[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117040-en":3,"doc-seo-117040-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117040,1649267921044,"Ava Thompson","https://us-avatar.wpscdn.com/avatar/1800007509477c92dfb?_k=1782875107921204101",8,"Research & Report","Accommodating machine learning algorithms in professional service firms","Machine learning algorithms, as a form of artificial intelligence, shape professional work by enabling predictions, interpretations, and algorithmic judgments that inform decisions. The central question is how professional tasks can be transformed to incorporate machine learning while addressing negative reactions from professionals whose work is altered by opaque and inscrutable algorithms. Original empirical analysis of accountants and lawyers identifies how firms accommodate machine learning, explaining what enables or inhibits cooperative AI adoption and implications for long-term impacts.","Author Accepted Manuscript  \nAccommodating machine learning algorithms in professional service firms  \n\n| Journal: | Organization Studies |\n| --- | --- |\n| Manuscript ID | OS-23-0002.R4 |\n| Manuscript Type: | Article |\n| Keywords: | professional service firms, algorithms, Interviews \u003C Research Design and Data Collection, machine learning, accounting, law, artificial intelligence |\n| Abstract: | Machine learning algorithms, as one form of artificial intelligence (AI), are significant for professional work because they create the possibility for some predictions, interpretations and judgements that inform decision making to be made by algorithms. However, little is known about whether it is possible to transform professional work to incorporate machine learning whilst also addressing negative responses from professionals whose work is changed by inscrutable algorithms. |\n\nOrganization Studies  \nDOI: 10. 1177/01708406241252930  \nPage 1 of 56 Author Accepted Manuscript  \n1 2  \n3 4  \n5 6  \n7 8  \n9  \n10  \n11  \n12  \n13  \n14  \n15  \n16  \n17  \n18  \n19  \n20  \n21  \n22  \n23  \n24  \n25  \n26  \n27  \n28  \n29  \n30  \n31  \n32  \n33  \n34  \n35  \n36  \n37  \n38  \n39  \n40  \n41  \n42  \n43  \n44  \n45  \n46  \n47  \n48  \n49  \n50  \n51  \n52  \n53  \n54  \n55  \n56  \n57  \n58  \n59  \n60  \n\n|  | Through original empirical analysis of the effects of machine learning algorithms on the work of accountants and lawyers, this paper identifies the role of accommodating machine learning algorithms in professional service firms. Accommodating machine learning algorithms involves strategic responses that both justify adoption in the context of the possibilities and new contributions of machine learning algorithms and respond to the algorithms’ limitations and opaque and inscrutable nature. The analysis advances understanding of the processes that enable or inhibit the cooperative adoption of AI in PSFs and develops insights relevant when examining the long-term impacts of machine learning algorithms as they become ever more sophisticated. |\n| --- | --- |\n|  |  |\n\nOrganization Studies  \nDOI: 10. 1177/01708406241252930  \n1 2  \n3 4  \n5 6  \n7 8  \n9  \n10  \n11  \n12  \n13  \n14  \n15  \n16  \n17  \n18  \n19  \n20  \n21  \n22  \n23  \n24  \n25  \n26  \n27  \n28  \n29  \n30  \n31  \n32  \n33  \n34  \n35  \n36  \n37  \n38  \n39  \n40  \n41  \n42  \n43  \n44  \n45  \n46  \n47  \n48  \n49  \n50  \n51  \n52  \n53  \n54  \n55  \n56  \n57  \n58  \n59  \n60  \nAuthor Accepted Manuscript Page 2 of 56  \nAccommodating machine learning algorithms in professional service firms  \nJames R. Faulconbridge, Lancaster University, [UK](UK j.faulconbridge@lancaster.ac.uk)[ j](UK j.faulconbridge@lancaster.ac.uk)[.faulconbridge@lancaster.ac.uk](UK j.faulconbridge@lancaster.ac.uk)[ ](UK j.faulconbridge@lancaster.ac.uk)Atif Sarwar, University of Liverpool, [UK](UK Atif.Sarwar@liverpool.ac.uk)[ ](UK Atif.Sarwar@liverpool.ac.uk)[Atif.Sarwar@liverpool.ac.uk](UK Atif.Sarwar@liverpool.ac.uk)  \nMartin Spring, Lancaster University, [UK](UK m.spring@lancaster.ac.uk)[ ](UK m.spring@lancaster.ac.uk)[m.spring@lancaster.ac.uk](UK m.spring@lancaster.ac.uk)  \nCorresponding author: James R. Faulconbridge, Department of Organisation, Work and Technology, Lancaster University Management School, Lancaster, LA1 4YX, UK. Email:  \n[j](j.faulconbridge@lancaster.ac.uk)[.faulconbridge@lancaster.ac.uk](j.faulconbridge@lancaster.ac.uk)  \nOrganization Studies  \nDOI: 10. 1177/01708406241252930  \nPage 3 of 56  \n12345678910111213141516 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60  \nAuthor Accepted Manuscript  \nAccommodating machine learning algorithms in professional service firms  \nAbstract  \nMachine learning algorithms, as one form of artificial intelligence, are significant for professional work because they create the possibility for some predictions, interpretations and judgements that inform decision making to be made by algorithms. However, little is known about whether it is possible to transform p","cbCailTN8uqyvTVs","https://ap.wps.com/l/cbCailTN8uqyvTVs","pdf",808976,1,58,"English","en",105,"# Introduction\n## Background: technology and professional work\n## Research question and approach\n## Findings: accommodating machine learning in PSFs\n## Implications for adoption and long-term impacts\n# Conclusion","[{\"question\":\"What is the paper’s main focus on machine learning in professional service firms?\",\"answer\":\"It examines how professional service firms can accommodate machine learning algorithms when deploying AI changes professionals’ work and introduces opaque decision-making.\"},{\"question\":\"Why are negative responses from professionals important in this research?\",\"answer\":\"The paper addresses whether professionals accept or resist transformations caused by inscrutable algorithms, and how firms respond strategically to those limitations.\"},{\"question\":\"What methods does the paper use to understand these effects?\",\"answer\":\"It relies on original empirical analysis of the effects of machine learning algorithms on the work of accountants and lawyers.\"}]","Accommodating machine learning algorithms in professional service firms | 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