Topics — The twenty-eight kinds of claim this anthology files against — the primary axis of both the practice registry and the reading list, and the same twenty-eight for each (ADR-026). The filing rule is the point: take a domain topic when the claim is ABOUT the domain; a claim merely discovered in one still takes its kind. The axis organizes the record, it does not bound it: content the list cannot place is evidence the list is short (ADR-059).
Human–AI interaction — how people work with a model through an interface — prompting and steering controls, editing and co-writing tools, assistive and co-adaptive interfaces, how such interfaces are scored, and what lab studies of them can and cannot show.
1 of 129 THEORY documents. Back to the full index.
| # | Title | Summary | Status |
|---|---|---|---|
| THEORY-091 | Command-to-outcome mutual information scores an interface because it measures how reliably the operator’s input determines what happens at the chosen horizon, which rewards a learnable channel rather than an intuitive one | Reddy, Levine and Dragan (2022), LIT-503. The paper’s reason is that an intuitive interface makes commands less noisy. Its own results fit a narrower account: the score measures how much the operator’s input determines the state Δ steps later. Users adapt, so any consistent mapping scores well, and learned interfaces converge on both no perturbation and exact inversion. The account also explains the one failure: an assistant that overrides commands to prevent crashes lowers one-step influence and raises long-horizon influence. | Proposed |