The latest news and developments on AI in the form of articles, blogs, emails, conference papers and presentations cross the desk (or screen) of information professionals every day. Aware that publishing schedules rarely enable books to keep up with the pace of change, particularly in the constantly evolving AI arena, I approached reviewing this publication with some slight hesitation.
The author, Martin De Saulles, a technology analyst and writer who focuses on the impacts of digital innovations on organisations and the broader economy, sets out his aim for the book as “helping the reader have a broad understanding of the forces currently driving the AI and data sectors and where it all might lead”. He refers to the book “as a useful starting point for understanding these forces and what they mean for how we work”. He succeeds in that aim. The reader is left with a clear understanding of the data landscape as at the end of 2024, how we got to that point and a sense of what shape the future might take. The book gathers many threads, including societal, commercial and regulatory issues, and pulls them together successfully in a very accessible manner. It is centred around how the current wave of AI-driven innovations represents a step-change in how organisations can extract value from data and the significant implications this will have for business innovation and competition.
The first chapter takes us through a clear and comprehensive timeline of the development of the information age, the role of technology, introduces us to the scope and scale of data – a recurring theme - and sets out a brief history of AI; introducing the reader to terms including Machine Learning, Deep Learning, Generative AI, and Large Language Models. The use of real-world examples, case studies and figures throughout the book enhance the reader’s experience and understanding.
Chapter 2 looks at data in more detail, why there has been such an increase in volume, where has it come from, formats, and how it is being used. The storage, organisation and retrieval of data/information/knowledge is central to the role of the information professional so familiarity with some of the content was to be expected, but the breadth of coverage made for a fascinating read. Not only were familiar concepts of structured and unstructured, public and private sector data detailed, but the more recent concept of synthetic data was also introduced. This chapter comprehensively sets out the role and the value of data in today’s world, demonstrated by the operation and success of familiar companies such as Alphabet and Apple.
In Chapter 3 the author moves on to the thought-provoking theme of the ‘Data-Driven AI Revolution’, and the focus on how data-driven AI is impacting on organisations, the way they work and the products and services they offer. The challenges of making forecasts are immediately acknowledged, but using solid examples, the author takes us through the opportunities presented by AI, including the potential for the information professional, while also recognising and discussing the challenges.
Ethical, policy and legal issues of data-driven AI are the focus of Chapter 4. Initiatives and policies are dealt with on a national and international scale. The author looks at how the UK, EU and US have responded to the pace and scale of changes in technology and AI. It is balanced, reflecting on commercial realities as well as the rights of citizens. The legislation is explained and relevant examples used to ensure the reader understands how these laws are working in practice. Many of the premises underlying the why and the how of those policies and initiatives remain relevant, but this is one of the pitfalls of a text written at the end 2024 just before the change in administration in the United States. Even though the author makes certain forecasts about possible approaches and policies, the global impact of this change could not have been anticipated.
Chapter 5 looks at how the social and economic implications of the developments in AI and the data industry might play out. The theme of uncertainty runs throughout the chapter. Practical aspects such as unemployment and the role of human judgement are discussed. The author identifies trust as key – how can we trust what we see or hear? How do we differentiate between truth and fiction? Misinformation and cybersecurity are discussed. Education and training, in the form of data literacy and media literacy, are presented as key for the future. The realities of global challenges including energy shortages, the requirement for ever more data to train models, the role of APIs and the demand on physical infrastructure are identified. The author speculates on developments to 2030, and the regulatory and commercial environment to 2030. Again, my reading of this was coloured by global events subsequent to the date of writing. The author then pulls his many threads together in a very brief final chapter.
Many facets of this book captured my attention, the discussion on information and data literacy, the sheer scale of volumes of data involved, the commercial value and monetisation of data, the role played by platforms and networks, and the ability of companies who are household names to leverage existing connections. This work will leave the reader with a better overall understanding of what recent developments in AI and the data behind it mean for organisations.
