Название: The AI and Data Revolution: Understanding the New Data Landscape
Автор: Martin De Saulles
Издательство: Facet Publishing
Год: 2025
Страниц: 252
Язык: английский
Формат: pdf, epub (true)
Размер: 10.1 MB

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 organizations can extract value from data and that this will have significant implications for business innovation and how companies compete.

Before looking in detail at where all these exabytes of data are coming from, it is worth noting that there are two broad types of data that make up what IDC calls the ‘global datasphere’: structured and unstructured data. According to IDC, unstructured data makes up more than 90% of the data being created each year. Structured data fits easily into tabular format and includes types such as numbers, dates and short text descriptors. Unstructured data cannot be slotted neatly into tables and comprises formats such as audio and video files and large quantities of text. The processing of structured data is straightforward using tools such as standard query language (SQL) databases. Making sense of unstructured data requires more elaborate approaches, including data visualisation, programmatic manipulation and Machine Learning (ML). From a user perspective, structured data allows organisations to build workflows more easily around their information, but the predefined structure constricts users to a more limited range of functionality. Unstructured data is more complex to manage and extract value from but, once harnessed, can be put to a wider range of purposes. Much of data gathering and processing carried out by AI firms such as Anthropic and OpenAI has involved collecting disparate sets of unstructured data from websites and feeding it into their large language models (LLMs).

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
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.