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As generative AI rapidly advances with the field of artificial intelligence, its presence poses significant ethical, security, and data management challenges. While this technology encourages innovation across various industries, ethical concerns regarding the potential misuse of AI-generated content for misinformation or manipulation may arise. The risks of AI-generated deepfakes and cyberattacks demand more research into effective security tactics. The supervision of datasets required to train generative AI models raises questions about privacy, consent, and responsible data management. As generative AI evolves, further research into the complex issues regarding its potential is required to safeguard ethical values and security of people’s data. Generative AI and Implications for Ethics, Security, and Data Management explores the implications of generative AI across various industries who may use the tool for improved organizational development. The security and data management benefits of generative AI are outlined, while examining the topic within the lens of ethical and social impacts. This book covers topics such as cybersecurity, digital technology, and cloud storage, and is a useful resource for computer engineers, IT professionals, technicians, sociologists, healthcare workers, researchers, scientists, and academicians.
As generative AI rapidly advances with the field of artificial intelligence, its presence poses significant ethical, security, and data management challenges. While this technology encourages innovation across various industries, ethical concerns regarding the potential misuse of AI-generated content for misinformation or manipulation may arise. The risks of AI-generated deepfakes and cyberattacks demand more research into effective security tactics. The supervision of datasets required to train generative AI models raises questions about privacy, consent, and responsible data management. As generative AI evolves, further research into the complex issues regarding its potential is required to safeguard ethical values and security of people's data. Generative AI and Implications for Ethics, Security, and Data Management explores the implications of generative AI across various industries who may use the tool for improved organizational development. The security and data management benefits of generative AI are outlined, while examining the topic within the lens of ethical and social impacts. This book covers topics such as cybersecurity, digital technology, and cloud storage, and is a useful resource for computer engineers, IT professionals, technicians, sociologists, healthcare workers, researchers, scientists, and academicians.
Digital transformation and innovation reshape today’s emerging markets, unlocking new opportunities for economic growth and social progress. As these regions embrace technological advancements, industries such as finance, healthcare, and education continue to improve. Mobile connectivity and internet access have increased the presence of digital entrepreneurs, fostering innovation to address local challenges and enhance quality of life. Governments and organizations are leveraging data-driven strategies to improve services and infrastructure, driving inclusivity and sustainability. Harnessing the power of digital tools may allow emerging markets to adapt to global trends while paving the way for an interconnected and prosperous future. Digital Transformation and Innovation in Emerging Markets explores the impact of digital technology on various new industries and markets. It offers useful solutions to address the challenges of technological transformation in healthcare, education, and marketing. This book covers topics such as cyber security, digital technology, and telemedicine, and is a useful resource for computer engineers, business owners, educators, managers, scientists, academicians, and researchers.
Generative Artificial Intelligence (AI), an ever-evolving technology, holds immense promise across various industries, from healthcare to content generation. However, its rapid advancement has also given rise to profound ethical concerns. Illicit black-market industries exploit generative AI for counterfeit imagery, and in educational settings, biases and misinformation perpetuate. These issues underscore the need to grapple with the risks accompanying generative AI integration. Exploring the Ethical Implications of Generative AI emerges as a wellspring of insight for discerning academic scholars. It sets the stage by acknowledging generative AI's multifaceted potential and its capacity to reshape industries. The book addresses these complex ethical concerns, offering a comprehensive analysis and providing a roadmap for responsible AI development and usage. Its intended audience spans business leaders, policymakers, scholars, and individuals passionate about the ethical dimensions of AI.
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This book demonstrates how generative artificial intelligence (AI), a form of sophisticated AI technology, is transforming our knowledge of how the human mind functions in relation to business leadership and decision-making. It describes the most recent findings and applications of generative AI in psychology. The book explains the relationships between language, thinking, and behavior as well as how AI may aid in our understanding of learning, decision-making, and problem-solving. In addition, it discusses the significance of applying AI properly and ethically. This book provides a comprehensive overview of how AI is increasing our understanding of the mind and how it impacts each of us professionally.
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Artificial Intelligence (AI) technology has led to the creation of many opportunities in the field of healthcare. Like other industries, stakeholders in the healthcare sector stand to benefit tremendously from its adoption. The multifaceted benefits associated with AI are something that makes the adoption of technology constructive for the sector. That said, it is equally important to take care of the ethical, security, and safety challenges related to AI applications. AI Healthcare Applications and Security, Ethical, and Legal Considerations discusses in detail the various facets of AI integration in the healthcare sector. This book offers comprehensive information on how to integrate AI into the healthcare sector safely and ethically. Covering topics such as cybersecurity, machine learning models, and public policy, this book is an excellent resource for healthcare professionals and administrators, researchers, ethicists, legal scholars, healthcare policy makers and regulators, medical informatics and IT professionals, educators, bioethics professionals, academicians, and more.
In today's fast-paced digital world, marketers face an ever-growing challenge: effectively navigating the vast and complex data landscape while ensuring ethical practices. The explosion of digital information has created new opportunities for targeted marketing. Still, it has also raised concerns about privacy, security, and the responsible use of data. Marketers risk damaging consumer trust and facing regulatory scrutiny without a comprehensive understanding of data governance and ethical frameworks. Ethical AI and Data Management Strategies in Marketing provides a timely and comprehensive solution. This insightful guide offers practical strategies for implementing robust data governance plans that focus on eradicating isolated data repositories and adhering to ethical guidelines. These theoretical and actionable strategies give marketers the confidence to implement them effectively. By leveraging the power of artificial intelligence in marketing, marketers can enhance their understanding of the target audience and optimize content creation while maintaining ethical standards. The book delves into essential topics such as data privacy, ethical marketing, and technology ethics, providing valuable insights and practical solutions for managing data ethically in modern marketing.