Safety in the Digital Age: Sociotechnical Perspectives on Algorithms and Machine Learning

This book gathers authors from a wide range of social-scientific and engineering disciplines to review challenges from their respective fields that arise from the processes of social and technological transformation taking place worldwide. The result is a much-needed collection of knowledge about the integration of social, organizational and technical challenges that need to be tackled to uphold safety in the digital age.
The contributors whose work features in this book help their readers to navigate the massive increase in the capability to generate and use data in developing algorithms intended for automation of work, machine learning and next-generation artificial intelligence and the blockchain technology already in such extensive use in real-world organizations.
This book deals with such issues as:
· How can high-risk and safety-critical systems be affected by these developments, in terms of their activities, their organization, management and regulation?

· What are the sociotechnical challenges of the proliferation of big data, algorithmic influence and cyber-security challenges in health care, transport, energy production/distribution and production of goods?
Understanding the ways these systems operate in the rapidly changing digital context has become a core issue for academic researchers and other experts in safety science, security and critical-infrastructure protection. The research presented here offers a lens through which the reader can grasp the way such systems evolve and the implications for safety—an increasingly multidisciplinary challenge that this book does not shrink from addressing.