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Synthetic Hate investigates how extremists exploit artificial intelligence to modernize the world’s oldest hatred. Antisemitism - rooted in religious discrimination, medieval blood libels, Nazi propaganda, and contemporary Islamist and far-right conspiracies - has found new life through generative tools that can produce persuasive text, images, audio, and video at scale.Drawing on documented cases and controlled demonstrations, the book shows how LLMs, deepfakes, bots, and recommendation systems enable cheap, rapid, and adaptive propaganda - memes that evade moderation, fabricated “evidence,” synthetic voices, and narrative laundering that spreads across platforms and into mainstream feeds. The result is not “new” hate, but hate that is faster, more convincing, and harder to police.Crucially, Synthetic Hate goes beyond diagnosis, and it lays out a practical counterstrategy of technical safeguards, platform accountability and regulation, and education and resilience, so policymakers, researchers, and practitioners can blunt AI-amplified antisemitism and hate without sacrificing democratic values.

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Synthetic Hate investigates how extremists exploit artificial intelligence to modernize the world’s oldest hatred. Antisemitism - rooted in religious discrimination, medieval blood libels, Nazi propaganda, and contemporary Islamist and far-right conspiracies - has found new life through generative tools that can produce persuasive text, images, audio, and video at scale.Drawing on documented cases and controlled demonstrations, the book shows how LLMs, deepfakes, bots, and recommendation systems enable cheap, rapid, and adaptive propaganda - memes that evade moderation, fabricated “evidence,” synthetic voices, and narrative laundering that spreads across platforms and into mainstream feeds. The result is not “new” hate, but hate that is faster, more convincing, and harder to police.Crucially, Synthetic Hate goes beyond diagnosis, and it lays out a practical counterstrategy of technical safeguards, platform accountability and regulation, and education and resilience, so policymakers, researchers, and practitioners can blunt AI-amplified antisemitism and hate without sacrificing democratic values.

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This book comprehensively discusses the cooperation of corporations with startups in the context of accelerator programs. It focuses on recognizing how open innovation can catalyze startups’ development and success, and benefit corporations through access to new business models, innovative products, services and technologies developed outside the R&D departments of large organizations.The book presents a variety of collaboration models, motivations, barriers and potential for collaboration, offering readers a wealth of theoretical and practical knowledge based on the author’s research and experience in managing startup acceleration programs for multinational corporations. Readers will gain insight into the challenges and critical aspects of startup accelerator programs via a detailed analysis of open innovation theory and collaboration strategies. Based on literature and empirical research, the author offers practical guidance on how corporations should prepare and conduct acceleration activities to maximize the potential of innovation from startups and increase the chances of success.Open Innovation and Startups will appeal to scholars and researchers in the fields of innovation studies, entrepreneurship and organizational studies.The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non-Commercial-No Derivative Licence (CC-BY-NC-ND) 4.0 International license.

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