Choose an institution to see its records and dossier, or choose a topic.
Through year 2027 · all records, including scheduled dates 2026 2025 2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2008 2005 1965 Show Organisations and infrastructure All types Organisation Person Document Concept Infrastructure Public body Reset filters
94 people, organisations and other records · 122 relationships · 34 claims about a valueEverything recorded up to the chosen year, whether or not still in effect · Undated records included
Claim and evidence Close ×
Agrawal, Gans, Goldfarb, “Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction” (2019-02) bears on M03. The authors call AI a general-purpose technology because prediction is an input into decisions across many occupations. Copy claim link
Copy claim reference
Machine-checked, not reviewed by an editor Stated in source Supported
Supporting evidence: primary · 1 source
Date 2019-02 · publication Role Context Register (kind of text) Nonfiction Missing element No statement that measured productivity gains lag adoption. Tier Tier 1. NBER working paper (core venue). Scope and limits GPT label only.
The evidence 01 primary source Supports the claim
Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction ↗ NBER Working Paper 25619 · 2019-02
Copy source reference
Cite the original source Cite the original document, not Selekoa. Check these details against it.
Copy APA
Download BibTeX Download RIS Download CSL-JSON
Source excerpt “This wide breadth of application means that developments in artificial intelligence represent what Bresnahan and Trajtenberg (1995) called a "general purpose technology." Location in source pdf page 3; introduction (printed p. 1)
Machine-checked · 2026-10-14
Source details and check notes Authors Ajay Agrawal; Joshua S. 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 dbd015967a47f77a41ff8028f5cc8208c3bb0e8cb44d6b1cc9be04f7df9c2450. Journal version not retrieved. Agrawal, A., Gans, J. S., & Goldfarb, A. (2019). Artificial intelligence: The ambiguous labor market impact of automating prediction. Journal of Economic Perspectives, 33(2), 31–50. https://doi.org/10.1257/jep.33.2.31 Canonical address Open the canonical source ↗ Accessed 2026-10-09 Language English (en) Attribution Ajay Agrawal, Joshua S. Gans, Avi Goldfarb, “Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction”, NBER Working Paper 25619, 2019-02. 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 M03-07 (research/economics-mainstream). The quotation (22 words) matched the retrieved current copy (SHA-256 dbd015967a47f77a41ff8028f5cc8208c3bb0e8cb44d6b1cc9be04f7df9c2450) in the pack's verification. Re-checked at admission on 2026-10-14 against a copy retrieved that day. 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 bears on the proposition without meeting its criterion; the record names the missing element. It is not an articulation and implies no influence.
Date. Cover "February 2019". Journal version: JEP 33(2), 2019, pp. 31–50 (abstract page jep2019-agg). Checked in a current copy; an archive capture was not available, so earlier bytes are not authenticated.
Record ID ec-m03-agrawal-gans-goldfarb-2019-ambiguous-labor-market-impact-b