Iazdi, Oz (2023): Vieses orto-heterodoxos e os algoritmos economistas do ChatGPT.
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Abstract
Recommendations for economic policies can be based on different theoretical perspectives and may present biases that are not always perceptible to the public. Identifying these biases is even more challenging when they are embedded in recommendations coming from sources with high technological and social disruptive potential, where a high level of impartiality is expected, such as contemporary large language models. Thus, a questionnaire was administered to economists affiliated with the Brazilian academic community to assess their perception of the presence of orthodox or heterodox biases in economic policy recommendations derived from interactions with ChatGPT in April 2023. The results showed that: i) there is still no consensus on the concepts of orthodoxy and heterodoxy in Brazil; ii) there are indications of a positive relationship between how self-proclaimed heterodox (orthodox) an economist is and how heterodox (orthodox) the perceived bias in an economic policy is; iii) it was not possible to identify a consistently orthodox or heterodox bias in ChatGPT's recommendations, which exhibited a good degree of impartiality.
Item Type: | MPRA Paper |
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Original Title: | Vieses orto-heterodoxos e os algoritmos economistas do ChatGPT |
English Title: | Ortho-Heterodox biases and the economist algorithms of ChatGPT |
Language: | Portuguese |
Keywords: | ChatGPT, orthodoxy, heterodoxy, biases, economic policy, artificial intelligence. |
Subjects: | A - General Economics and Teaching > A1 - General Economics > A13 - Relation of Economics to Social Values B - History of Economic Thought, Methodology, and Heterodox Approaches > B4 - Economic Methodology > B41 - Economic Methodology B - History of Economic Thought, Methodology, and Heterodox Approaches > B5 - Current Heterodox Approaches > B50 - General L - Industrial Organization > L8 - Industry Studies: Services > L86 - Information and Internet Services ; Computer Software |
Item ID: | 117655 |
Depositing User: | Oz Iazdi |
Date Deposited: | 25 Jun 2023 14:12 |
Last Modified: | 25 Jun 2023 14:12 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/117655 |