Summer is the time for reading, and perhaps also the time for learning something new. If you'd like to gain some insight on AI this summer, you should check out our AI summer reading list. Whether you are a beginner to AI or an AI enthusiast interested in deepening your knowledge, we have selected a few books that will widen your AI horizon.
For the beginner
Having a solid background in math or computer science is a prerequisite to fully understand the technical aspects of AI, but this is not the case for all of us. Luckily there are many ways to learn about AI, the scope and potential of the technology, without having a computer science degree. In recent years, several books have been published with the ambition to inform a general audience about AI. Below you can find the books we recommend for those who would like a good introduction to AI without complicated formulas and technical details.
Melanie Mitchell - Artificial Intelligence: A guide for thinking humans (2019)
In this book from 2019, professor Melanie Mitchell gives an introduction to the field of AI, by providing an overview of the different AI methods and a short history of the development of AI. Mitchell explains why the high ambitions for AI technology have proved challenging to fulfill, and argues that people tend to overestimate the capabilities of AI. The book is entertaining and easy to read, filled with humour and interesting personal reflections, at the same time as it thoroughly explains how the different AI methods work. A warm recommendation to anyone is getting into the field of AI.
Erik J. Larson - The myth about Artificial Intelligence: Why computers can't think the way we do (2021)
This is another book that aims to debunk the too good to be true aspirations about AI. This book was published in spring of 2021. Larson is a tech entrepreneur working with natural language processing. and in this excellent read, he explains why he believes that AI will never be equal to human intelligence.
Morten Goodwin - Myten om maskinene (2020, Norwegian)
The myths related to AI is a popular topic in the literature. This is another great example, written specifically for the Norwegian audience. Denne boken av professor Morten Goodwin (Universitetet i Agder) er langt fra tungt fagstoff, men består av en rekke interessante og morsomme historier med hensikt å knuse mytene som verserer om kunstig intelligens. Resultatet er en god og lettfattelig introduksjon til KI, som vi varmt kan anbefale til alle som vil lære om teknologien og dens muligheter.
Inga Strümke - Maskiner som tenker: algoritmenes hemmeligheter og veien til kunstig intelligens (2023, Norwegian)
Vi vil også så klart anbefale boka "Maskiner som tenker" av vår egen Inga Strümke. Den går nøye gjennom hvordan kunstig intelligens fungerer, helt fra opprettelsen av fagfeltet til hvordan ChatGPT er i dag. Dette kan kanskje høres overveldende ut, men boken er veldig lettlest og roses stadig for å være tilgjengelig for alle uansett forkunnskapsnivå.
Pedro Domingos - The Master Algorithm: How the quest for the ultimate learning machine will change our world (2015)
A different perspective on AI and machine learning is offered in this book from 2015, that is still a relevant read. It introduces the "method areas", groups and compares the different machine learning methods in an easy to comprehend manner. Domingos aims to show how the different machine learning methods can "melt together" in one basic method, that he refers to as "the master algorithm". The book can be downloaded for free from this web page.
George Luger - Artificial Intelligence: Structures and Strategies for Complex Problem Solving (6th Edition, 2009)
This one is for those who feel nostalgic about the school days and would like to read a proper AI textbook. This book is recommended by professor emeritus Agnar Aamodt (NTNU), who used the book in a former introduction course to AI which was open to students with various backgrounds. It gives a good introduction to AI, but is less focused on math and requires less background knowledge than most of the textbooks being used in university classes. Although a few years have gone by since this book was published, it covers the "broadness" of AI in a nice way. The first chapters give a thorough introduction to the history and principles of AI. The previous edition of the book can be downloaded for free from the author's web pages.
Stuart J. Russel - Human compatible: Artificial Intelligence and the Problem of Control (2019)
Several of the books that have been written about AI in recent years try to look into the future and make predictions about how AI will change our lives and societies. For sure, nobody can predict the future, but this book makes a decent effort. This is a book from 2019 by leading computer scientist Stuart J. Russel, which discusses the risk to humanity from advanced artificial intelligence and argues that advanced AI is a serious concern despite the uncertainty surrounding its future progress. In this futuristic book, Russel lays out a new approach to AI that he claims will enable us to coexist successfully with increasingly intelligent machines.
looking into the future
For the AI enthusiast
For those who are interested in getting deep into the technical details of AI, our professors make the following literature recommendations
On Deep learning: Ian Goodfellow and Yoshua Bengio and Aaron Courville - Deep Learning (2015)
This comprehensive book on the topic of deep learning is written for anyone who would like to deepen their knowledge of deep learning, and get familiar with the theoretical concepts behind the technology. You can find a free version of the book on this web page.
On Reinforcement learning: Sutton & Barto - Reinforcement learning: An introduction (2018)
In this book, Sutton and Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent develoments and applications.
On Bio-AI: Keith Downing - Intelligence Emerging (2015)
Our own Professor in Computer Science Keith Downing, has written an excellent book for anyone who would like to obtain deeper knowledge of neural networks and their inspiration from the human brain.
On Predictive neural nets: Keith Downing - Gradient Expectations (2023)
Keith is also coming out with another book this summer, where he maps the origins and anatomy of natural and artificial neural networks and does a combined look on research within neuroscience, cognitive science, and connectionism.
On AI and Health: Ishita Barua - Kunstig intelligens redder liv - AI er legenes nye superkrefter (2023, Norwegian)
Ishita Barua er forsker og lege, og i denne boken om AI og helse skriver hun om de ulike måtene denne teknologien kan brukes for forbedre helsehjelp - og i forlengelse redde liv. Vår egen forsker, Inga Strümke, er også bidragsyter.
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Vil du lære om AI gjennom et kurs i stedet?
Lurer du på hva kunstig intelligens egentlig er og hva teknologien kan brukes til? Da er Elements of AI noe for deg!
NTNU og Norwegian Open AI Lab tilbyr et online intro-kurs om kunstig intelligens: Elements of AI. I løpet av kurset lærer du det grunnleggende om KI, samt mulighetene og begrensninger som finnes i KI-teknologi.
