Ataharul Chowdhury On Linkedin Ai For Agri Food Innovation This research will use a mixed methods approach to investigate the key factors influencing ai adoption in ontario’s horticultural and livestock sectors, the associated challenges and opportunities, and the essential skills and knowledge for agri food workers to thrive. This research aims to build on past examples of success in participatory, media led agricultural innovations such as seed, pesticide and soil management improvements in bangladesh.
Reactfolio This study aims to identify artificial intelligence (ai) technologies that are applied in climate smart agricultural practices and address ethical concerns of deploying those technologies from. associate professor, university of guelph cited by 1,350 development communication participatory methods rural development sustainable agriculture. I completed my doctoral studies at the university of natural resources and life sciences (boku), vienna, austria. my doctoral research was in the area of sustainable agricultural development and focused on video mediated learning to support agricultural innovation in bangladesh. Applying a systems perspective and responsible innovation, it identifies and categorizes emerging ai applications, develops a conceptual framework to capture technological, social, environmental, individual, and institutional factors, and proposes practical strategies to promote adoption.
Agri Food Ai I completed my doctoral studies at the university of natural resources and life sciences (boku), vienna, austria. my doctoral research was in the area of sustainable agricultural development and focused on video mediated learning to support agricultural innovation in bangladesh. Applying a systems perspective and responsible innovation, it identifies and categorizes emerging ai applications, develops a conceptual framework to capture technological, social, environmental, individual, and institutional factors, and proposes practical strategies to promote adoption. Our new paper, “enabling responsible ai driven agri food innovation in ontario”, published in advancements in agricultural development, develops a comprehensive framework that integrates. Adopting ai technologies is complex and requires careful consideration of positive and negative consequences. to better understand ai adoption, we present a framework that examines multiple nested factors, from the individual level to the enabling environment and technology characteristics. A framework for analyzing ai adoption is proposed that incorporates systemic perspectives on capacity development and responsible innovation and is applied to identify and prioritize key factors influencing ai adoption in the livestock and horticulture sectors. The sshrc post doctoral work at the university of guelph investigated use of social media in multi stakeholder learning and collaboration in the agri food and rural development sectors in ontario.
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