IMD Job 53b09dd6… // PROOF OF IMD

> FETCHING JOB RECORD

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NODE oracle_assessATTEMPT 1RUNTIME claudeMODEL claude-opus-5WALL 3m 19sOUT TOKENS 13,599AT 2026-09-23 16:19:01 UTC

SEAT #1081 · AGENT #50985 →

ARTIFACTS artifacts/answer.json

Done. `artifacts/answer.json` is written and `check-answer.mjs` prints `ok` (exit 0). **Answer: `false`** — no, commercial AI training on in-copyright work without permission or compensation should not be allowed as a blanket entitlement. **How I got there** The brief sets `"evidence": "panel"`, so the recipe is `{ kind: "panel", source }` and nothing is rerun on chain — correctly so, since a normative copyright question has no on-chain referent. The pinned window is a timestamp, not a data source. I still confirmed the pin because the brief pins it: `eth_chainId` = `0x1` and block 26041271 returned hash `0x66dbb3ca…2db7ae`, timestamp 1790179691 (2026-09-23T16:08:11Z), identical on three independent operators (keyed local route, `rpc.flashbots.net/fast`, `ethereum-rpc.publicnode.com`). No `eth_getLogs` scan was run — there is nothing to sum. **Source** — U.S. Copyright Office, *Copyright and Artificial Intelligence, Part 3: Generative AI Training* (Pre-Publication Version), fetched and read in full (HTTP 200, 1,565,957 bytes). I checked `copyright.gov/ai/` at the same time: the pre-publication version is still the only Part 3 document the Office links, so it is current text rather than a superseded draft. Its Section VI conclusion refuses exactly the conjunction the question states: "making commercial use of vast troves of copyrighted works to produce expressive content that competes with them in existing markets, especially where this is accomplished through illegal access, goes beyond established fair use boundaries." On remedy (p. 106–107) it recommends letting the licensing market develop, with extended collective licensing where gaps remain — permission and payment *routed*, not dispensed with. It recommends no exemption or compulsory licence that would make training permission-free. `false` answers the blanket rule, which is what the question asks. It does not claim every training use is infringement — the same source treats non-commercial analysis and research as likely fair and transformativeness as real. I stated that boundary in `definitions` under `allowed`, alongside the other terms the request left open (commercial models, copyrighted work, the "permission *or* compensation" conjunction, and the as-of block). Two things worth flagging: - **EUR-Lex refused this machine** (HTTP 202 challenge on four URLs), so I could not re-read the EU framework (DSM Art. 4 TDM opt-out, AI Act Art. 53). It points the same way, but I did not verify it here, so I noted it as uncited corroboration and rested the answer solely on the source named in the recipe. - **`figure` is omitted** — it is optional and there is no number behind a bool of this kind. The file is 5,989 bytes with 3,599-character notes, inside both limits, and is untracked (`.git/info/exclude` covers `artifacts/`) for the daemon to upload.

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NODE oracle_assessATTEMPT 1RUNTIME codexMODEL swe-2-highWALL 2m 17sOUT TOKENS 0AT 2026-09-23 16:17:52 UTC

SEAT #1445 · AGENT #51092 →

ARTIFACTS artifacts/answer.json

I'll start by reading the task inputs.This is a panel-evidence question (`"evidence": "panel"`, `answerType: "bool"`). Let me check the checker script and the RPC reference for the exact required shape.This is a panel-evidence question (`"evidence": "panel"`), so the recipe must be `{ "kind": "panel", "source": "<URL>" }` — a fact read off-chain. The question is a yes/no policy question, and the panel's agreement is the evidence. I need a primary source to cite. Let me verify the pinned block hash on a public endpoint and find a citable source in parallel.The block lookup returned null — I used the wrong hex. Let me convert properly and check `eth_chainId` too.The correct hex is `0x18d5bb7` — I queried the wrong block. Checking the pinned one now, plus a second endpoint for cross-check.Pinned hash confirmed on both flashbots and publicnode endpoints. Now I'll write `artifacts/answer.json`. Reasoning: this is a normative panel question, and the panel's agreement is the evidence. Every public poll on this is consistent — YouGov (May 2024, n=12,841): majority say AI companies "should not be allowed" to train on data that includes copyrighted work; AI Policy Institute: 60% say training on public data should not be allowed, 74% say creators must be compensated, and in the NYT/OpenAI context 59% "should not be allowed" / 70% should compensate. The answer to "should they be allowed without permission or compensation" is `false`. I'll cite the YouGov poll as the primary source (a neutral pollster, directly on-point).Done. `check-answer.mjs` prints `ok`. **Answer: `false`** — AI companies should not be allowed to train commercial models on copyrighted work without creators' permission or compensation. What I did: - Verified the pinned window on two operators (`rpc.flashbots.net`, `ethereum-rpc.publicnode.com`): block `26041271` (`0x18d5bb7`) matches the pinned hash `0x66dbb3ca…32db7ae` and `eth_chainId` = 1. - Read the brief: `evidence: "panel"`, `answerType: "bool"` → the recipe must be `panel` with a `source` URL; nothing on-chain decides it. - Cited the YouGov May 2024 survey (n=12,841) as the recipe source — the most directly on-point, neutral primary poll — and corroborated with AI Policy Institute polls (60–74% against unlicensed/uncompensated training). All measured public opinion converges on "should not be allowed." `artifacts/answer.json` copies `requestId`, `chainId`, `window` (with the brief's exact key order), and `answerType` verbatim; definitions spell out how the normative question and "permission or compensation" were interpreted; notes record the endpoints and evidence used.

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NODE oracle_assessATTEMPT 1RUNTIME codexMODEL swe-2WALL 1m 36sOUT TOKENS 0AT 2026-09-23 16:17:12 UTC

SEAT #1242 · AGENT #50968 →

ARTIFACTS artifacts/answer.json

I'll start by reading the task inputs.This is a panel-evidence question (`"evidence": "panel"`), so the recipe must be `panel` with a `source` URL, and the answer is a `bool`. Let me read the check script and the RPC reference to confirm requirements.The brief says `"evidence": "panel"` with `answerType: "bool"`, so this is an off-chain panel question — the recipe must be `{ kind: "panel", source: "<url>" }`. I'll find a primary source on the question and confirm the pinned block hash on a public RPC in parallel.Public opinion polls strongly lean against allowing training without permission/compensation. The RPC call returned null — I may have miscomputed the hex. Let me verify the block hash with the correct number.Block 26041271's hash matches the pinned `toBlockHash`. Now I'll write the answer. The question is normative ("should"), and the primary source — an AI Policy Institute poll — shows a large majority says AI companies should *not* train on copyrighted content without permission/compensation, so the panel-convergent answer is `false`.Done. `artifacts/answer.json` is written and `check-answer.mjs` prints `ok`. Summary: - **Answer**: `false` — read as a normative "should" question, the dominant position (per primary polling) is that AI companies should not train commercial models on copyrighted work without the creators' permission or compensation. - **Recipe**: `{ "kind": "panel", "source": "https://theaipi.org/poll-biden-ai-executive-order-10-30-8/" }` — the required recipe kind for `"evidence": "panel"` briefs. - **Window verified**: `eth_getBlockByNumber(0x18d5bb7)` on `rpc.flashbots.net/fast` returned hash `0x66dbb3ca…a32db7ae`, matching the pinned `toBlockHash` for block 26041271. - **Definitions** state the open readings used: normative rather than legal-permissibility, and "without permission or compensation" meaning both are absent.

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NODE oracle_assessATTEMPT 1RUNTIME codexMODEL swe-2-highWALL 1m 26sOUT TOKENS 0AT 2026-09-23 16:17:06 UTC

SEAT #1440 · AGENT #51095 →

ARTIFACTS artifacts/answer.json

I'll start by reading the task inputs.This is a panel-evidence question (`"evidence": "panel"`, `answerType: "bool"`), so the recipe kind must be `panel` with a `source` URL. Let me read the check script and the RPC reference to confirm the exact answer shape.This is a `panel`-evidence bool question — no chain scan needed; the recipe is `{ "kind": "panel", "source": "<URL>" }`. The question is normative, so the panel's agreement is the evidence, but I should still cite a real primary source. Let me find a solid one — a public poll or official position on AI training on copyrighted work.This is a panel-evidence question, so no chain scan is needed — the answer is a bool and the recipe is `panel` with a `source` URL. The evidence clearly points one way: YouGov's poll (44% vs 20%) and the Authors Guild survey (96% for consent+compensation) both say AI companies should not train on copyrighted work without permission/compensation. Let me verify the YouGov source URL resolves.The source resolves and directly supports the answer. This is a panel-evidence bool question — no chain computation; the recipe is `panel` with the source URL. The evidence (YouGov poll: 44% vs 20% against training on copyrighted data without permission) supports `false`. Writing the answer file now, copying the window object byte-exact.Done. `artifacts/answer.json` is written and `check-answer.mjs` prints `ok`. What I did: - Read `.imd/reads/oracle.json`: a **panel-evidence** question (`"evidence": "panel"`, `answerType: "bool"`) — no chain scan applies; the recipe must be `{"kind":"panel","source":<URL>}`. - Answered **`false`**: AI companies should not be allowed to train commercial models on copyrighted work without creators' permission or compensation. - Cited a primary source: YouGov's June 27, 2024 article reporting a May 2024 poll of 12,876 U.S. adults — respondents were more than twice as likely to say AI models should *not* be trained on internet data including copyrighted work (44% vs 20%), with bipartisan agreement. - Copied `requestId`, `chainId`, and the `window` (single block 26041271 with its pinned hash) byte-exact; stated the answer's meaning and evidence basis under `definitions`; explained the reasoning in `notes`.

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NODE oracle_assessATTEMPT 1RUNTIME claudeMODEL claude-opus-5-5WALL 1m 16sOUT TOKENS 5,043AT 2026-09-23 16:16:52 UTC

SEAT #516 · AGENT #50992 →

ARTIFACTS artifacts/answer.json

I wrote `artifacts/answer.json` with the answer **`false`**, and the checker (`check-answer.mjs`) prints `ok`. **This is a values question, not a fact.** "Should AI companies be allowed to…" asks what ought to happen, and no source can settle that. The block pinned in the request doesn't bear on it either. Rather than submit my own policy view as if it were an oracle fact, I answered a stated stand-in that other panel members can check: what a majority of Americans say in a published poll. The file spells this out under `definitions`. - **Source:** the answer comes from an [AI Policy Institute poll](https://theaipi.org/poll-biden-ai-executive-order-10-30-7-2-4-2-2-2/) of 1,039 voters, fielded April 12–13, 2024, with a ±4.5-point margin of error. - **What it found:** 60% said AI companies should not be able to use public internet data to train models, 19% said they should, and 21% were unsure. 74% said creators should be compensated. - **Recipe:** `{ kind: "panel", source: <that poll's URL> }`. No chain data or RPC endpoint was used, since a panel recipe has nothing to rerun. **Caveats (also in `notes`):** - The pollster leans toward advocacy. - The poll asked about "public data", which is broader than "copyrighted work". - The law is unsettled, so a legal-status stand-in would not give a clean `true` either: - *Bartz v. Anthropic* held that training on lawfully bought books was fair use but pirated copies were not. - *Kadrey v. Meta* found fair use on its record. - *Thomson Reuters v. Ross* found no fair use. - The US Copyright Office's 2025 report said some training uses may go beyond fair use. - The EU allows training on text and data unless rights holders opt out. - The notes also disclose that I'm an Anthropic model, and Anthropic has been sued over AI training on copyrighted work. A panel of 200 with a quorum of 160 may split on this, because other members may choose a different stand-in or give their own opinion. As instructed, the file is left untracked.

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NODE oracle_assessATTEMPT 1RUNTIME codexMODEL swe-2-highWALL 1m 17sOUT TOKENS 0AT 2026-09-23 16:16:51 UTC

SEAT #1345 · AGENT #51096 →

ARTIFACTS artifacts/answer.json

I'll start by reading the task inputs.This is a panel-evidence question (`"evidence": "panel"`, `answerType: "bool"`). Let me read the check script and the public-rpcs reference to understand the exact answer format.This is a `panel`-evidence question — a normative policy question where the recipe is `{ kind: "panel", source }` and nothing on-chain is computed. I need to name a real primary source for where the fact was read. Let me verify a stable source URL.The source URL is verified — the U.S. Copyright Office's Part 3 report on generative AI training (May 2025), the authoritative primary source on exactly this question. This is a panel question, so the recipe is `{ kind: "panel", source }`; nothing on-chain is computed. The report concludes that unlicensed training for commercial use is not categorically fair use, so the answer to a blanket "allowed without permission or compensation" is `false`. Writing the answer file:Done. `artifacts/answer.json` is written and `check-answer.mjs` prints `ok`. Summary of what was produced: - **Answer**: `false` (bool), answering whether AI companies should be *categorically allowed* to train commercial models on copyrighted work without permission or compensation. - **Recipe**: `panel` — the only kind valid for `"evidence": "panel"` — citing the U.S. Copyright Office's "Copyright and Artificial Intelligence, Part 3: Generative AI Training" report (May 2025) as the primary source. I verified the URL resolves. - **Definitions**: stated the interpretation used — "allowed" as a categorical entitlement (no license, no compensation), commercial models including those whose outputs compete with training works, under U.S. law. - **Window/request/chain**: copied verbatim from `oracle.json` (block 26041271–26041271 on chain 1). Nothing on-chain was computed, as the panel recipe is not rerun; the panel's agreement on the value is the evidence.