000			02081cam a2200313 4500500
005			20260322004939.0
041			_afre
042			_adc
100	1	0	_aRychalski, Aude _eauthor
700	1	0	_aAubry, Mathilde _eauthor
245	0	0	_aDiversify Approaches to Better Understand the Compatibility of Artificial Intelligence and Sustainability: “I Love You… Me Neither”
260			_c2024.
500			_a35
520			_aThe aim of this article is twofold: 1. Suggest an overview of current knowledge and understanding of both concepts and 2. Present the six contributions and their positioning in relation to current the literature linked to artificial intelligence and sustainability. For that, we use different but complementary sources. First, we ask artificial intelligence to reveal the mainstream view. Then we call on human intelligence to provide a critical perspective. Finally, we carry out a bibliometric analysis using the SCOPUS database and two different statistical analyses (the CCA – co-citation analysis, the BCA – bibliographic coupling analysis). The diversity of the sources used, and their complementarity allow us to propose a holistic vision of the subject, highlighting the concerns that surround it and identifying future avenues of research for academics. The articles selected in this special issue fill some of the gaps raised and call for further research.JEL Codes: O33, O44, Q55, Q56
690			_aArtificial Intelligence
690			_aBibliographic Coupling Analysis (BCA)
690			_aBibliometrics
690			_aCo-Citation Analysis (CCA)
690			_aEthics
690			_aSustainability
690			_aArtificial Intelligence
690			_aBibliographic Coupling Analysis (BCA)
690			_aBibliometrics
690			_aCo-Citation Analysis (CCA)
690			_aEthics
690			_aSustainability
786	0		_nJournal of Innovation Economics & Management | o 44 | 2 | 2024-05-17 | p. 1-21
856	4	1	_uhttps://shs.cairn.info/journal-of-innovation-economics-2024-2-page-1?lang=en&redirect-ssocas=7080
999			_c1744323 _d1744323