Human-machine interactions with clinical phrase prediction system, aligning with Zipf's least effort principle?
The essence of language and its evolutionary determinants have long been research subjects with multifaceted explorations. This work reports on a large-scale observational study focused on the language use of clinicians interacting with a phrase prediction system in a clinical setting. By adopting p...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2024-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0316177 |
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| author | Jamil Zaghir Mina Bjelogrlic Jean-Philippe Goldman Julien Ehrsam Christophe Gaudet-Blavignac Christian Lovis |
| author_facet | Jamil Zaghir Mina Bjelogrlic Jean-Philippe Goldman Julien Ehrsam Christophe Gaudet-Blavignac Christian Lovis |
| author_sort | Jamil Zaghir |
| collection | DOAJ |
| description | The essence of language and its evolutionary determinants have long been research subjects with multifaceted explorations. This work reports on a large-scale observational study focused on the language use of clinicians interacting with a phrase prediction system in a clinical setting. By adopting principles of adaptation to evolutionary selection pressure, we attempt to identify the major determinants of language emergence specific to this context. The observed adaptation of clinicians' language behaviour with technology have been confronted to properties shaping language use, and more specifically on two driving forces: conciseness and distinctiveness. Our results suggest that users tailor their interactions to meet these specific forces to minimise the effort required to achieve their objective. At the same time, the study shows that the optimisation is mainly driven by the distinctive nature of interactions, favouring communication accuracy over ease. These results, published for the first time on a large-scale observational study to our knowledge, offer novel fundamental qualitative and quantitative insights into the mechanisms underlying linguistic behaviour among clinicians and its potential implications for language adaptation in human-machine interactions. |
| format | Article |
| id | doaj-art-1578a005b30e4d40bf1fef6508c6381f |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-1578a005b30e4d40bf1fef6508c6381f2025-02-09T05:30:42ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-011912e031617710.1371/journal.pone.0316177Human-machine interactions with clinical phrase prediction system, aligning with Zipf's least effort principle?Jamil ZaghirMina BjelogrlicJean-Philippe GoldmanJulien EhrsamChristophe Gaudet-BlavignacChristian LovisThe essence of language and its evolutionary determinants have long been research subjects with multifaceted explorations. This work reports on a large-scale observational study focused on the language use of clinicians interacting with a phrase prediction system in a clinical setting. By adopting principles of adaptation to evolutionary selection pressure, we attempt to identify the major determinants of language emergence specific to this context. The observed adaptation of clinicians' language behaviour with technology have been confronted to properties shaping language use, and more specifically on two driving forces: conciseness and distinctiveness. Our results suggest that users tailor their interactions to meet these specific forces to minimise the effort required to achieve their objective. At the same time, the study shows that the optimisation is mainly driven by the distinctive nature of interactions, favouring communication accuracy over ease. These results, published for the first time on a large-scale observational study to our knowledge, offer novel fundamental qualitative and quantitative insights into the mechanisms underlying linguistic behaviour among clinicians and its potential implications for language adaptation in human-machine interactions.https://doi.org/10.1371/journal.pone.0316177 |
| spellingShingle | Jamil Zaghir Mina Bjelogrlic Jean-Philippe Goldman Julien Ehrsam Christophe Gaudet-Blavignac Christian Lovis Human-machine interactions with clinical phrase prediction system, aligning with Zipf's least effort principle? PLoS ONE |
| title | Human-machine interactions with clinical phrase prediction system, aligning with Zipf's least effort principle? |
| title_full | Human-machine interactions with clinical phrase prediction system, aligning with Zipf's least effort principle? |
| title_fullStr | Human-machine interactions with clinical phrase prediction system, aligning with Zipf's least effort principle? |
| title_full_unstemmed | Human-machine interactions with clinical phrase prediction system, aligning with Zipf's least effort principle? |
| title_short | Human-machine interactions with clinical phrase prediction system, aligning with Zipf's least effort principle? |
| title_sort | human machine interactions with clinical phrase prediction system aligning with zipf s least effort principle |
| url | https://doi.org/10.1371/journal.pone.0316177 |
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