Recommended reading on AI and technology

Given the seismic changes introduced by generative AI in the past couple of years, this book may appear somewhat dated. Nevertheless, it offers an excellent historical overview of the field by a prominent frontline participant. In fact, the juxtaposition between deep learning and abstract and analogical reasoning that the book ends with is particularly poignant today, highlighting the natural limits of the currently dominant AI paradigm. 

Written in an expertly accessible style, this book provides an intuitive introduction to the fundamental algorithms guiding much of optimisation and automatic decision-making today. The authors emphasise links and parallels between human and algorithmic thinking, leaving the reader both admiring the unintentional robotic perfection of many human and social behaviours and anticipating a familiar, human-like intelligence from machines in the future. 

This is a nearly complete collection of Isaac Asimov’s short stories about robots. Most of these stories revolve around “AI alignment” problems – situations where robots go rogue and act against human’s’ values and goals. What is most notable about the situations Asimov describes is that the robots misbehave not because they violate the three laws of robotics, but because they stick to the letter of these laws. But do not worry – Susan Calvin, the cold and stern robopsychologist who has trouble understanding and interacting with fellow humans, will be there to analyse and outsmart the machines! 

We might think of AI as something we do on our computers, with little regard to the actual infrastructure – both physical and human – that underpins it. This book explores the AI ecosystem, exposing its exploitative underbelly. Based on extensive interviews, it presents a number of profiles of individuals involved: for example, an underpaid data annotator in East Africa, a data centre engineer in Iceland, a voice artist whose voice (and work) has been “stolen”, and a highly-paid data scientist living a sophisticated city life.  

Concisely written, but with a wide scope, this is a very thoughtful book from a leading AI researcher. It discusses the development of AI and its possible future, limitations and challenges. The “shortcut” referred to in the title is the methodological switch from logical symbolic methods to those based on statistics and probability which make use of huge datasets and computing power. 

Recent years have seen both an explosion in AI systems and a corresponding rise in critical analyses of such technologies. Feminist scholarship has been central to this critique, showing the ways that the design and deployment of AI can further, rather than undermine, the pursuit of social justice. This excellent anthology persuasively demonstrates why AI is a feminist issue. 

This insightful and meticulously researched book makes a compelling case that the “connective labour” or socioemotional skills increasingly important to millions of jobs, both old and new, are at risk of being lost with the automation of jobs. Pugh argues that we need to protect this vital humane work and the face-to-face interactions that are so essential to our wellbeing. The book is a refreshing challenge to the promissory discourse about AI being able to replicate and even surpass human capacities/capabilities. 

This book by Richard Susskind, the well-known futurologist who has written about the future of professions, lawyers and courts, is the perfect introduction for someone new to the subject of AI and its challenges. Susskind writes about AI in an instantly accessible way and focuses not on how AI functions but on what it does in terms of its societal impact. He shows how AI is likely to change our lives in the future and asks us to think whether we are ready to meet that challenge. 

This is not strictly a book about AI but rather one about the lakes of big data which are the fuel of modern AI. O’Neil examines how data extracted from these data lakes may be used to make algorithmic decisions about you, and how bias, error or the mistakes made in selecting proxy data can impact our lives. It’s a book that gets “under the hood” of how AI works.

AI 2041 presents insightful, narrative-driven scenarios that illuminate the societal and ethical implications of AI, encouraging critical reflection on its near-future impact. 

In Generative AI in Education, B Mairéad Pratschke offers a timely and practical guide for educators to the role of AI in learning innovation. She takes a critical, theory-based perspective and presents it in a practical and accessible way. After introducing the reader to AI and digital education, the book offers practical strategies for educators to begin their teaching innovation journey with generative AI (GAI). Taking a constructive and forward-looking perspective, Pratschke encourages educators to rethink traditional teaching and assessment methods and co-design more interactive, personalised and innovative learning approaches that equip students with the skills they need in the AI age.