The AI and Data Revolution
Understanding the New Data Landscape
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Product details:
- Edition number 1
- Publisher Facet Publishing
- Date of Publication 24 April 2025
- ISBN 9781783307081
- Binding Paperback
- No. of pages192 pages
- Size 234x156x3 mm
- Language English 690
Categories
Short description:
Grounded in theory, this book uses real-life case studies to illustrate how the collection, manipulation and application of data are reshaping businesses. It explains what this means for your organisation and strategies for staying ahead of this data and AI revolution.
MoreLong description:
We are entering a new phase in the information revolution driven by the introduction of innovative artificial intelligence (AI) technologies. From the rise of mass media, mass communications and the expansion of the internet, to mobile computing, social networks and Generative AI, this important and authoritative book outlines the key changes over the last 30 years that have led to this moment.
Drawing on established frameworks, theories, historical research and empirical evidence, this book argues that the current wave of AI-driven innovations represents a step-change in how organisations can extract value from data and that this will have significant implications for business innovation and how companies compete. Individual chapters explore
- the history of the information industry and key milestones in artificial intelligence
- an overview of the data and AI landscape
- the opportunities and challenges of the AI revolution
- the ethical, policy and legal issues of data-driven AI
- and scenarios for where the data revolution is heading up to 2030
Insightful and accessibly written, The AI and Data Revolution is a valuable resource for knowledge managers, information managers and data analysts as well as researchers and students in library, information and computer sciences.
MoreTable of Contents:
Introduction
Chapter 1: How Did We Get Here?
Chapter 2: The Current AI and Data Landscape
Chapter 3: The Emerging Data-Driven AI Revolution
Chapter 4: Ethical, Policy and Legal Issues of Data-Driven AI
Chapter 5: Looking Ahead
Chapter 6: Pulling the Threads Together
Conclusion
Index
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