Claim · 2019-05 · publication · Stated in source · Supported

Agrawal, Gans and Goldfarb (2019), summarising a discussant’s comment that humans must tell machines what to optimise, attribute the name “value-loading problem” for that task to Bostrom (2014).

One recorded claim. The claim panel gives its qualification, the source passages with their place in each source, and how it was checked.

What it connects

Introduction to "The Economics of Artificial Intelligence: An Agenda" → attributes to → Superintelligence: Paths, Dangers, Strategies

Where it appears

No collection page holds this claim. It is listed with its records in the explorer.

Claim and evidence

Introduction to "The Economics of Artificial Intelligence: An Agenda"attributes to ↓Superintelligence: Paths, Dangers, Strategies

Machine-checked, not reviewed by an editorStated in sourceSupported

Supporting evidence: primary · 1 source

Date: 2019-05 · publication Records dated 2019 →
Kind of attribution: Attributes a term or concept to the work

Scope and limitsThe citing text's attribution of a term while summarising a discussant's comment; not evidence that the discussant drew on Bostrom (2014) or that the editors endorse the book.

The evidence 01

primary sourceSupports the claim

Introduction to "The Economics of Artificial Intelligence: An Agenda"

NBER volume chapter (University of Chicago Press) · 2019-05

Cite the original source

Cite the original document, not Selekoa. Check these details against it.

Source excerpt

“Bostrom (2014) describes this as the value-loading problem.”

Location in source PDF p. 10, summary of the volume's chapters

Machine-checked · 2026-10-31

Source details and check notes

Authors: Ajay Agrawal; Joshua Gans; Avi Goldfarb
Version: Full text. Current copy retrieved directly on 2026-10-09; no archive capture (Wayback unreachable), so earlier bytes are not authenticated. SHA-256 176dbcbd8a7e924d0f6d7506a9c04fb862a37a99ff3abe07670e7ba892a62839.
Canonical address: Open the canonical source ↗
Accessed: 2026-10-09
Language: English (en)
Attribution: Ajay Agrawal, Joshua Gans, Avi Goldfarb, “Introduction to "The Economics of Artificial Intelligence: An Agenda"”, NBER volume chapter (University of Chicago Press), 2019-05.
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, key papers (research/key-papers). The quotation (8 words) matched the text retrieved for the candidate pack on 2026-10-28 (research/key-papers/verification.json). Matching ignored differences of whitespace, case, quotation marks, dashes and line-break hyphens, so the source’s typography can differ. A cross-family machine check (2026-10-30, item B003) found the attribution at its locator and in the citing text’s reference entry. 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 document expressly attributes an argument, concept, term, finding or approach to another work, in its own words; the kind of attribution is recorded. The record is the citing document’s claim. It is not evidence that the cited work originated the idea, that the attribution is accurate, or of influence beyond the passage. Citation alone is recorded as a citation.

Date. Date of the citing text as the dataset records it (May 2019).

Record ID kp-shaping-agg-intro-bostrom