AI Act compact (eBook)

Compliance, management & use cases in corporate practice

Peter Hense, Tea Mustac (Autoren)

eBook Download: PDF

2024 | 1. Auflage
329 Seiten
Fachmedien Recht und Wirtschaft (Verlag)
978-3-8005-9772-7 (ISBN)

Infos

The EU AI Act is here, and contrary to popular opinion, it is not just Europe's problem. As the first comprehensive law to regulate AI systems, the AI Act attempts to establish a global framework, setting limits on dynamic technological developments and creating new legal responsibilities for organisations worldwide. The AI Act's definition of AI systems is expansive, covering a wide range of technologies, even those that, until recently, were considered traditional machine learning models. This makes understanding and preparing for compliance even more critical, because if your business involves AI, the AI Act is now your business. 'AI Act Compact' is your go-to tool for tackling the challenges imposed by the Act. Written by Tea Mustac and Peter Hense, experienced legal experts and hosts of the podcast 'RegInt: Decoding AI Regulation,' this book provides a deep dive into the AI Act's key provisions, processes, and real-world implications. The AI Act introduces a new risk-based framework, establishing compliance assessments and relying on harmonized standards. It imposes obligations for data governance, data quality management, accuracy and robustness, risk management, explainability, non-discrimination, accountability, liability, human controllability and more. Implementing these requirements presents significant practical challenges, especially given their broad application to numerous actors along the AI supply chain. Drawing heavily on international technical standards from CEN/CENELEC, ISO, IEC, and IEEE, the authors provide a practical toolkit for managing AI risks and ensuring compliance. Whether you're a lawyer, data scientist, or machine learning engineer, this book offers clear, actionable strategies for staying compliant and competitive in this fast-evolving landscape.

Peter Hense, lawyer and partner at Spirit Legal, specializes in the fields of technology, data, research and development and privacy engineering. For over a decade, he has been working with leading R and D-companies on machine learning, in particular artificial neural networks and knowledge graphs. His focus is on compliance and data governance in the context of automated decision-making systems (Accountable AI). Translated with DeepL.com (free version) Tea Mustac, Mag. iur. is an expert in European and international technology and IP law at Spirit Legal. She advises and publishes at the interface of law and technology, with a particular focus on artificial intelligence. Together with Peter Hense, she hosts the English-language podcast 'RegInt: Decoding AI Regulation'.

Produkt-Details

• Erscheint lt. Verlag: 25.11.2024
• Reihe/Serie: InTeR-Schriftenreihe
• Verlagsort: Frankfurt am Main
• Sprache: englisch
• Themenwelt: Recht / Steuern ► Wirtschaftsrecht
• Schlagworte: Accountability • AI regulation • Artificial Intelligence • bücher für juristen • Buch Recht • Buch Recht und Wirtschaft • CDSMD • Compliance Literatur • compliance management • compliance testing • da • data governance • data protection • Data Quality • Datenqualität • Datenschutz • Deutsche Gesetze Buch • Deutscher Fachverlag GmbH • dga • Diskriminierungsverbot • DMA • DSGVO • EU AI Act • fachbücher recht • Fachbuch Recht • Fachbuch Verlag • Fachliteratur Recht • fachmedien recht und wirtschaft • Gesetzbuch bestellen • Gesetze Buch • Gesetze Bücher • Gesetze kaufen • jura bücher • Jura Recht • juristische Bücher • Juristische Literatur • juristischer Fachverlag • KI-Verordnung • Konformitätsprüfung • Künstliche Intelligenz • Nachschlagewerk • nachschlagewerk recht • Non-Discrimination • Peter Hense • Rechenschaftspflicht • Recht • Rechtshandbuch • Recht und Wirtschaft • Risikoklassen • risk classes • Risk Management • Tea Mustac • training data • Trainingsdaten • Unternehmenspraxis • Use Cases • Verlag Recht • Verlag Recht und Wirtschaft Frankfurt
• ISBN-10: 3-8005-9772-1 / 3800597721
• ISBN-13: 978-3-8005-9772-7 / 9783800597727