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Agrawal, Gans, Goldfarb, “The Simple Economics of Machine Intelligence” (2016-11-17) articulates M04. Writing as economists, the authors treat machine intelligence as a prediction technology whose economic effect centres on a fall in the cost of prediction, and conclude that human judgment, a complement, becomes more valuable. Copy claim link
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Date 2016-11-17 · publication Wording attested 2016-11-25. Wayback capture of the article page. Role Earliest located Register (kind of text) Nonfiction Tier Tier 1. Tier 1. An essay in a magazine by economists, which the collection’s rule counts as tier 1: the authors write "as economists", and the author notes on the captured page give their academic positions (cross-family check of 2026-10-25). It develops an economic argument with examples; it is not a reply, comment or debate turn. Scope and limits Added on 2026-10-25 after the same-family and cross-family re-checks of the economics admission (maintainer decision of 2026-10-25). A short essay for managers; the authors’ formal model of prediction and judgment followed in their NBER working paper of January 2018. The essay allows that some judgment tasks will be reframed as predictions. The cross-family check of 2026-10-25 read the whole essay in the 2016-11-25 capture.
The evidence 02 primary source Supports the claim
The Simple Economics of Machine Intelligence ↗ Harvard Business Review · 2016-11-17
Archived copy, captured 2016-11-25: The Simple Economics of Machine Intelligence ↗
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Source excerpt “Machine intelligence is, in its essence, a prediction technology, so the economic shift will center around a drop in the cost of prediction.” Location in source Opening section, paragraph beginning "Today we are seeing similar hype"
Machine-checked · 2026-10-25
Source details and check notes Authors Ajay Agrawal; Joshua Gans; Avi Goldfarb Version Wayback capture 20161125124850 of the article page, read in full by the cross-family check of 2026-10-25. Current copy retrieved directly on 2026-10-25: the page shows the opening paragraph and carries the whole article text in its structured data (the page is generated per request; SHA-256 of that retrieval 776ad22c2265ae74dc87fd327fd07b7d60602b84c5bb94fcc50225abebbfbc7d). web.archive.org refused connections in the correction pass, so the capture was not re-read. Canonical address Open the canonical source ↗ Accessed 2026-10-25 Language English (en) Archive copy Open archived copy, captured 2016-11-25: The Simple Economics of Machine Intelligence ↗ . Captured 8 days after the recorded publication date. An archive copy shows only what the archive retrieved on 2016-11-25. It does not prove what the page said earlier, and it can differ from the copy checked on 2026-10-25.Attribution Ajay Agrawal, Joshua Gans, Avi Goldfarb, “The Simple Economics of Machine Intelligence”, Harvard Business Review, 2016-11-17. 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 Quoted by the cross-family check of 2026-10-25 from the capture of 2016-11-25. In the correction pass of 2026-10-25 the quotation matched the current copy of the article text; web.archive.org refused connections, so the capture was not re-read. primary source Supports the claim
The Simple Economics of Machine Intelligence ↗ Harvard Business Review · 2016-11-17
Archived copy, captured 2016-11-25: The Simple Economics of Machine Intelligence ↗
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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 “Using the language of economics, judgment is a complement to prediction and therefore when the cost of prediction falls demand for judgment rises.” Location in source Section "Judgment will become more valuable"
Machine-checked · 2026-10-25
Source details and check notes Authors Ajay Agrawal; Joshua Gans; Avi Goldfarb Version Wayback capture 20161125124850 of the article page, read in full by the cross-family check of 2026-10-25. Current copy retrieved directly on 2026-10-25: the page shows the opening paragraph and carries the whole article text in its structured data (the page is generated per request; SHA-256 of that retrieval 776ad22c2265ae74dc87fd327fd07b7d60602b84c5bb94fcc50225abebbfbc7d). web.archive.org refused connections in the correction pass, so the capture was not re-read. Canonical address Open the canonical source ↗ Accessed 2026-10-25 Language English (en) Archive copy Open archived copy, captured 2016-11-25: The Simple Economics of Machine Intelligence ↗ . Captured 8 days after the recorded publication date. An archive copy shows only what the archive retrieved on 2016-11-25. It does not prove what the page said earlier, and it can differ from the copy checked on 2026-10-25.Attribution Ajay Agrawal, Joshua Gans, Avi Goldfarb, “The Simple Economics of Machine Intelligence”, Harvard Business Review, 2016-11-17. 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 The cross-family check of 2026-10-25 read this section in the capture of 2016-11-25 and summarised it without quoting it; the same-family re-check quoted it from the current copy. In the correction pass of 2026-10-25 the quotation matched the current copy of the article text; web.archive.org refused connections, so the capture was not re-read. 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.
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Date. Page date "November 17, 2016" (Harvard Business Review online).
Record ID ec-m04-agrawal-gans-goldfarb-2016-simple-economics-of-machine-intelligence-a