---
id: "entity-prediction-machines"
type: "entity"
source_timestamps: ["¶5"]
tags: ["economics-literature", "adjacent-literature"]
related: ["concept-complementarity", "entity-ajay-agrawal", "entity-joshua-gans", "entity-avi-goldfarb"]
entityType: "other"
canonicalName: "Prediction Machines"
aliases: ["Prediction Machines: The Simple Economics of Artificial Intelligence"]
sources: ["futures"]
sourceVaultSlug: "hbr-seg-futures"
originDay: 2
articleStem: "hbr-cl-84-big-tech-capability-crisis"
sourceUrl: "https://hbr.org/2026/06/big-techs-looming-capability-crisis"
sourceTitle: "Big Tech’s Looming Capability Crisis"
---
# Prediction Machines (book)

## Prediction Machines (book)

**Role in source:** the intellectual foundation for the article's economics. A book by [[entity-ajay-agrawal|Ajay Agrawal]], [[entity-joshua-gans|Joshua Gans]], and [[entity-avi-goldfarb|Avi Goldfarb]] that explains the economics of AI — specifically [[concept-complementarity|complementarity]]: how cheaper prediction raises the value of judgment and accountability.

*(entityType recorded as "other" — a publication — since the fixed enum has no "publication" value.)*

> Enrichment: the central adjacent framework for the complementarity thesis; the economics book that formalized the "prediction gets cheaper, complements get more valuable" view of AI.