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Article: Regulating Artificial Intelligence in Finance: Putting the Human in the Loop

TitleRegulating Artificial Intelligence in Finance: Putting the Human in the Loop
Authors
KeywordsArtificial intelligence
Machine learning
Financial regulation
Black box
Issue Date2021
PublisherUniversity of Sydney, Sydney Law School. The Journal's web site is located at http://sydney.edu.au/law/slr/
Citation
The Sydney Law Review, 2021, v. 43 n. 1, p. 43-81 How to Cite?
AbstractThis article develops a framework for understanding and addressing the increasing role of artificial intelligence (‘AI’) in finance. It focuses on human responsibility as central to addressing the AI ‘black box’ problem — that is, the risk of an AI producing undesirable results that are unrecognised or unanticipated due to people’s difficulties in understanding the internal workings of an AI or as a result of the AI’s independent operation outside human supervision or involvement. After mapping the various use cases of AI in finance and explaining its rapid development, we highlight the range of potential issues and regulatory challenges concerning financial services AI and the tools available to address them. We argue that the most effective regulatory approaches to addressing the role of AI in finance bring humans into the loop through personal responsibility regimes, thus eliminating the black box argument as a defence to responsibility and legal liability for AI operations and decisions.
Persistent Identifierhttp://hdl.handle.net/10722/300108
ISSN
2022 Impact Factor: 0.8
SSRN

 

DC FieldValueLanguage
dc.contributor.authorBuckley, RP-
dc.contributor.authorZetzsche, DA-
dc.contributor.authorArner, DW-
dc.contributor.authorTang, BW-
dc.date.accessioned2021-06-03T04:24:14Z-
dc.date.available2021-06-03T04:24:14Z-
dc.date.issued2021-
dc.identifier.citationThe Sydney Law Review, 2021, v. 43 n. 1, p. 43-81-
dc.identifier.issn0082-0512-
dc.identifier.urihttp://hdl.handle.net/10722/300108-
dc.description.abstractThis article develops a framework for understanding and addressing the increasing role of artificial intelligence (‘AI’) in finance. It focuses on human responsibility as central to addressing the AI ‘black box’ problem — that is, the risk of an AI producing undesirable results that are unrecognised or unanticipated due to people’s difficulties in understanding the internal workings of an AI or as a result of the AI’s independent operation outside human supervision or involvement. After mapping the various use cases of AI in finance and explaining its rapid development, we highlight the range of potential issues and regulatory challenges concerning financial services AI and the tools available to address them. We argue that the most effective regulatory approaches to addressing the role of AI in finance bring humans into the loop through personal responsibility regimes, thus eliminating the black box argument as a defence to responsibility and legal liability for AI operations and decisions.-
dc.languageeng-
dc.publisherUniversity of Sydney, Sydney Law School. The Journal's web site is located at http://sydney.edu.au/law/slr/-
dc.relation.ispartofThe Sydney Law Review-
dc.rightsThis article was first published in the Sydney Law Review. © 2021 Sydney Law Review and authors.-
dc.subjectArtificial intelligence-
dc.subjectMachine learning-
dc.subjectFinancial regulation-
dc.subjectBlack box-
dc.titleRegulating Artificial Intelligence in Finance: Putting the Human in the Loop-
dc.typeArticle-
dc.identifier.emailArner, DW: douglas.arner@hku.hk-
dc.identifier.authorityArner, DW=rp01237-
dc.description.naturepublished_or_final_version-
dc.identifier.hkuros700003951-
dc.identifier.volume43-
dc.identifier.issue1-
dc.identifier.spage43-
dc.identifier.epage81-
dc.publisher.placeAustralia-
dc.identifier.ssrn3831758-
dc.identifier.hkulrp2021/016-

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