Tereza Raquel Merlo – författare

As artificial intelligence (AI) permeates day-to-day life-influencing who is granted what type of healthcare, determining who is granted an employment interview or academic enrollment, or delivering what information to whom-it frames individuals and society. AI has far-reaching powers to improve lives, but it is not without risks. Owing to its limitations, AI may prevent a person from receiving needed healthcare, block a deserving candidate from employment, or present fake and inaccurate information. How to trust that AI systems will improve lives and not create greater inequality and strife? How to foster the benefits of AI and mitigate the harms from AI? Ethical AI and Data Science: Building Trustworthy and Transparent Systems answers these questions.A vital and ongoing dialogue surrounding data, accessibility, and the multifaceted challenges posed by AI in ethics, safety, and societal impact, the book features diverse perspectives and practical approaches written by a panel of experts. Highlights of the book include: Ensuring safety in agentic AI through decision traceability Promoting responsible and ethical AI in financial services Bridging human-machine knowledge for responsible AI Responsible agentic AI for effective cybersecurity and ethical safety The book offers valuable insights into navigating the complexities of developing AI systems that are not only innovative but also transparent, equitable, and secure. This volume aims to advance understanding and foster collaboration among researchers, practitioners, and policymakers, helping to shape AI technologies that responsibly serve society while addressing critical concerns around fairness, accountability, and human well-being.

As artificial intelligence (AI) permeates day-to-day life-influencing who is granted what type of healthcare, determining who is granted an employment interview or academic enrollment, or delivering what information to whom-it frames individuals and society. AI has far-reaching powers to improve lives, but it is not without risks. Owing to its limitations, AI may prevent a person from receiving needed healthcare, block a deserving candidate from employment, or present fake and inaccurate information. How to trust that AI systems will improve lives and not create greater inequality and strife? How to foster the benefits of AI and mitigate the harms from AI? Ethical AI and Data Science: Building Trustworthy and Transparent Systems answers these questions.A vital and ongoing dialogue surrounding data, accessibility, and the multifaceted challenges posed by AI in ethics, safety, and societal impact, the book features diverse perspectives and practical approaches written by a panel of experts. Highlights of the book include: Ensuring safety in agentic AI through decision traceability Promoting responsible and ethical AI in financial services Bridging human-machine knowledge for responsible AI Responsible agentic AI for effective cybersecurity and ethical safety The book offers valuable insights into navigating the complexities of developing AI systems that are not only innovative but also transparent, equitable, and secure. This volume aims to advance understanding and foster collaboration among researchers, practitioners, and policymakers, helping to shape AI technologies that responsibly serve society while addressing critical concerns around fairness, accountability, and human well-being.

As artificial intelligence (AI) permeates day-to-day life—influencing who is granted what type of healthcare, determining who is granted an employment interview or academic enrollment, or delivering what information to whom—it frames individuals and society. AI has far-reaching powers to improve lives, but it is not without risks. Owing to its limitations, AI may prevent a person from receiving needed healthcare, block a deserving candidate from employment, or present fake and inaccurate information. How to trust that AI systems will improve lives and not create greater inequality and strife? How to foster the benefits of AI and mitigate the harms from AI? Ethical AI and Data Science: Building Trustworthy and Transparent Systems answers these questions.A vital and ongoing dialogue surrounding data, accessibility, and the multifaceted challenges posed by AI in ethics, safety, and societal impact, the book features diverse perspectives and practical approaches written by a panel of experts. Highlights of the book include:Ensuring safety in agentic AI through decision traceabilityPromoting responsible and ethical AI in financial servicesBridging human-machine knowledge for responsible AIResponsible agentic AI for effective cybersecurity and ethical safetyThe book offers valuable insights into navigating the complexities of developing AI systems that are not only innovative but also transparent, equitable, and secure. This volume aims to advance understanding and foster collaboration among researchers, practitioners, and policymakers, helping to shape AI technologies that responsibly serve society while addressing critical concerns around fairness, accountability, and human well-being.

As artificial intelligence (AI) permeates day-to-day life—influencing who is granted what type of healthcare, determining who is granted an employment interview or academic enrollment, or delivering what information to whom—it frames individuals and society. AI has far-reaching powers to improve lives, but it is not without risks. Owing to its limitations, AI may prevent a person from receiving needed healthcare, block a deserving candidate from employment, or present fake and inaccurate information. How to trust that AI systems will improve lives and not create greater inequality and strife? How to foster the benefits of AI and mitigate the harms from AI? Ethical AI and Data Science: Building Trustworthy and Transparent Systems answers these questions.A vital and ongoing dialogue surrounding data, accessibility, and the multifaceted challenges posed by AI in ethics, safety, and societal impact, the book features diverse perspectives and practical approaches written by a panel of experts. Highlights of the book include:Ensuring safety in agentic AI through decision traceabilityPromoting responsible and ethical AI in financial servicesBridging human-machine knowledge for responsible AIResponsible agentic AI for effective cybersecurity and ethical safetyThe book offers valuable insights into navigating the complexities of developing AI systems that are not only innovative but also transparent, equitable, and secure. This volume aims to advance understanding and foster collaboration among researchers, practitioners, and policymakers, helping to shape AI technologies that responsibly serve society while addressing critical concerns around fairness, accountability, and human well-being.

In an era where digital transformation is no longer a choice but a necessity, AI-Driven Revolution: Transforming the Business Landscape serves as a comprehensive guide for business leaders, entrepreneurs, and technology enthusiasts, as well as academics and students eager to harness the power of artificial intelligence (AI). This book delves into the profound impact AI is having on businesses and knowledge professions across various industries and fields, providing case studies and suggesting a roadmap for successfully integrating AI into organizational strategies and operations. Readers will find practical advice on developing AI strategies, selecting the right technologies, and aligning AI initiatives with business goals whilst maintaining a discussion on the ethical implications of AI, including data privacy, algorithmic bias, and compliance with regulations, ensuring responsible and sustainable AI practices.The book embarks on an in-depth exploration of AI technologies such as machine learning, natural language processing, and robotics, and their role in driving digital transformation. The chapters utilize detailed case studies to showcase how leading companies have implemented AI to revolutionize their business models, enhance efficiency, and create new value propositions. Using this knowledge, an overview is provided of emerging AI trends and innovations, from advanced analytics and predictive modeling to AI-driven customer experiences. By bridging the gap between theoretical concepts and practical applications, readers are empowered to not only grasp the significance of AI but also effectively implement it within their organizations, ensuring that they are at the forefront of the digital revolution.

This book explores the intersection of artificial intelligence (AI) with knowledge management, ethics, and social justice, shedding light on how technology can perpetuate or mitigate societal inequities. It presents a curated selection of works from the International Conference on Knowledge Management (ICKM) 2024, held at Kent State University, USA, uniting thought leaders, scholars, and practitioners to discuss the opportunities and challenges associated with the rise of AI and to address these challenges head-on.AI is reshaping many aspects of society in a rapid revolution that raises urgent questions of equity, ethics, business, and society. Through theoretical frameworks, case studies, and critical analyses, the contributors to this volume examine the role of AI in diverse sectors such as education, healthcare, governance, and industry, emphasizing its impact on marginalized communities. Key topics include bias in AI algorithms, ethical frameworks for AI governance, equitable access to technology, the role of knowledge management in promoting inclusive decision-making, and the impact of AI in education.The insights presented aim to empower readers to navigate the complexities of AI responsibly and advocate for systems that prioritize fairness and social good. This is an essential resource for academics, policymakers, industry professionals, and anyone interested in understanding how AI shapes societal structures and how we can leverage it for a more equitable future.

In the rapidly evolving AI-driven world, knowledge management (KM) and leadership are critical pillars for organizational success. This volume offers a groundbreaking exploration of how leaders can leverage cutting-edge technology to foster smarter, more adaptive organizations. The book explores the convergence of AI, knowledge management, and leadership, offering actionable strategies to address the challenges and opportunities of the 21st-century digital era. With a focus on diverse businesses and regions worldwide, it delivers fresh perspectives on global knowledge management practices and technological accessibility.Readers will receive practical guidance, including actionable strategies for implementing AI-driven KM systems to enhance decision-making and organizational agility. The book also offers regional insights, exploring how organizations worldwide are innovating in response to complex economic and technological challenges, and presents a variety of leadership strategies that are transforming traditional KM into a dynamic, technology-enabled discipline. These explorations are supported by case studies engaging with real-world examples from diverse industries, illustrating the impact of AI and KM on organizational growth and resilience.Written for business leaders, knowledge managers, and academics, this book combines theoretical insights with hands-on approaches, making it a vital resource for anyone looking to stay ahead in the AI era.

AI-Driven Education: Transforming Teaching, Learning, and Data-Driven Decision Making explores the growing impact of artificial intelligence (AI)-powered tools — such as intelligent tutoring systems, personalized learning platforms, adaptive assessments, and predictive analytics — on modern education. AI is reshaping the education landscape by transforming teaching methodologies, enhancing student learning experiences, and enabling data-driven decision-making. This book provides a comprehensive analysis of AI's role in education, offering insights into how these technologies can improve learning outcomes, optimize institutional performance, and address educational disparities. It examines how AI-driven solutions support educators by automating administrative tasks, enabling real-time feedback, and fostering personalized learning pathways. Additionally, the book discusses the ethical challenges associated with AI adoption, including concerns about data privacy, algorithmic bias, and the importance of maintaining human oversight in AI-driven learning environments.Designed for educators, administrators, policymakers, and ed-tech professionals, this book bridges the gap between theory and practice. It presents real-world applications, case studies, and emerging trends to equip readers with the knowledge and tools needed to implement AI in education effectively. Whether you are an AI advocate, a skeptic, or simply curious about its impact, this book offers valuable perspectives on the evolving relationship between AI and education. By addressing both the opportunities and challenges of AI-driven learning, AI-Driven Education provides a forward-looking exploration of how AI can revolutionize education while ensuring student-centered, ethical, and equitable learning experiences.