Artificial Intelligence and Technology in Teaching Negotiation
Artificial intelligence (AI), machine learning (ML), affective computing, and big‐data techniques are improving the ways that humans negotiate and learn to negotiate. These technologies, long deployed in industry and academic research, are now being adopted for educational use. We describe several s...
Gespeichert in:
| Veröffentlicht in: | Negotiation journal 2021, Vol.37 (1), p.65-82 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 82 |
|---|---|
| container_issue | 1 |
| container_start_page | 65 |
| container_title | Negotiation journal |
| container_volume | 37 |
| creator | Dinnar, Samuel “Mooly” Dede, Chris Johnson, Emmanuel Straub, Carrie Korjus, Kristjan |
| description | Artificial intelligence (AI), machine learning (ML), affective computing, and big‐data techniques are improving the ways that humans negotiate and learn to negotiate. These technologies, long deployed in industry and academic research, are now being adopted for educational use. We describe several systems that help human negotiators evaluate and learn from role‐play simulations as well as applications that help human instructors teach negotiators at the individual, team, and organizational levels. AI can enable the personalization of negotiation instruction, taking into consideration factors such as culture and bias. These tools will enable improvements not only in the teaching of negotiation, but also in teaching humans how to program and collaborate with technology‐based negotiation systems, including avatars and computer‐controlled negotiation agents. These advances will provide theoretical and practical insights, require serious consideration of ethical issues, and revolutionize the way we practice and teach negotiation. |
| doi_str_mv | 10.1111/nejo.12351 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2491244314</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2491244314</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3011-3b56b398f35bac4eb1df49e8f6894eee616af64903a0217037e0038ef15816333</originalsourceid><addsrcrecordid>eNp9kFFLwzAQx4MoOKcvfoKCb0JnrknT5kUYY-pkbC_zOaTZpcuoyUw7ZN_ezvrsvRwHv7v78yPkHugE-nryuA8TyFgOF2QEeQGplIW8JCNa8DLleSauyU3b7imlgrFyRJ6nsXPWGaebZOE7bBpXozeYaL9NNmh2PjShPiXO95M2O-frZIV16JzuXPC35MrqpsW7vz4mHy_zzewtXa5fF7PpMjWMAqSsykXFZGlZXmnDsYKt5RJLK0rJEVGA0FZwSZmmGRSUFUgpK9FCXkIflI3Jw3D3EMPXEdtO7cMx-v6lyriEjHMGvKceB8rE0LYRrTpE96njSQFVZz_q7Ef9-ulhGOBv1-DpH1Kt5u_rYecHBUNmkA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2491244314</pqid></control><display><type>article</type><title>Artificial Intelligence and Technology in Teaching Negotiation</title><source>HeinOnline Law Journal Library</source><source>Access via Wiley Online Library</source><creator>Dinnar, Samuel “Mooly” ; Dede, Chris ; Johnson, Emmanuel ; Straub, Carrie ; Korjus, Kristjan</creator><creatorcontrib>Dinnar, Samuel “Mooly” ; Dede, Chris ; Johnson, Emmanuel ; Straub, Carrie ; Korjus, Kristjan</creatorcontrib><description>Artificial intelligence (AI), machine learning (ML), affective computing, and big‐data techniques are improving the ways that humans negotiate and learn to negotiate. These technologies, long deployed in industry and academic research, are now being adopted for educational use. We describe several systems that help human negotiators evaluate and learn from role‐play simulations as well as applications that help human instructors teach negotiators at the individual, team, and organizational levels. AI can enable the personalization of negotiation instruction, taking into consideration factors such as culture and bias. These tools will enable improvements not only in the teaching of negotiation, but also in teaching humans how to program and collaborate with technology‐based negotiation systems, including avatars and computer‐controlled negotiation agents. These advances will provide theoretical and practical insights, require serious consideration of ethical issues, and revolutionize the way we practice and teach negotiation.</description><identifier>ISSN: 0748-4526</identifier><identifier>EISSN: 1571-9979</identifier><identifier>DOI: 10.1111/nejo.12351</identifier><language>eng</language><publisher>Oxford: Blackwell Publishing Ltd</publisher><subject>affective computing ; Artificial intelligence ; avatars ; Bias ; computer‐controlled negotiation agents ; Ethical dilemmas ; ethics ; Feedback ; Humans ; Intelligence ; Machine learning ; Negotiation ; Negotiations ; Simulation ; Skills ; Students ; Teaching ; Teams ; Technology</subject><ispartof>Negotiation journal, 2021, Vol.37 (1), p.65-82</ispartof><rights>2021 President and Fellows of Harvard College</rights><rights>Copyright Blackwell Publishing Ltd. Winter 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3011-3b56b398f35bac4eb1df49e8f6894eee616af64903a0217037e0038ef15816333</citedby><cites>FETCH-LOGICAL-c3011-3b56b398f35bac4eb1df49e8f6894eee616af64903a0217037e0038ef15816333</cites><orcidid>0000-0001-7598-2238 ; 0000-0003-0322-2461</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fnejo.12351$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fnejo.12351$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><creatorcontrib>Dinnar, Samuel “Mooly”</creatorcontrib><creatorcontrib>Dede, Chris</creatorcontrib><creatorcontrib>Johnson, Emmanuel</creatorcontrib><creatorcontrib>Straub, Carrie</creatorcontrib><creatorcontrib>Korjus, Kristjan</creatorcontrib><title>Artificial Intelligence and Technology in Teaching Negotiation</title><title>Negotiation journal</title><description>Artificial intelligence (AI), machine learning (ML), affective computing, and big‐data techniques are improving the ways that humans negotiate and learn to negotiate. These technologies, long deployed in industry and academic research, are now being adopted for educational use. We describe several systems that help human negotiators evaluate and learn from role‐play simulations as well as applications that help human instructors teach negotiators at the individual, team, and organizational levels. AI can enable the personalization of negotiation instruction, taking into consideration factors such as culture and bias. These tools will enable improvements not only in the teaching of negotiation, but also in teaching humans how to program and collaborate with technology‐based negotiation systems, including avatars and computer‐controlled negotiation agents. These advances will provide theoretical and practical insights, require serious consideration of ethical issues, and revolutionize the way we practice and teach negotiation.</description><subject>affective computing</subject><subject>Artificial intelligence</subject><subject>avatars</subject><subject>Bias</subject><subject>computer‐controlled negotiation agents</subject><subject>Ethical dilemmas</subject><subject>ethics</subject><subject>Feedback</subject><subject>Humans</subject><subject>Intelligence</subject><subject>Machine learning</subject><subject>Negotiation</subject><subject>Negotiations</subject><subject>Simulation</subject><subject>Skills</subject><subject>Students</subject><subject>Teaching</subject><subject>Teams</subject><subject>Technology</subject><issn>0748-4526</issn><issn>1571-9979</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kFFLwzAQx4MoOKcvfoKCb0JnrknT5kUYY-pkbC_zOaTZpcuoyUw7ZN_ezvrsvRwHv7v78yPkHugE-nryuA8TyFgOF2QEeQGplIW8JCNa8DLleSauyU3b7imlgrFyRJ6nsXPWGaebZOE7bBpXozeYaL9NNmh2PjShPiXO95M2O-frZIV16JzuXPC35MrqpsW7vz4mHy_zzewtXa5fF7PpMjWMAqSsykXFZGlZXmnDsYKt5RJLK0rJEVGA0FZwSZmmGRSUFUgpK9FCXkIflI3Jw3D3EMPXEdtO7cMx-v6lyriEjHMGvKceB8rE0LYRrTpE96njSQFVZz_q7Ef9-ulhGOBv1-DpH1Kt5u_rYecHBUNmkA</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Dinnar, Samuel “Mooly”</creator><creator>Dede, Chris</creator><creator>Johnson, Emmanuel</creator><creator>Straub, Carrie</creator><creator>Korjus, Kristjan</creator><general>Blackwell Publishing Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88F</scope><scope>88G</scope><scope>8AM</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>BGRYB</scope><scope>CCPQU</scope><scope>DPSOV</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>JBE</scope><scope>K60</scope><scope>K6~</scope><scope>K7.</scope><scope>KC-</scope><scope>L.-</scope><scope>M0C</scope><scope>M0O</scope><scope>M1Q</scope><scope>M2L</scope><scope>M2M</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0001-7598-2238</orcidid><orcidid>https://orcid.org/0000-0003-0322-2461</orcidid></search><sort><creationdate>2021</creationdate><title>Artificial Intelligence and Technology in Teaching Negotiation</title><author>Dinnar, Samuel “Mooly” ; Dede, Chris ; Johnson, Emmanuel ; Straub, Carrie ; Korjus, Kristjan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3011-3b56b398f35bac4eb1df49e8f6894eee616af64903a0217037e0038ef15816333</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>affective computing</topic><topic>Artificial intelligence</topic><topic>avatars</topic><topic>Bias</topic><topic>computer‐controlled negotiation agents</topic><topic>Ethical dilemmas</topic><topic>ethics</topic><topic>Feedback</topic><topic>Humans</topic><topic>Intelligence</topic><topic>Machine learning</topic><topic>Negotiation</topic><topic>Negotiations</topic><topic>Simulation</topic><topic>Skills</topic><topic>Students</topic><topic>Teaching</topic><topic>Teams</topic><topic>Technology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dinnar, Samuel “Mooly”</creatorcontrib><creatorcontrib>Dede, Chris</creatorcontrib><creatorcontrib>Johnson, Emmanuel</creatorcontrib><creatorcontrib>Straub, Carrie</creatorcontrib><creatorcontrib>Korjus, Kristjan</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Access via ABI/INFORM (ProQuest)</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Military Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Criminal Justice 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>Criminology Collection</collection><collection>ProQuest One Community College</collection><collection>Politics Collection</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>International Bibliography of the Social Sciences</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ProQuest Criminal Justice (Alumni)</collection><collection>ProQuest Politics Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Criminal Justice Database</collection><collection>Military Database</collection><collection>Political Science Database</collection><collection>Psychology Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</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 One Psychology</collection><collection>ProQuest Central Basic</collection><jtitle>Negotiation journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dinnar, Samuel “Mooly”</au><au>Dede, Chris</au><au>Johnson, Emmanuel</au><au>Straub, Carrie</au><au>Korjus, Kristjan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Artificial Intelligence and Technology in Teaching Negotiation</atitle><jtitle>Negotiation journal</jtitle><date>2021</date><risdate>2021</risdate><volume>37</volume><issue>1</issue><spage>65</spage><epage>82</epage><pages>65-82</pages><issn>0748-4526</issn><eissn>1571-9979</eissn><abstract>Artificial intelligence (AI), machine learning (ML), affective computing, and big‐data techniques are improving the ways that humans negotiate and learn to negotiate. These technologies, long deployed in industry and academic research, are now being adopted for educational use. We describe several systems that help human negotiators evaluate and learn from role‐play simulations as well as applications that help human instructors teach negotiators at the individual, team, and organizational levels. AI can enable the personalization of negotiation instruction, taking into consideration factors such as culture and bias. These tools will enable improvements not only in the teaching of negotiation, but also in teaching humans how to program and collaborate with technology‐based negotiation systems, including avatars and computer‐controlled negotiation agents. These advances will provide theoretical and practical insights, require serious consideration of ethical issues, and revolutionize the way we practice and teach negotiation.</abstract><cop>Oxford</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1111/nejo.12351</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0001-7598-2238</orcidid><orcidid>https://orcid.org/0000-0003-0322-2461</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0748-4526 |
| ispartof | Negotiation journal, 2021, Vol.37 (1), p.65-82 |
| issn | 0748-4526 1571-9979 |
| language | eng |
| recordid | cdi_proquest_journals_2491244314 |
| source | HeinOnline Law Journal Library; Access via Wiley Online Library |
| subjects | affective computing Artificial intelligence avatars Bias computer‐controlled negotiation agents Ethical dilemmas ethics Feedback Humans Intelligence Machine learning Negotiation Negotiations Simulation Skills Students Teaching Teams Technology |
| title | Artificial Intelligence and Technology in Teaching Negotiation |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T05%3A15%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Artificial%20Intelligence%20and%20Technology%20in%20Teaching%20Negotiation&rft.jtitle=Negotiation%20journal&rft.au=Dinnar,%20Samuel%20%E2%80%9CMooly%E2%80%9D&rft.date=2021&rft.volume=37&rft.issue=1&rft.spage=65&rft.epage=82&rft.pages=65-82&rft.issn=0748-4526&rft.eissn=1571-9979&rft_id=info:doi/10.1111/nejo.12351&rft_dat=%3Cproquest_cross%3E2491244314%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2491244314&rft_id=info:pmid/&rfr_iscdi=true |