Thématiques, GTAIM & TRACKS > L'impact de l'intelligence artificielle sur les entreprises et la société

L'impact de l'intelligence artificielle sur les entreprises et la société

Les système d'Intelligence Artificielle (IA), s’ils sont bien implémentés, peuvent potentiellement avoir un impact majeur sur les stratégies et les performances des organisations publiques et privées. Dans le domaine de la recherche en sciences de gestion, ces technologies de pointe sont connues non seulement pour leur contribution substantielle à la création d'un avantage concurrentiel (Akter et al. 2020) mais également à la forte participation aux développements économiques, écologiques et sociaux (Wamba et al. 2015) et sont également connus pour leur contribution à l'amélioration du bien-être. En effet, ils ont le potentiel d'apporter une valeur aux entreprises et aux organisations dans de vastes domaines tels que la réponse aux catastrophes (Ofli et al 2016 ; Zhou et al. 2018), la réduction des inégalités (Korinek et Stiglitz 2019), le développement de nouvelles connaissances (Harfouche et al. al. al. 2017), l’amélioration de la santé humaine (Guo et Li 2018 ; Stone et al. 2018 ; Wahl et al. 2018), l’amélioration de l'éducation (McCalla 2004) et les transports et aussi révolutionner l'agriculture (Harfouche et al. 2019). Ils peuvent également étendre la microfinance et l'entrepreneuriat social (Popkova et Sergi 2020). Ce track vise à identifier de nouvelles théories et applications liées au role de l'intelligence artificielle dans l'amélioration des stratégies, de la gestion et des opérations des entreprises et des organisations. Il vise également à faire la lumière sur la façon dont ces technologies doivent être conçues, adoptées et adaptées dans le respect de la vie privée, de l'éthique et de la sécurité. L'accent sera mis sur l'impact de ces technologies aux niveaux stratégique, opérationnel, technique et social. 

Ce track invite les chercheurs et les spécialistes à soumettre des recherches académiques dans divers domaines de l'intelligence artificielle et du management, en particulier des recherches conceptuelles innovantes et rigoureuses, ainsi que des contributions et applications empiriques.

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If well implemented, Artificial Intelligence (AI) is expected to have a major impact on strategies and performance of public and private organizations. In the business and management research field, these cutting-edge technologies are known not only for their substantial contribution in creating a competitive advantage (Akter et al. 2020) but also in promoting economic, ecological, and social developments (Wamba et al. 2015) and in contributing to the improvement of the wellbeing. Thus, they have the potential to bring great value to companies and organisations in wide areas such as responding to disasters (Ofli et al 2016; Zhou et al. 2018), reducing inequalities (Korinek and Stiglitz 2019), developing new knowledge (Harfouche et al. 2017), improving human health (Guo and Li 2018; Stone et al. 2018; Wahl et al. 2018), improving education (McCalla 2004), transportation, and revolutionizing agriculture (Harfouche et al. 2019). They can also enhance and extend microfinance and social entrepreneurship (Popkova and Sergi 2020). 

This track aims to identify new theories and applications related to the impact of Artificial Intelligence in enhancing the strategies, the management, and operations of companies and organizations. It also aims to shed light on how these technologies should be designed, adopted, and adapted while respecting privacy, ethics, and security. The focus will be on the impact of these technologies at the strategic, operational, technical, and social levels. 

This track invites researchers, academics, and specialists to submit scientific research in various areas of Artificial Intelligence and management, especially innovative and rigorously developed conceptual studies and empirical contributions and applications are welcome. 

An indicative list of themes: 

• AI for development strategies 
• Digital eco-system for AI
•  Ai to improve the quality of life 
• Legal and ethical issues of AI use 
•  Application of AI to respond to climate and sustainability challenges as well as to human and natural disasters 
• AI role in reducing inequalities 
• AI to reduce the digital divide 
•  AI and Big Data Applications in counterterrorism, pre-and post-attacks 
• AI role in security 
•  AI role in improving education 
• AI role in enhancing microfinance 
• AI role in developing human health 
• AI human-centric design for security 
• AI to improve the efficiency of the public sector 
• Artificial Intelligence implementation, adoption, adaptation by companies and organisations to create new business models
• AI and Digital transformation for an inter-organization data sharing 
• The role of AI in solving complex social problems 
• AI and deep learning to identify risks 
• AI and democratization in developing countries: opportunities and threats
• AI and innovations in HR, Supply Chain, Logistics, and other business areas
• AI  and their role in the development of countries
• AI as a strategic tool for social entrepreneurship 
• Impact of automation ad robotics on society
• Use of AI for social impact and the common good, such as conflict resolution, mitigating refuge crises
• Role of AI in diversifying the economy
• Strategies for governments to support AI deployment in society
• Tackling climate change, water scarcity through AI
• Improving public health using AI
• Improving food security by sustainable agricultural practices through AI

Responsables du track:

References/ Références :

Akter, S, Gunasekaran, A., Wamba, SF, Babu, MM, Hani U (2020) Reshaping competitive advantages with analytics capabilities in service systems. Technological Forecasting and Social Change 159, 120-180

Fosso Wamba, S., Akter, S., Edwards, A., Chopin, G., and Gnanzou, D. (2015). "How ‘Big Data’ Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study," International Journal of Production Economics, 165, 234-246.

Guo J, Li B. (2018) The Application of Medical Artificial Intelligence Technology in Rural Areas of Developing Countries. Health Equity;2(1):174-181.

Harfouche, A. Quinio, B., Skandrani, S., Marciniak, R. (2017), « A Framework for Artificial Knowledge Creation in Organizations, » Thirty eighth International Conference on Information Systems ICIS2017, Seoul.

Harfouche, AL, DA Jacobson, D Kainer, JC Romero, AH Harfouche, G. Scarascia Mugnozza, M. Moshelion, G. A. Tuskan, J. J.B. Keurentjes, A. Altman (2019). “Accelerating Climate Resilient Plant Breeding by Applying Next-Generation Artificial Intelligence, Trends in Biotechnology, In press.

Korinek, A. and. Stiglitz J.E (2019), “Artificial Intelligence and Its Implications for Income Distribution and Unemployment,” forthcoming in Agrawal et al.: The Economics of Artificial Intelligence, NBER and University of Chicago Press.

McCalla, G., 2004. The Ecological Approach to the Design of E-Learning Environments: Purpose-based Capture and Use of Information About Learners. Journal of Interactive Media in Education, 2004(1), p.Art. 3.

Ofli, F., Meier, P., Imran, M., Castillo, C., Tuia, D., Rey, N., Briant, J., Millet, P., Reinhard, F., Parkan, M., & Joost, S. (2016). Combining human computing and machine learning to make sense of big (aerial) data for disaster response. Big Data, 4(1): 47–59.

Popkova, E.G. and Sergi, B.S. (2020). “Human capital and AI in industry 4.0. Convergence and divergence in social entrepreneurship in Russia”, Journal of Intellectual Capital, 21(4), 565-581

Stone, P., Brooks, R., Brynjolfsson, E., Calo, R., Etzioni, O., Hager, G., Hirschberg, J., Kalyanakrishnan, S., Kamar, E., Kraus, S., Leyton-Brown, K., Parkes, D., Press, W., Saxenian, A. L., Shah, J., Tambe, M., and Teller, A. (2016). “Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel,” Stanford University, Stanford, CA.

Viale Pereira, G., Cunha, M. A., lampoltshammer, T.J, Parycek P. and Gregianin Testa M. (2017). Increasing collaboration and participation in smart city governance: a cross-case analysis of smart city initiatives. Information Technology for Development, 23(3), 526-553.

Wahl B, C.-G.A., Germann S, et al (2018) Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings?  BMJ Global Health, 2018;3:e000798.

Watts, D. (2014). Common Sense and Sociological Explanations. American Journal of Sociology, 120(2), 313-351. doi:10.1086/678271

Watts, D. (2017). Should social science be more solution-oriented? Nature Human Behaviour, 1(1), 0015. http://dx.doi.org/10.1038/s41562-016-0015

Zhou, L., Wu, X., Xu, Z., Fujita H. (2018). Emergency decision making for natural disasters: an overview, Int. J. Disaster Risk Reduct., 27, 567-576

Wamba, S,  RE Bawack, C Guthrie, MM Queiroz, KDA Carillo (2020), Are we preparing for a good AI society? A bibliometric review and research agenda, Technological Forecasting and Social Change, 120482, In press