Identifying artificial intelligence actors using online data:
This paper uses information collected and provided by GlassAI to analyse the characteristics and activities of companies and universities in Canada, Germany, the United Kingdom and the United States that mention keywords related to Artificial Intelligence (AI) on their websites. The analysis finds t...
Gespeichert in:
| 1. Verfasser: | |
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| Weitere Verfasser: | , , , , |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Paris
OECD Publishing
2023
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| Schriftenreihe: | OECD Science, Technology and Industry Working Papers
no.2023/01 |
| Schlagworte: | |
| Online-Zugang: | UBA01 TUM01 UBG01 UEI01 UER01 UPA01 UBR01 UBW01 FFW01 FNU01 EUV01 FRO01 FHR01 FHN01 FHI01 Volltext |
| Zusammenfassung: | This paper uses information collected and provided by GlassAI to analyse the characteristics and activities of companies and universities in Canada, Germany, the United Kingdom and the United States that mention keywords related to Artificial Intelligence (AI) on their websites. The analysis finds that those companies tend to be young and small, mainly operate in the information and communication sector, have AI at the core of their business, and aim to provide customer solutions. It is noteworthy that the types of AI-related activities reported by them vary across sectors. Additionally, although universities are concentrated in and around large cities, this is not necessarily reflected in the intensity of AI-related activities. Taken together, this novel and timely evidence informs the debate on the most recent stages of digital transformation of the economy |
| Beschreibung: | 1 Online-Ressource (50 Seiten) |
| DOI: | 10.1787/1f5307e7-en |
Internformat
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| spelling | Dernis, Hélène Verfasser aut Identifying artificial intelligence actors using online data Hélène, Dernis ... [et al] Paris OECD Publishing 2023 1 Online-Ressource (50 Seiten) txt rdacontent c rdamedia cr rdacarrier OECD Science, Technology and Industry Working Papers no.2023/01 This paper uses information collected and provided by GlassAI to analyse the characteristics and activities of companies and universities in Canada, Germany, the United Kingdom and the United States that mention keywords related to Artificial Intelligence (AI) on their websites. The analysis finds that those companies tend to be young and small, mainly operate in the information and communication sector, have AI at the core of their business, and aim to provide customer solutions. It is noteworthy that the types of AI-related activities reported by them vary across sectors. Additionally, although universities are concentrated in and around large cities, this is not necessarily reflected in the intensity of AI-related activities. Taken together, this novel and timely evidence informs the debate on the most recent stages of digital transformation of the economy Science and Technology Industry and Services Calvino, Flavio ctb Moussiegt, Laurent ctb Nawa, Daisuke ctb Samek, Lea ctb Squicciarini, Mariagrazia ctb https://doi.org/10.1787/1f5307e7-en Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Dernis, Hélène Identifying artificial intelligence actors using online data Science and Technology Industry and Services |
| title | Identifying artificial intelligence actors using online data |
| title_auth | Identifying artificial intelligence actors using online data |
| title_exact_search | Identifying artificial intelligence actors using online data |
| title_exact_search_txtP | Identifying artificial intelligence actors using online data |
| title_full | Identifying artificial intelligence actors using online data Hélène, Dernis ... [et al] |
| title_fullStr | Identifying artificial intelligence actors using online data Hélène, Dernis ... [et al] |
| title_full_unstemmed | Identifying artificial intelligence actors using online data Hélène, Dernis ... [et al] |
| title_short | Identifying artificial intelligence actors using online data |
| title_sort | identifying artificial intelligence actors using online data |
| topic | Science and Technology Industry and Services |
| topic_facet | Science and Technology Industry and Services |
| url | https://doi.org/10.1787/1f5307e7-en |
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