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Agrawal, Gans, Goldfarb, “Prediction, Judgment and Complexity: A Theory of Decision Making and Artificial Intelligence” (2018-01) articulates M04. Treats AI as prediction technology and models how better prediction changes the value of judgment, the process of determining payoffs. Makes the fall in the cost of prediction the premise of the analysis. Draws the consequence of better prediction for a complement, human judgment. Copy claim link
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Supporting evidence: primary · 1 source
Date 2018-01 · publication Role Articulation Register (kind of text) Nonfiction Tier Tier 1. NBER working paper (core venue). Conditions (M04-03) Stated as an assumption of the model. (M04-04) Single-agent decision model with a risky and a safe action; holds while judgment is not too difficult; in complex environments results depend on whether prediction enables automated decision-making. Scope and limits (First passage) NBER Working Paper 24243, January 2018. (Second passage) NBER Working Paper 24243, January 2018. (Third passage) NBER Working Paper 24243, January 2018. Model result. It held M04’s tier-1 earliest-located role until 2026-10-25, when the same authors’ Harvard Business Review essay of November 2016 was added.
The evidence 03 primary source Supports the claim
Prediction, Judgment and Complexity: A Theory of Decision Making and Artificial Intelligence ↗ NBER Working Paper 24243 · 2018-01
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Source excerpt “We interpret recent developments in the field of artificial intelligence (AI) as improvements in prediction technology.” Location in source pdf page 2; abstract
Machine-checked · 2026-10-14
Source details and check notes Authors Ajay K. 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 64e4872abaea128fc37382d098bc0d4a5662fbdad641e38e010210169158a5ad. Canonical address Open the canonical source ↗ Accessed 2026-10-09 Language English (en) Attribution Ajay K. Agrawal, Joshua S. Gans, Avi Goldfarb, “Prediction, Judgment and Complexity: A Theory of Decision Making and Artificial Intelligence”, NBER Working Paper 24243, 2018-01. 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 M04-02 (research/economics-mainstream). The quotation (16 words) matched the retrieved current copy (SHA-256 64e4872abaea128fc37382d098bc0d4a5662fbdad641e38e010210169158a5ad) in the pack's verification. Re-checked at admission on 2026-10-14 against a copy retrieved that day. primary source Supports the claim
Prediction, Judgment and Complexity: A Theory of Decision Making and Artificial Intelligence ↗ NBER Working Paper 24243 · 2018-01
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Source excerpt “We proceed by first providing supportive evidence for our assumption that recent developments in AI overwhelmingly impact the costs of prediction.” Location in source pdf page 5; section 1 Introduction
Machine-checked · 2026-10-14
Source details and check notes Authors Ajay K. 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 64e4872abaea128fc37382d098bc0d4a5662fbdad641e38e010210169158a5ad. Canonical address Open the canonical source ↗ Accessed 2026-10-09 Language English (en) Attribution Ajay K. Agrawal, Joshua S. Gans, Avi Goldfarb, “Prediction, Judgment and Complexity: A Theory of Decision Making and Artificial Intelligence”, NBER Working Paper 24243, 2018-01. 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 M04-03 (research/economics-mainstream). The quotation (21 words) matched the retrieved current copy (SHA-256 64e4872abaea128fc37382d098bc0d4a5662fbdad641e38e010210169158a5ad) in the pack's verification. Re-checked at admission on 2026-10-14 against a copy retrieved that day. primary source Supports the claim
Prediction, Judgment and Complexity: A Theory of Decision Making and Artificial Intelligence ↗ NBER Working Paper 24243 · 2018-01
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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 “We show that prediction and judgment are generally complements, as long as judgment isn't too difficult.” Location in source pdf page 25; section 6 Conclusions
Machine-checked · 2026-10-14
Source details and check notes Authors Ajay K. 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 64e4872abaea128fc37382d098bc0d4a5662fbdad641e38e010210169158a5ad. Canonical address Open the canonical source ↗ Accessed 2026-10-09 Language English (en) Attribution Ajay K. Agrawal, Joshua S. Gans, Avi Goldfarb, “Prediction, Judgment and Complexity: A Theory of Decision Making and Artificial Intelligence”, NBER Working Paper 24243, 2018-01. 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 M04-04 (research/economics-mainstream). The quotation (16 words) matched the retrieved current copy (SHA-256 64e4872abaea128fc37382d098bc0d4a5662fbdad641e38e010210169158a5ad) 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 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. Cover "January 2018". Chapter in the NBER volume (2019). Checked in a current copy; an archive capture was not available, so earlier bytes are not authenticated.
Record ID ec-m04-agrawal-gans-goldfarb-2018-prediction-judgment-complexity-a