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The Quantified Worker
The information revolution has ushered in a data-driven reorganization of the workplace. Big data and AI are used to surveil workers and shift risk. Workplace wellness programs appraise our health. Personality job tests calibrate our mental state. The monitoring of social media and surveillance of the workplace measure our social behavior. With rich historical sources and contemporary examples, The Quantified Worker explores how the workforce science of today goes far beyond increasing efficiency and threatens to erase individual personhood. With exhaustive detail, Ifeoma Ajunwa shows how different forms of worker quantification are enabled, facilitated, and driven by technological advances. Timely and eye-opening, The Quantified Worker advocates for changes in the law that will mitigate the ill effects of the modern workplace.
Fairness and Machine Learning
An introduction to the intellectual foundations and practical utility of the recent work on fairness and machine learning. Fairness and Machine Learning introduces advanced undergraduate and graduate students to the intellectual foundations of this recently emergent field, drawing on a diverse range of disciplinary perspectives to identify the opportunities and hazards of automated decision-making. It surveys the risks in many applications of machine learning and provides a review of an emerging set of proposed solutions, showing how even well-intentioned applications may give rise to objectionable results. It covers the statistical and causal measures used to evaluate the fairness of machin...
Privacy, Due Process and the Computational Turn
Privacy, Due process and the Computational Turn: The Philosophy of Law Meets the Philosophy of Technology engages with the rapidly developing computational aspects of our world including data mining, behavioural advertising, iGovernment, profiling for intelligence, customer relationship management, smart search engines, personalized news feeds, and so on in order to consider their implications for the assumptions on which our legal framework has been built. The contributions to this volume focus on the issue of privacy, which is often equated with data privacy and data security, location privacy, anonymity, pseudonymity, unobservability, and unlinkability. Here, however, the extent to which predictive and other types of data analytics operate in ways that may or may not violate privacy is rigorously taken up, both technologically and legally, in order to open up new possibilities for considering, and contesting, how we are increasingly being correlated and categorizedin relationship with due process – the right to contest how the profiling systems are categorizing and deciding about us.
Ethics of Data and Analytics
Unique selling point: Applies business ethics to the use of analytics, data, and AI Core audience: Graduate and undergraduate business students Place in the market: Graduate and undergraduate textbook
Challenges of Law and Technology - Herausforderungen des Rechts und der Technologie - Retos del Derecho y de la Tecnología
Law and technology present humanity with challenges and opportunities. This international research volume is dedicated to three of their pillars: artificial intelligence, blockchain and digital platforms. The authors' contributions analyze these topics from different perspectives of public and private law in the German, Austrian, European, American, Japanese, and Latin American contexts.
Applications, Challenges, and the Future of ChatGPT
The rapid progress of artificial intelligence (AI) technologies has resulted in a complicated landscape for researchers and practitioners. Understanding and navigating the complexities of AI applications, particularly in the context of ChatGPT and its interactions with other AI tools, can be challenging. Researchers and academics need guidance to keep up with these technologies' evolving trends and implications, which leads to gaps in knowledge and implementation strategies. Additionally, the ethical and societal impacts of integrating AI into various domains remain a significant concern, requiring a comprehensive approach to address. Applications, Challenges, and the Future of ChatGPT provi...
Privacy
An incisive compendium of philosophical literature on privacy, part of the acclaimed Wiley-Blackwell Readings in Philosophy series Companies collect and share much of your daily life, from your location and search history, to your likes, habits, and relationships. As more and more of our personal data is collected, analyzed, and distributed, we need to think carefully about what we might be losing when we give up our privacy. Privacy is a thought-provoking collection of philosophical essays on privacy, offering deep insights into the nature of privacy, its value, and the consequences of its loss. Bringing together both classic and contemporary work, this timely volume explores the theories, ...
The Economics and Regulation of Digital Markets
Presenting new findings and perspectives from leading international scholars on three critical areas of developing government policies: Digital markets and their regulation, the divergence of expert and public views on European democracy, and the effects of firing notification procedures on wage growth.
Responsible AI in the Enterprise
Build and deploy your AI models successfully by exploring model governance, fairness, bias, and potential pitfalls Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn ethical AI principles, frameworks, and governance Understand the concepts of fairness assessment and bias mitigation Introduce explainable AI and transparency in your machine learning models Book DescriptionResponsible AI in the Enterprise is a comprehensive guide to implementing ethical, transparent, and compliant AI systems in an organization. With a focus on understanding key concepts of machine learning models, this book equips you with techniques and algorithms to tackle complex issues such as...
Artificial Intelligence in Finance
This book provides a comprehensive analysis of the primary challenges, opportunities and regulatory developments associated with the use of artificial intelligence (AI) in the financial sector. It will show that, while AI has the potential to promote a more inclusive and competitive financial system, the increasing use of AI may bring certain risks and regulatory challenges that need to be addressed by regulators and policymakers.
