Combining human and machine intelligence for making predictions
Thesis (S.M. in Management Research)--Massachusetts Institute of Technology, Sloan School of Management, June 2013.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2013
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| Online Access: | http://hdl.handle.net/1721.1/82272 |
| _version_ | 1826201010621644800 |
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| author | Nagar, Yiftach |
| author2 | Thomas W. Malone. |
| author_facet | Thomas W. Malone. Nagar, Yiftach |
| author_sort | Nagar, Yiftach |
| collection | MIT |
| description | Thesis (S.M. in Management Research)--Massachusetts Institute of Technology, Sloan School of Management, June 2013. |
| first_indexed | 2024-09-23T11:44:52Z |
| format | Thesis |
| id | mit-1721.1/82272 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T11:44:52Z |
| publishDate | 2013 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/822722019-04-10T10:37:58Z Combining human and machine intelligence for making predictions Nagar, Yiftach Thomas W. Malone. Sloan School of Management. Sloan School of Management. Sloan School of Management. Thesis (S.M. in Management Research)--Massachusetts Institute of Technology, Sloan School of Management, June 2013. "June 2012." Cataloged from PDF version of thesis. Includes bibliographical references (p. 28-32). An extensive literature in psychology, economics, statistics, operations research and management science has dealt with comparing forecasts based on human-expert judgment vs. (statistical) models in a variety of scenarios, mostly finding advantage of the latter, yet acknowledging the necessity of the former. Although computers can use vast amounts of data to make predictions that are often more accurate than those by human experts, humans are still 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 in comparison to 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. by Yiftach Nagar. S.M.in Management Research 2013-11-18T19:02:37Z 2013-11-18T19:02:37Z 2013 Thesis http://hdl.handle.net/1721.1/82272 861188744 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 32 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Sloan School of Management. Nagar, Yiftach Combining human and machine intelligence for making predictions |
| title | Combining human and machine intelligence for making predictions |
| title_full | Combining human and machine intelligence for making predictions |
| title_fullStr | Combining human and machine intelligence for making predictions |
| title_full_unstemmed | Combining human and machine intelligence for making predictions |
| title_short | Combining human and machine intelligence for making predictions |
| title_sort | combining human and machine intelligence for making predictions |
| topic | Sloan School of Management. |
| url | http://hdl.handle.net/1721.1/82272 |
| work_keys_str_mv | AT nagaryiftach combininghumanandmachineintelligenceformakingpredictions |