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The BIS Annual Economic Report 2024 (chapter III) states that large language models and generative AI hold promise for nowcasting by turning unstructured data into structured series, and that sentiment indices derived from such data can substantially improve forecasts of unemployment, GDP growth and inflation. Copy claim link
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Date 2024-06-30 · publication Records dated 2024 → Role Articulation Register (kind of text) Nonfiction Scope and limits ‘Most developed’ is an editorial judgement among this group’s located texts (a full box on nowcasting). The chapter also states limits on AI in macroprudential use given scarce crisis data.
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III. Artificial intelligence and the economy: implications for central banks ↗ Bank for International Settlements · 2024-06-30
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Source excerpt “LLMs and gen AI hold promise to overcome both bottlenecks (see Box D).” Location in source Section ‘Harnessing AI for policy objectives’, paragraph beginning ‘These capabilities are particularly promising for nowcasting’
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors Bank for International Settlements Version Retrieved for the candidate pack on 2026-11-02 (SHA-256 edfc9e2f0596108f4964c662268212890d005028eea3e11e9d45d1f90008adf7). Retrieved again at admission on 2026-11-06 (same file). BIS HTML chapter as served on 2026-11-02 (requested at https://www.bis.org/publ/arpdf/ar2024e3.htm, redirected to the address given) Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution Bank for International Settlements, “III. Artificial intelligence and the economy: implications for central banks”, 2024-06-30. 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, AI and money (research/ai-money). The quotation (13 words) matched a fresh retrieval of 2026-11-06 (the same file the candidate pack read). Matching ignored differences of whitespace, case, quotation marks, dashes, line-break hyphens and Unicode compatibility forms. No human editorial review. primary source Supports the claim
III. Artificial intelligence and the economy: implications for central banks ↗ Bank for International Settlements · 2024-06-30
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Source excerpt “Such sentiment indices can substantially improve forecasts for key macroeconomic quantities, such as unemployment, GDP growth and inflation.” Location in source Box D, paragraph beginning ‘Nowcasting models could benefit from deep neural networks’ embeddings’
How it was read Retrieved directly from the publisher
Machine-checked · 2026-11-06
Source details and check notes Authors Bank for International Settlements Version Retrieved for the candidate pack on 2026-11-02 (SHA-256 edfc9e2f0596108f4964c662268212890d005028eea3e11e9d45d1f90008adf7). Retrieved again at admission on 2026-11-06 (same file). BIS HTML chapter as served on 2026-11-02 (requested at https://www.bis.org/publ/arpdf/ar2024e3.htm, redirected to the address given) Canonical address Open the canonical source ↗ Accessed 2026-11-06 Language English (en) Attribution Bank for International Settlements, “III. Artificial intelligence and the economy: implications for central banks”, 2024-06-30. 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, AI and money (research/ai-money). The quotation (18 words) matched a fresh retrieval of 2026-11-06 (the same file the candidate pack read). Matching ignored differences of whitespace, case, quotation marks, dashes, line-break hyphens and Unicode compatibility forms. No human editorial review. Status and meaning Editorial status. Machine-checked . Machines found this record and checked it against its sources; no person accepted it individually. Each evidence record above shows how it was checked.
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Record ID am-u05-bis-2024-aer-ch3