Machine Learning and Artificial Intelligence
Submission deadline: 2023-12-31
Section Editors

Section Collection Information

Dear Colleagues,

 

In this era of rapid technological advancement, the ever-increasing applications of machine learning and artificial intelligence (AI) demand a concerted effort to shape a future steeped in innovation, ethical consideration, and responsible development. The realm of AI and ML requires us to cultivate processes firmly rooted in a vision of responsible AI and AI sovereignty as the ultimate objective. Collaborative research endeavors, multidisciplinary cooperation, cross-industry partnerships, the pivotal role of ethical AI frameworks, and more, are instrumental in forging pathways towards a sustainable, ethically-driven, socially equitable, economically viable, and culturally relevant future for individuals across the globe.

 

"Responsible AI and Territorial Advancements towards AI Sovereignty amidst Global Challenges" seeks to be a forum for invaluable contributions that address the societal impact of AI and ML technologies. Any vision of responsible AI necessitates the examination of grassroots initiatives fostered by diverse AI research and development organizations, aiming to bolster AI and ML transitions within various industries and sectors.

 

Hence, our interest lies in collective initiatives within the AI and ML framework, the strategies for their internal reinforcement, the narratives surrounding the common good, the genesis of inclusive agendas, and the various methodologies for action and advocacy. It is crucial to collect and analyze the experiences associated with different AI and ML policies that have been implemented, assessing their effects on society. We cordially invite research articles and reviews in this ever-evolving field of AI and ML.

 

We eagerly anticipate your valuable contributions in this arena.

 

We look forward to receiving your contributions. 

Dr. Mohit Mittal

Section Editor

 





Keywords

Machine Learning; Artificial Intelligence (AI);Face recognition,;Explainable AI; E- learning; Cognitive science;Computer vision.