Ai Deployment And Adoption In Public Administration And Organizations
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AI Deployment and Adoption in Public Administration and Organizations
The deployment of AI in public administration and organizations has the potential to revolutionize decision-making, improve efficiency, and enhance service delivery. By automating routine tasks and analyzing vast amounts of data, AI can streamline operations, reduce costs, and enable faster responses to societal challenges. Its adoption also raises critical questions about ethics, transparency, and inclusivity, as organizations must ensure AI technologies are implemented responsibly and equitably. Addressing these challenges can pave the way for more effective governance and innovation, benefiting society at large. AI Deployment and Adoption in Public Administration and Organizations explores the transformative potential of AI in public administration and organizational settings, highlighting its role in enhancing efficiency, decision-making, and service delivery. It delves into practical applications, case studies, and frameworks that guide organizations in leveraging AI to address complex challenges and improve outcomes. Covering topics such as customer relationship management systems, machine learning, and unemployment, this book is an excellent resource for public administration professionals, organizational leaders, policymakers, researchers, technology specialists, academicians, and more.
Electronic Government
This book constitutes the proceedings of the 23rd IFIP WG 8.5 International Conference, EGOV 2024, held in Ghent, Belgium, during September 3–5, 2024. The 29 full papers presented were carefully selected from 69 submissions. They were categorized under the topical sections as follows: Foundations, Digital transformation, Public Services, AI in government, Open government, Emerging topics.
Conversational Artificial Intelligence
This book reviews present state-of-the-art research related to the security of cloud computing including developments in conversational AI applications. It is particularly suited for those that bridge the academic world and industry, allowing readers to understand the security concerns in advanced security solutions for conversational AI in the cloud platform domain by reviewing present and evolving security solutions, their limitations, and future research directions. Conversational AI combines natural language processing (NLP) with traditional software like chatbots, voice assistants, or an interactive voice recognition system to help customers through either a spoken or typed interface. Conversational chatbots that respond to questions promptly and accurately to help customers are a fascinating development since they make the customer service industry somewhat self-sufficient. A well-automated chatbot can decimate staffing needs, but creating one is a time-consuming process. Voice recognition technologies are becoming more critical as AI assistants like Alexa become more popular. Chatbots in the corporate world have advanced technical connections with clients thanks to improvements in artificial intelligence. However, these chatbots’ increased access to sensitive information has raised serious security concerns. Threats are one-time events such as malware and DDOS (Distributed Denial of Service) assaults. Targeted strikes on companies are familiar and frequently lock workers out. User privacy violations are becoming more common, emphasizing the dangers of employing chatbots. Vulnerabilities are systemic problems that enable thieves to break in. Vulnerabilities allow threats to enter the system, hence they are inextricably linked. Malicious chatbots are widely used to spam and advertise in chat rooms by imitating human behavior and discussions, or to trick individuals into disclosing personal information like bank account details.