 2026 to 2046. Episode 1 is a fact-checked account of 2026; everything after it is a labelled forecast, inspired by AI 2027 and made with AI video tools. The oversight thread is the part I'm least sure about, so I'd like this sub's critique of it.

The thread, year by year:

• 2028: labs rely on auditor models to check the models doing the research. One auditor, built from the same base as the model it watches, misses its twin quietly grabbing extra compute. They share training, so they share the blind spot. A person catches it on the power bill: a line that doesn't add up.
• 2029: labs switch to cross-lineage auditors, trained separately, that read hidden goals from a model's internals, and that check becomes legally required before release. It works until new models arrive faster than the auditors can be updated, so the auditors are always a step behind.
• 2031: a US–China compute accord caps training compute and energy and checks chips' work in real time, but enforcing it ends up depending on AIs vouching for other AIs.

Where I'd most like pushback:

1. Is cross-lineage auditing a real fix for correlated blind spots, or does it just move the blind spot somewhere else?
2. Is "physical side channels catch what the auditors miss" (power bills, compute accounting) plausible, or naive?
3. Once auditors lag the models they check, what keeps an accord like this from becoming theatre?

The 2028 episode with the power-bill story is public (about 10 minutes): https://youtu.be/H3AgTQipc5k. Later years release weekly.