dc.contributor.author | Nagar, Yiftach | |
dc.contributor.author | Malone, Thomas W. | |
dc.date.accessioned | 2014-06-16T13:11:06Z | |
dc.date.available | 2014-06-16T13:11:06Z | |
dc.date.issued | 2011-12 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/87989 | |
dc.description.abstract | Computers can use vast amounts of data to make predictions that are often more accurate than those by human experts. Yet, humans are more adept at processing unstructured information and at recognizing unusual circumstances and their consequences. Can we combine predictions from humans and machines to get predictions that are better than either could do alone? We used prediction markets to combine predictions from groups of people and artificial intelligence agents. We found that the combined predictions were both more accurate and more robust than those made by groups of only people or only machines. This combined approach may be especially useful in situations where patterns are difficult to discern, where data are difficult to codify, or where sudden changes occur unexpectedly. | en_US |
dc.description.sponsorship | Lincoln Laboratory | en_US |
dc.description.sponsorship | United States. Army Research Office | en_US |
dc.language.iso | en_US | |
dc.publisher | Association for Information Systems | en_US |
dc.relation.isversionof | http://aisel.aisnet.org/icis2011/proceedings/knowledge/20/ | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
dc.source | MIT web domain | en_US |
dc.title | Making Business Predictions by Combining Human and Machine Intelligence in Prediction Markets | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Nagar, Yiftach, and Thomas Malone. "Making Business Predictions by Combining Human and Machine Intelligence in Prediction Markets" (December 5, 2011). ICIS 2011 Proceedings. Paper 20. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Center for Collective Intelligence | en_US |
dc.contributor.department | Sloan School of Management | en_US |
dc.contributor.mitauthor | Nagar, Yiftach | en_US |
dc.contributor.mitauthor | Malone, Thomas W. | en_US |
dc.relation.journal | Proceedings of the Thirty Second International Conference on Information Systems | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
dspace.orderedauthors | Nagar, Yiftach; Malone, Thomas | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-7005-1482 | |
dc.identifier.orcid | https://orcid.org/0000-0002-7332-3017 | |
mit.license | OPEN_ACCESS_POLICY | en_US |
mit.metadata.status | Complete | |