Towards an Equitable Digital Society: Artificial Intelligence (AI) and Corporate Digital Responsibility (CDR)
In the digital era, we witness the increasing use of artificial intelligence (AI) to solve problems, while improving productivity and efficiency. Yet, inevitably costs are involved with delegating power to algorithmically based systems, some of whose workings are opaque and unobservable and thus ter...
Gespeichert in:
Veröffentlicht in: | Society (New Brunswick) 2021-06, Vol.58 (3), p.179-188 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 188 |
---|---|
container_issue | 3 |
container_start_page | 179 |
container_title | Society (New Brunswick) |
container_volume | 58 |
creator | Elliott, Karen Price, Rob Shaw, Patricia Spiliotopoulos, Tasos Ng, Magdalene Coopamootoo, Kovila van Moorsel, Aad |
description | In the digital era, we witness the increasing use of artificial intelligence (AI) to solve problems, while improving productivity and efficiency. Yet, inevitably costs are involved with delegating power to algorithmically based systems, some of whose workings are opaque and unobservable and thus termed the “black box”. Central to understanding the “black box” is to acknowledge that the algorithm is not mendaciously undertaking this action; it is simply using the recombination afforded to scaled computable machine learning algorithms. But an algorithm with arbitrary precision can easily reconstruct those characteristics and make life-changing decisions, particularly in financial services (credit scoring, risk assessment, etc.), and it could be difficult to reconstruct, if this was done in a fair manner reflecting the values of society. If we permit AI to make life-changing decisions, what are the opportunity costs, data trade-offs, and implications for social, economic, technical, legal, and environmental systems? We find that over 160 ethical AI principles exist, advocating organisations to act responsibly to avoid causing digital societal harms. This maelstrom of guidance, none of which is compulsory, serves to confuse, as opposed to guide. We need to think carefully about how we implement these algorithms, the delegation of decisions and data usage, in the absence of human oversight and AI governance. The paper seeks to harmonise and align approaches, illustrating the opportunities and threats of AI, while raising awareness of Corporate Digital Responsibility (CDR) as a potential collaborative mechanism to demystify governance complexity and to establish an equitable digital society. |
doi_str_mv | 10.1007/s12115-021-00594-8 |
format | Article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8202049</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2543704904</sourcerecordid><originalsourceid>FETCH-LOGICAL-c474t-3c22b24f3d52f0ca6f230431629f0b9673be2c2fbcbd0cc8f70df8f851a26b1a3</originalsourceid><addsrcrecordid>eNp9kcFvFCEUxomxsevqP-DBTOJlexiFBwwzHkw226qbNDGp9UyAgZVmdtgCY7P_falbW-tBLhDe7_vee_kQekPwe4Kx-JAIEMJrDKTGmHesbp-hGeloUzMB_DmaYcJEDZiQY_QypStcDgB7gY4pI6wjADO0vQw3KvapUmN1dj35rPRgq1O_Ka-h-h6Mt3n_sVrG7J03vvytx2yHwW_saGy1WK5PirSvViHuQlT5UXth0y6MyWs_-LyvFqvTi5NX6MipIdnX9_cc_fh8drn6Wp9_-7JeLc9rwwTLNTUAGpijPQeHjWocUMwoaaBzWHeNoNqCAaeN7rExrRO4d61rOVHQaKLoHH06-O4mvbW9sWOOapC76Lcq7mVQXj6tjP6n3IRfsgUMmHXFYHFvEMP1ZFOWW59M2VuNNkxJAmdUFLBMNUfv_kGvwhTHsl6hOBei5fzOEA6UiSGlaN3DMATLuzTlIU1Z0pS_05RtEb39e40HyZ_4CkAPQCqlcWPjY-__2N4Cwneq2A</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2555778559</pqid></control><display><type>article</type><title>Towards an Equitable Digital Society: Artificial Intelligence (AI) and Corporate Digital Responsibility (CDR)</title><source>SpringerLink Journals</source><source>Worldwide Political Science Abstracts</source><source>Sociological Abstracts</source><creator>Elliott, Karen ; Price, Rob ; Shaw, Patricia ; Spiliotopoulos, Tasos ; Ng, Magdalene ; Coopamootoo, Kovila ; van Moorsel, Aad</creator><creatorcontrib>Elliott, Karen ; Price, Rob ; Shaw, Patricia ; Spiliotopoulos, Tasos ; Ng, Magdalene ; Coopamootoo, Kovila ; van Moorsel, Aad</creatorcontrib><description>In the digital era, we witness the increasing use of artificial intelligence (AI) to solve problems, while improving productivity and efficiency. Yet, inevitably costs are involved with delegating power to algorithmically based systems, some of whose workings are opaque and unobservable and thus termed the “black box”. Central to understanding the “black box” is to acknowledge that the algorithm is not mendaciously undertaking this action; it is simply using the recombination afforded to scaled computable machine learning algorithms. But an algorithm with arbitrary precision can easily reconstruct those characteristics and make life-changing decisions, particularly in financial services (credit scoring, risk assessment, etc.), and it could be difficult to reconstruct, if this was done in a fair manner reflecting the values of society. If we permit AI to make life-changing decisions, what are the opportunity costs, data trade-offs, and implications for social, economic, technical, legal, and environmental systems? We find that over 160 ethical AI principles exist, advocating organisations to act responsibly to avoid causing digital societal harms. This maelstrom of guidance, none of which is compulsory, serves to confuse, as opposed to guide. We need to think carefully about how we implement these algorithms, the delegation of decisions and data usage, in the absence of human oversight and AI governance. The paper seeks to harmonise and align approaches, illustrating the opportunities and threats of AI, while raising awareness of Corporate Digital Responsibility (CDR) as a potential collaborative mechanism to demystify governance complexity and to establish an equitable digital society.</description><identifier>ISSN: 0147-2011</identifier><identifier>EISSN: 1936-4725</identifier><identifier>DOI: 10.1007/s12115-021-00594-8</identifier><identifier>PMID: 34149122</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Algorithms ; Artificial intelligence ; Data Use ; Decisions ; Delegation ; Ethics ; Financial services ; Governance ; Intelligence ; Legal system ; Mathematics ; Opportunity costs ; Original ; Original Article ; Political Science ; Productivity ; Responsibility ; Risk assessment ; Scores ; Social Sciences ; Society ; Sociology</subject><ispartof>Society (New Brunswick), 2021-06, Vol.58 (3), p.179-188</ispartof><rights>The Author(s) 2021</rights><rights>The Author(s) 2021.</rights><rights>The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-3c22b24f3d52f0ca6f230431629f0b9673be2c2fbcbd0cc8f70df8f851a26b1a3</citedby><cites>FETCH-LOGICAL-c474t-3c22b24f3d52f0ca6f230431629f0b9673be2c2fbcbd0cc8f70df8f851a26b1a3</cites><orcidid>0000-0001-7233-6943 ; 0000-0002-2455-0475 ; 0000-0002-9914-4586 ; 0000-0002-9573-8360</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12115-021-00594-8$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12115-021-00594-8$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,12845,27344,27924,27925,33774,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34149122$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Elliott, Karen</creatorcontrib><creatorcontrib>Price, Rob</creatorcontrib><creatorcontrib>Shaw, Patricia</creatorcontrib><creatorcontrib>Spiliotopoulos, Tasos</creatorcontrib><creatorcontrib>Ng, Magdalene</creatorcontrib><creatorcontrib>Coopamootoo, Kovila</creatorcontrib><creatorcontrib>van Moorsel, Aad</creatorcontrib><title>Towards an Equitable Digital Society: Artificial Intelligence (AI) and Corporate Digital Responsibility (CDR)</title><title>Society (New Brunswick)</title><addtitle>Soc</addtitle><addtitle>Society</addtitle><description>In the digital era, we witness the increasing use of artificial intelligence (AI) to solve problems, while improving productivity and efficiency. Yet, inevitably costs are involved with delegating power to algorithmically based systems, some of whose workings are opaque and unobservable and thus termed the “black box”. Central to understanding the “black box” is to acknowledge that the algorithm is not mendaciously undertaking this action; it is simply using the recombination afforded to scaled computable machine learning algorithms. But an algorithm with arbitrary precision can easily reconstruct those characteristics and make life-changing decisions, particularly in financial services (credit scoring, risk assessment, etc.), and it could be difficult to reconstruct, if this was done in a fair manner reflecting the values of society. If we permit AI to make life-changing decisions, what are the opportunity costs, data trade-offs, and implications for social, economic, technical, legal, and environmental systems? We find that over 160 ethical AI principles exist, advocating organisations to act responsibly to avoid causing digital societal harms. This maelstrom of guidance, none of which is compulsory, serves to confuse, as opposed to guide. We need to think carefully about how we implement these algorithms, the delegation of decisions and data usage, in the absence of human oversight and AI governance. The paper seeks to harmonise and align approaches, illustrating the opportunities and threats of AI, while raising awareness of Corporate Digital Responsibility (CDR) as a potential collaborative mechanism to demystify governance complexity and to establish an equitable digital society.</description><subject>Algorithms</subject><subject>Artificial intelligence</subject><subject>Data Use</subject><subject>Decisions</subject><subject>Delegation</subject><subject>Ethics</subject><subject>Financial services</subject><subject>Governance</subject><subject>Intelligence</subject><subject>Legal system</subject><subject>Mathematics</subject><subject>Opportunity costs</subject><subject>Original</subject><subject>Original Article</subject><subject>Political Science</subject><subject>Productivity</subject><subject>Responsibility</subject><subject>Risk assessment</subject><subject>Scores</subject><subject>Social Sciences</subject><subject>Society</subject><subject>Sociology</subject><issn>0147-2011</issn><issn>1936-4725</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>7UB</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>BHHNA</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kcFvFCEUxomxsevqP-DBTOJlexiFBwwzHkw226qbNDGp9UyAgZVmdtgCY7P_falbW-tBLhDe7_vee_kQekPwe4Kx-JAIEMJrDKTGmHesbp-hGeloUzMB_DmaYcJEDZiQY_QypStcDgB7gY4pI6wjADO0vQw3KvapUmN1dj35rPRgq1O_Ka-h-h6Mt3n_sVrG7J03vvytx2yHwW_saGy1WK5PirSvViHuQlT5UXth0y6MyWs_-LyvFqvTi5NX6MipIdnX9_cc_fh8drn6Wp9_-7JeLc9rwwTLNTUAGpijPQeHjWocUMwoaaBzWHeNoNqCAaeN7rExrRO4d61rOVHQaKLoHH06-O4mvbW9sWOOapC76Lcq7mVQXj6tjP6n3IRfsgUMmHXFYHFvEMP1ZFOWW59M2VuNNkxJAmdUFLBMNUfv_kGvwhTHsl6hOBei5fzOEA6UiSGlaN3DMATLuzTlIU1Z0pS_05RtEb39e40HyZ_4CkAPQCqlcWPjY-__2N4Cwneq2A</recordid><startdate>20210601</startdate><enddate>20210601</enddate><creator>Elliott, Karen</creator><creator>Price, Rob</creator><creator>Shaw, Patricia</creator><creator>Spiliotopoulos, Tasos</creator><creator>Ng, Magdalene</creator><creator>Coopamootoo, Kovila</creator><creator>van Moorsel, Aad</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7U4</scope><scope>7UB</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X7</scope><scope>7XB</scope><scope>87Z</scope><scope>88B</scope><scope>88E</scope><scope>88J</scope><scope>8BJ</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BHHNA</scope><scope>CCPQU</scope><scope>CJNVE</scope><scope>DPSOV</scope><scope>DWI</scope><scope>DWQXO</scope><scope>FQK</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HEHIP</scope><scope>JBE</scope><scope>K60</scope><scope>K6~</scope><scope>K9.</scope><scope>KC-</scope><scope>L.-</scope><scope>M0C</scope><scope>M0P</scope><scope>M0S</scope><scope>M1P</scope><scope>M2L</scope><scope>M2O</scope><scope>M2R</scope><scope>M2S</scope><scope>MBDVC</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEDU</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>WZK</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-7233-6943</orcidid><orcidid>https://orcid.org/0000-0002-2455-0475</orcidid><orcidid>https://orcid.org/0000-0002-9914-4586</orcidid><orcidid>https://orcid.org/0000-0002-9573-8360</orcidid></search><sort><creationdate>20210601</creationdate><title>Towards an Equitable Digital Society: Artificial Intelligence (AI) and Corporate Digital Responsibility (CDR)</title><author>Elliott, Karen ; Price, Rob ; Shaw, Patricia ; Spiliotopoulos, Tasos ; Ng, Magdalene ; Coopamootoo, Kovila ; van Moorsel, Aad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-3c22b24f3d52f0ca6f230431629f0b9673be2c2fbcbd0cc8f70df8f851a26b1a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Artificial intelligence</topic><topic>Data Use</topic><topic>Decisions</topic><topic>Delegation</topic><topic>Ethics</topic><topic>Financial services</topic><topic>Governance</topic><topic>Intelligence</topic><topic>Legal system</topic><topic>Mathematics</topic><topic>Opportunity costs</topic><topic>Original</topic><topic>Original Article</topic><topic>Political Science</topic><topic>Productivity</topic><topic>Responsibility</topic><topic>Risk assessment</topic><topic>Scores</topic><topic>Social Sciences</topic><topic>Society</topic><topic>Sociology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Elliott, Karen</creatorcontrib><creatorcontrib>Price, Rob</creatorcontrib><creatorcontrib>Shaw, Patricia</creatorcontrib><creatorcontrib>Spiliotopoulos, Tasos</creatorcontrib><creatorcontrib>Ng, Magdalene</creatorcontrib><creatorcontrib>Coopamootoo, Kovila</creatorcontrib><creatorcontrib>van Moorsel, Aad</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Sociological Abstracts (pre-2017)</collection><collection>Worldwide Political Science Abstracts</collection><collection>Access via ABI/INFORM (ProQuest)</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Education Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Social Science Database (Alumni Edition)</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Sociological Abstracts</collection><collection>ProQuest One Community College</collection><collection>Education Collection</collection><collection>Politics Collection</collection><collection>Sociological Abstracts</collection><collection>ProQuest Central Korea</collection><collection>International Bibliography of the Social Sciences</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Sociology Collection</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Politics Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Education Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Political Science Database</collection><collection>Research Library</collection><collection>Social Science Database</collection><collection>Sociology Database</collection><collection>Research Library (Corporate)</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Education</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>Sociological Abstracts (Ovid)</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Society (New Brunswick)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Elliott, Karen</au><au>Price, Rob</au><au>Shaw, Patricia</au><au>Spiliotopoulos, Tasos</au><au>Ng, Magdalene</au><au>Coopamootoo, Kovila</au><au>van Moorsel, Aad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Towards an Equitable Digital Society: Artificial Intelligence (AI) and Corporate Digital Responsibility (CDR)</atitle><jtitle>Society (New Brunswick)</jtitle><stitle>Soc</stitle><addtitle>Society</addtitle><date>2021-06-01</date><risdate>2021</risdate><volume>58</volume><issue>3</issue><spage>179</spage><epage>188</epage><pages>179-188</pages><issn>0147-2011</issn><eissn>1936-4725</eissn><abstract>In the digital era, we witness the increasing use of artificial intelligence (AI) to solve problems, while improving productivity and efficiency. Yet, inevitably costs are involved with delegating power to algorithmically based systems, some of whose workings are opaque and unobservable and thus termed the “black box”. Central to understanding the “black box” is to acknowledge that the algorithm is not mendaciously undertaking this action; it is simply using the recombination afforded to scaled computable machine learning algorithms. But an algorithm with arbitrary precision can easily reconstruct those characteristics and make life-changing decisions, particularly in financial services (credit scoring, risk assessment, etc.), and it could be difficult to reconstruct, if this was done in a fair manner reflecting the values of society. If we permit AI to make life-changing decisions, what are the opportunity costs, data trade-offs, and implications for social, economic, technical, legal, and environmental systems? We find that over 160 ethical AI principles exist, advocating organisations to act responsibly to avoid causing digital societal harms. This maelstrom of guidance, none of which is compulsory, serves to confuse, as opposed to guide. We need to think carefully about how we implement these algorithms, the delegation of decisions and data usage, in the absence of human oversight and AI governance. The paper seeks to harmonise and align approaches, illustrating the opportunities and threats of AI, while raising awareness of Corporate Digital Responsibility (CDR) as a potential collaborative mechanism to demystify governance complexity and to establish an equitable digital society.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>34149122</pmid><doi>10.1007/s12115-021-00594-8</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-7233-6943</orcidid><orcidid>https://orcid.org/0000-0002-2455-0475</orcidid><orcidid>https://orcid.org/0000-0002-9914-4586</orcidid><orcidid>https://orcid.org/0000-0002-9573-8360</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0147-2011 |
ispartof | Society (New Brunswick), 2021-06, Vol.58 (3), p.179-188 |
issn | 0147-2011 1936-4725 |
language | eng |
recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8202049 |
source | SpringerLink Journals; Worldwide Political Science Abstracts; Sociological Abstracts |
subjects | Algorithms Artificial intelligence Data Use Decisions Delegation Ethics Financial services Governance Intelligence Legal system Mathematics Opportunity costs Original Original Article Political Science Productivity Responsibility Risk assessment Scores Social Sciences Society Sociology |
title | Towards an Equitable Digital Society: Artificial Intelligence (AI) and Corporate Digital Responsibility (CDR) |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T04%3A19%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Towards%20an%20Equitable%20Digital%20Society:%20Artificial%20Intelligence%20(AI)%20and%20Corporate%20Digital%20Responsibility%20(CDR)&rft.jtitle=Society%20(New%20Brunswick)&rft.au=Elliott,%20Karen&rft.date=2021-06-01&rft.volume=58&rft.issue=3&rft.spage=179&rft.epage=188&rft.pages=179-188&rft.issn=0147-2011&rft.eissn=1936-4725&rft_id=info:doi/10.1007/s12115-021-00594-8&rft_dat=%3Cproquest_pubme%3E2543704904%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2555778559&rft_id=info:pmid/34149122&rfr_iscdi=true |