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Turner and Tadepalli's paper of 27 June 2022 (arXiv v1) states that many decision-making procedures, not only optimal ones, are retargetable, and that retargetability is sufficient to cause power-seeking tendencies. Copy claim link
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Machine-checked, not reviewed by an editor Stated in source Supported
Supporting evidence: primary · 1 source
Date 2022-06-27 · publication Records dated 2022 → Role Articulation Register (kind of text) Nonfiction Scope and limits A formal result about the decision-making models the paper defines; it states that such training procedures may eventually produce power-seeking agents, not that they have.
The evidence 02 primary source Supports the claim
Parametrically Retargetable Decision-Makers Tend To Seek Power ↗ arXiv (2206.13477v1) · 2022-06-27
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Source excerpt “We discover that many decision-making functions are retargetable, and that retargetability is sufficient to cause power-seeking tendencies.” Location in source Abstract, PDF p. 1
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-31
Source details and check notes Authors Alexander Matt Turner; Prasad Tadepalli Version Retrieved for the candidate pack on 2026-10-29 (SHA-256 cea91b314d046b1650057d0386279b4b55ec8b7102a001074a597e74bb78b0af). arXiv v1 of 27 June 2022; v2 not compared. Canonical address Open the canonical source ↗ Accessed 2026-10-29 Language English (en) Attribution Alexander Matt Turner, Prasad Tadepalli, “Parametrically Retargetable Decision-Makers Tend To Seek Power”, 2022-06-27. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, arguments about catastrophic risk from advanced AI (research/risk-debate). The quotation (17 words) matched the text retrieved for the candidate pack on 2026-10-29. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. No human editorial review. primary source Supports the claim
Parametrically Retargetable Decision-Makers Tend To Seek Power ↗ arXiv (2206.13477v1) · 2022-06-27
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Cite the original source Cite the original document, not Selekoa. Check these details against it.
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Source excerpt “Eventually, highly retargetable training procedures may train real-world agents which seek power over humans.” Location in source Abstract, PDF p. 1
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-31
Source details and check notes Authors Alexander Matt Turner; Prasad Tadepalli Version Retrieved for the candidate pack on 2026-10-29 (SHA-256 cea91b314d046b1650057d0386279b4b55ec8b7102a001074a597e74bb78b0af). arXiv v1 of 27 June 2022; v2 not compared. Canonical address Open the canonical source ↗ Accessed 2026-10-29 Language English (en) Attribution Alexander Matt Turner, Prasad Tadepalli, “Parametrically Retargetable Decision-Makers Tend To Seek Power”, 2022-06-27. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, arguments about catastrophic risk from advanced AI (research/risk-debate). The quotation (14 words) matched the text retrieved for the candidate pack on 2026-10-29. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. No human editorial review. Status and meaning Editorial status. Not reviewed by an editor . An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.
Relation. A passage of the document meets the proposition’s criterion. The record documents what the text states, in its register (fiction and satire are labelled); it is not evidence that the proposition is true and implies no influence on or from another text.
Date. Date of the arXiv v1 submission.
Record ID rd-r02-turner-tadepalli-2022-retargetable