There is still a significant gap between expectations and the successful adoption of AI to innovate and improve businesses. Due to the emergence of deep learning, AI adoption is more complex as it often incorporates big data and the internet of things, affecting data privacy. Existing frameworks have identified the need to focus on human-centered design, combining technical and business/organizational perspectives. However, trust remains a critical issue that needs to be designed from the beginning. The proposed framework expands from the human-centered design approach, emphasizing and maintaining the trust that underpins the process. This paper proposes a theoretical framework for responsible artificial intelligence (AI) implementation. The proposed framework emphasizes a synergistic business technology approach for the agile co-creation process. The aim is to streamline the adoption process of AI to innovate and improve business by involving all stakeholders throughout the project so that the AI technology is designed, developed, and deployed in conjunction with people and not in isolation. The framework presents a fresh viewpoint on responsible AI implementation based on analytical literature review, conceptual framework design, and practitioners' mediating expertise. The framework emphasizes establishing and maintaining trust throughout the human-centered design and agile development of AI. This human-centered approach is aligned with and enabled by the privacy by design principle. The creators of the technology and the end-users are working together to tailor the AI solution specifically for the business requirements and human characteristics. An illustrative case study on adopting AI for assisting planning in a hospital will demonstrate that the proposed framework applies to real-life applications.
Education-centered critical policy analysis of AI: Ghana's AI strategy as a case
University of Georgia（佐治亚大学）；Université de Guyane（圭亚那大学）；University of Manitoba（曼尼托巴大学）；Gambaga College of Education（甘巴加教育学院）；University for Development Studies（发展研究大学）；The Open University（开放大学）；St. Joseph’s College of Education（圣约瑟夫教育学院）；Mampong Technical College of Education（曼庞技术教育学院）；Bagabaga College of Education（巴加巴加教育学院）
Culturally-Aware AI for Cross-Boundary Community Learning: Undergraduate Innovation at the Intersection of Computation and Design
Duke Kunshan University（杜克昆山大学）；Zhouzhuang Mystery of Life Museum（周庄生命之谜博物馆）；Digital Innovation Research Center and Social Science Division（数字创新研究中心和社会科学系）
What is Implementation Science; and Why It Matters for Bridging the Artificial Intelligence Innovation-to-Application Gap in Medical Imaging
Tehran University of Medical Sciences（德黑兰医科大学）；Imperial College（帝国理工学院）；Washington University in St. Louis（圣路易斯华盛顿大学）；Sultan Qaboos University（苏丹卡布斯大学）；Universiti Sains Malaysia（马来西亚理科大学）；University of British Columbia（不列颠哥伦比亚大学）；BC Cancer Research Institute（不列颠哥伦比亚癌症研究所）
Advancing Responsible Innovation in Agentic AI: A study of Ethical Frameworks for Household Automation
Department of CST Tsinghua University Beijing, China（计算机科学与技术系 清华大学 北京中国）；Department of CSE Chandigarh University Mohali, India（计算机科学与工程系 印度昌迪加尔大学 摩哈利）
NuHF Claw: A Risk Constrained Cognitive Agent Framework for Human Centered Procedure Support in Digital Nuclear Control Rooms
Institute of Nuclear and New Energy Technology, Tsinghua University（清华大学核能与新能源技术研究院）；National Key Laboratory of Human Factors Engineering（人因工程国家重点实验室）；Institute of Software, Chinese Academy of Sciences（中国科学院软件研究所）
