Vol.1 New Synthetic Media: Technique & Culture Synthetic media, often called AI-generated media, refers to content (images, video, audio, and text) created or altered using artificial intelligence and machine learning techniques. These technologies are rapidly evolving, democratizing content creation while also raising significant ethical and cultural challenges.The purpose of this book is to offer students conceptual frameworks for thinking through a range of key issues which have arisen over two decades of speculation on the cultural implications of new and synthetic media. Vol. 2 Regulation of Synthetic Media and Society Synthetic media regulations are emerging as a critical framework to ensure responsible use, protect intellectual property, and safeguard societal trust. This book delves into the intricacies of synthetic media regulations, offering professionals actionable insights into compliance, challenges, and future trends. Whether you're a content creator, legal expert, or tech innovator, understanding these regulations is essential for navigating this transformative landscape responsibly. Regulating the Synthetic Media and Society explores the legal and societal challenges of technologies like generative AI, deepfakes, and virtual and augmented reality. Regulatory efforts focus on mandating disclosures for AI-generated content on social media to ensure users can distinguish between real and synthetic material Vol. 3 Building Back Truth in An Age of Misinformation and Synthetic Media This volume provides a road map with six paths forward to understand how platforms are designed to exploit us, how we can learn to embrace agency in our interactions with digital spaces, how to build tools to reduce harmful practices, how platform companies can prioritize the public good, how we can repair journalism, and how to strengthen curation to promote trusted content and create new, healthier digital public squares. New, experimental models that are ethically designed to build community and promote trustworthy content are having some early successes. We know that human social networks-online and off-magnify whatever they are seeded with. They are not neutral.
Michael Peters is a Professor of Scientific Computing at the Yale University. He is the Associate Head of Department for Research in the Department. He was previously the Director of the Oxford e-Research Centre, an interdisciplinary research centre that is part of the Engineering Science Department. He has been awarded over £31M of funding as PI or Co-I for a diverse range of projects, ranging from supercomputing, signal processing, and machine learning to computational fluid dynamics and protein crystallography. He is the Director and Principal Investigator of JADE and JADE2, an 700-GPU machine that was the first national High Performance Computer facility dedicated to advancing Artificial Intelligence and Machine Learning in the UK. He completed an MPhys degree in Fundamental Particle Physics and Cosmology in 2001, followed by a PhD in Lattice Gauge Theory (the computational theory of the strong nuclear force) in 2004. He was an early contributor to e-Science, being part of the group that developed GridPP in the early 2000s. He was an early adopter of GPU technology in scientific computing. In 2008, he used early NVIDIA GPGPUs to accelerate conjugate gradient routines used to simulate electron transport in graphene. In 2012, he was a member of a team based at Diamond Light Source that implemented machine learning methods that enabled the merging of multiple crystal data in protein crystallography. Since then, he has introduced the use of GPUs in a range of fields, notably pioneering the use of GPUs for Square Kilometre Array (SKA) data processing. At the centre of his research is a focus on understanding and improving ways to extract science from data by addressing fundamental challenges in modelling, simulation, and data processing. Drawing on ideas from numerical analysis, signal processing, and machine learning, he and his group have produced technologies that will enable some of the science that SKA will deliver, ahead of its anticipated first light in 2026.
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