Here are 100 books that This Could Be Important fans have personally recommended if you like
This Could Be Important.
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My passion for generative AI first ignited in 2016 when I spoke about it at a conference, and ever since then, I can’t stop! I've created an online course, a newsletter and even wrote a book to spread knowledge on this groundbreaking technology. As an instructor, I empower others to explore the boundless potential of generative AI applications. Day in day out, I assist clients in crafting their own generative AI solutions, tailoring them to their unique needs.
I truly believe that this is the book that brought my generation of AI experts into the fold. Despite having studied AI and ML, this book took me by the hand and grounded me in the fundamentals. I love the fact that it covers everything from mathematical basics to industry-level techniques.
Written by the OGs of deep learning, it's an absolute must-read for anyone serious about the field. Highly recommend for students and engineers alike.
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.
“Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all…
Magical realism meets the magic of Christmas in this mix of Jewish, New Testament, and Santa stories–all reenacted in an urban psychiatric hospital!
On locked ward 5C4, Josh, a patient with many similarities to Jesus, is hospitalized concurrently with Nick, a patient with many similarities to Santa. The two argue…
As a child of the microcomputer revolution in the late 1970s, I’ve always been fascinated by the concept of a general-purpose machine that I could control. The deep learning revolution of 2010 or so, followed most recently by the advent of large language models like ChatGPT, has completely altered the landscape. It is now difficult to interpret the behavior of these systems in a way that doesn’t argue for intelligence of some kind. I’m passionate about AI because, decades after the initial heady claims made in the 1950s, AI has reached a point where the lofty promise is genuinely beginning to be kept. And we’re just getting started.
Goodfellow’s Deep Learning is a must in the field because it was the first. Prince’s new book is an essential follow-up to be up-to-date with the latest model types, including diffusion models (think Stable Diffusion or DALL-E), transformers (the heart of large language models), graph networks (reasoning over relationships), and reinforcement learning.
The math level is similar to what you’ll find in Goodfellow’s book.
An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.
Deep learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts. Many deep learning texts are crowded with technical details that obscure fundamentals, but Simon Prince ruthlessly curates only the most important ideas to provide a high density of critical information in an intuitive and digestible form. From machine learning basics to advanced…
As a child of the microcomputer revolution in the late 1970s, I’ve always been fascinated by the concept of a general-purpose machine that I could control. The deep learning revolution of 2010 or so, followed most recently by the advent of large language models like ChatGPT, has completely altered the landscape. It is now difficult to interpret the behavior of these systems in a way that doesn’t argue for intelligence of some kind. I’m passionate about AI because, decades after the initial heady claims made in the 1950s, AI has reached a point where the lofty promise is genuinely beginning to be kept. And we’re just getting started.
Woolridge presents the history of artificial intelligence from the point of view of an insider. This book is one of the few accounts of AI history presenting a measured perspective, one that has weathered more than one boom and bust cycle.
The book is nicely complemented by his recent series of lectures, which can be easily found on YouTube. I read Woolridge as saying, “Yes, something new has happened with the advent of large language models, but much work remains.”
From Oxford's leading AI researcher comes a fun and accessible tour through the history and future of one of the most cutting edge and misunderstood field in science: Artificial Intelligence
The somewhat ill-defined long-term aim of AI is to build machines that are conscious, self-aware, and sentient; machines capable of the kind of intelligent autonomous action that currently only people are capable of. As an AI researcher with 25 years of experience, professor Mike Wooldridge has learned to be obsessively cautious about such claims, while still promoting an intense optimism about the future of the field. There have been genuine…
A poisonous maiden, a Daoist sex cult, and a violent insurgency.
The polyandrous Yan family in China's rural Shaanxi Province takes in two carpenter brothers. When one brother is convicted of murder after killing their neighbor in a dispute, a constable threatens to expose the family's rumored polyandry and extorts…
As a child of the microcomputer revolution in the late 1970s, I’ve always been fascinated by the concept of a general-purpose machine that I could control. The deep learning revolution of 2010 or so, followed most recently by the advent of large language models like ChatGPT, has completely altered the landscape. It is now difficult to interpret the behavior of these systems in a way that doesn’t argue for intelligence of some kind. I’m passionate about AI because, decades after the initial heady claims made in the 1950s, AI has reached a point where the lofty promise is genuinely beginning to be kept. And we’re just getting started.
Alan Turing’s 1936 paper “On Computable Numbers, with an Application to the Entscheidungsproblem” was foundational to the development of computer science. To this day, Turing machines, the theoretical computational devices imagined in Turing’s paper, are a research cornerstone as they embody the concept of “computable.” If a programming language can implement a Turing machine, then the language is deemed Turing complete and is, therefore, general-purpose enough to implement any algorithm.
Turing’s paper is readable, but Petzold’s book breaks it down in minute detail to explain the nomenclature and meaning behind Turing’s words. I believe all computer science students should study this paper, and you’ll be hard-pressed to find a more thorough review than the one presented in this book.
Programming Legend Charles Petzold unlocks the secrets of the extraordinary and prescient 1936 paper by Alan M. Turing
Mathematician Alan Turing invented an imaginary computer known as the Turing Machine; in an age before computers, he explored the concept of what it meant to be computable, creating the field of computability theory in the process, a foundation of present-day computer programming.
The book expands Turing's original 36-page paper with additional background chapters and extensive annotations; the author elaborates on and clarifies many of Turing's statements, making the original difficult-to-read document accessible to present day programmers, computer science majors, math…
I spent over forty years developing complex, software-intensive systems, and the Association of Computing Machinery honored me with the title of distinguished engineer. AI and robotics have been my main technical focus for the last 5 years. For the last couple of years, I have been binge-watching videos on advances in AI and robotics and binge-reading books on the topic. I am also a multi-award-winning author of science fiction novels and short stories. Most of the short stories in my coming book involve AI and robots.
I really loved this book because of its wide breadth. If you are only going to read a single book on AI and its ramifications, this would be my top recommendation.
It covers everything from the history of artificial intelligence to what the short- and mid-term future will look like. This book provides a solid foundation to help you prepare for a future dominated by AIs and robots.
"Machines of Tomorrow offers a fascinating journey into the future of AI, providing a unique perspective that combines technology, economics, geopolitics, and history." — PASCAL BORNET, Technology Influencer, 2 million followers.
How AI Will Shape Our World.
Written in an easy-to-read style accessible to everyone, "Machines of Tomorrow" grounds the reader in a thorough history and description of Artificial Intelligence, enabling an appreciation of its real trajectory and ultimately a deeper level of engagement with the core concept of the book: what should societies expect from AI in the coming decades?
I tell stories for the page and the screen (and sometimes to bribe my kid to brush her teeth). The stories I tell have one thing in common – they transport the reader to another world. For me, building a new world starts with building a new character – a narrator with strong opinions and a complicated past that will shape how the reader experiences their world. We don't experience the real world objectively – no matter how hard we try, our past, our feelings, and even our bodies affect how we experience the world. That's why the worlds I build and the stories I tell are all filtered through the particular truth of a bold narrator.
Illuminae is the first book in a YA science fiction series called the Illuminae Files Trilogy.
The story is told through intersecting first-person narratives constructed from journals, letters, texts, reports, and pictures. You want to absorb all that “found footage” goodness on paper. Trust.
There’s almost no exposition in Illuminae, especially in the first few chapters. That’s the beauty of these books – the narration is so visceral and urgent that you get invested in the story long before you really understand what’s happening. Putting the pieces of the world-building together is an addictive mystery in and of itself.
I don’t recommend cracking open this book the night before anything requiring a good night’s rest and lots of focus – your mind will be in 2575 until well after you’ve finished the last page.
'Never have I read a book so wholly unique and utterly captivating.' Marie Lu
'It certainly filled the Battlestar Galactica-shaped hole in my heart.' Victoria Aveyard
The internationally bestselling first book in a high-octane trilogy
Kady thought breaking up with Ezra was the worst thing she'd ever been through. That was before her planet was invaded. Now, with enemy fire raining down on them, Kady and Ezra are forced to fight their way onto one of the evacuating craft, with an enemy warship in hot pursuit.
But the warship could be the least of their problems.…
Big Ideas... For Small Businesses
by
John Lamerton,
Big Ideas… for Small Businesses is a straight-talking, no-nonsense guide to growing a small business without sacrificing your lifestyle. Written by a former civil servant turned entrepreneur, the book challenges hustle culture and instead champions the idea of an "ambitious lifestyle business" - one that provides freedom and financial stability,…
The art of computer programming is a lot like the art of writing: It's not just about what your program says but about how it says it. One of the reasons I like the C and C++ languages—which I picked up in the late 1990s and haven't put down since—is that, as compiled, non-sandboxed languages, they promise total control over the machine. Show me where you want each byte of data to go in memory; show me the machine instructions you want; and I can make C++ do that for you.
Every "computer person" should read GEB at least once. Preferably in high school, when you still have the free time to dive deep into all the recreational math exercises. If you're already working 40-hour weeks and wonder who has time for Hofstadter's 750-page "metaphorical fugue on minds and machines," all I can say is: Better late than never!
Douglas Hofstadter's book is concerned directly with the nature of maps" or links between formal systems. However, according to Hofstadter, the formal system that underlies all mental activity transcends the system that supports it. If life can grow out of the formal chemical substrate of the cell, if consciousness can emerge out of a formal system of firing neurons, then so too will computers attain human intelligence. Goedel, Escher, Bach is a wonderful exploration of fascinating ideas at the heart of cognitive science: meaning, reduction, recursion, and much more.
I have spent over a decade studying and teaching digital media, communication, and technology policy, while also working in journalism and media production. My passion for this topic comes from watching how technology quietly reshapes everyday life, from how people form relationships to how societies govern themselves. I am fascinated by the space where media, culture, and human behavior intersect, especially when change feels invisible but profound. Writing and reading about AI helps me make sense of these transformations, and I care deeply about helping people remain thoughtful, ethical, and human in an increasingly algorithmic world.
I loved this book because it completely reframed how I think about AI’s physical and environmental footprint.
While reading, I realized how often discussions about artificial intelligence ignore the material world behind the screens. Crawford’s perspective pushed me to think beyond software and consider labor, extraction, energy, and global inequality. It challenged my own assumptions as a technology scholar and reminded me that every algorithm is embedded in real-world systems.
This book expanded my understanding of AI from a technical issue into a planetary one, which I found both unsettling and essential.
The hidden costs of artificial intelligence-from natural resources and labor to privacy, equality, and freedom
"This study argues that [artificial intelligence] is neither artificial nor particularly intelligent. . . . A fascinating history of the data on which machine-learning systems are trained."-New Yorker
"A valuable corrective to much of the hype surrounding AI and a useful instruction manual for the future."-John Thornhill, Financial Times
"It's a masterpiece, and I haven't been able to stop thinking about it."-Karen Hao, senior editor, MIT Tech Review
What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our…
Everyone uses technology, but few stop to think about where these technologies come from and what this trajectory means to humanity. During my professional career, I have dedicated myself to public service focused on security and defense as a U.S. Army officer, senior government civilian, and in think tanks, industry, and academia. My journey has taken me to over 60 countries where I have witnessed humankind's best and worst. The difference is often in how our technologies are used—to build cities, feed populations, and develop life-saving vaccines or to oppress peoples or as tools of war.
This book speaks to the opportunities and challenges for the participants in today’s Artificial Intelligence (AI) competition. It highlights the barriers to entry in this tech war—high costs, advanced hardware such as semiconductors and high-performance computing, and perhaps most importantly, access to human capital.
This book provides a roadmap for thinking about the current AI tech competition. It also highlights what is at stake if the United States does not lead in this space. The idea of AI development led by an authoritarian regime or a nation that does not place humanity first could arrive at solutions that are unfriendly and perhaps even hostile to humanity.
We like to think that we are in control of the future of "artificial" intelligence. The reality, though, is that we--the everyday people whose data powers AI--aren't actually in control of anything. When, for example, we speak with Alexa, we contribute that data to a system we can't see and have no input into--one largely free from regulation or oversight. The big nine corporations--Amazon, Google, Facebook, Tencent, Baidu, Alibaba, Microsoft, IBM and Apple--are the new gods of AI and are short-changing our futures to reap immediate financial gain.
In this book, Amy Webb reveals the pervasive, invisible ways in which…
The problem is not with the actions young women take but with the toxic, sexist conditions they are responding to.
Tanenbaum found, based on six years of interviews with young people ages 14-30, that young women are navigating a culture littered with gendered dress codes, revenge porn, and sexually explicit…
I’ve spent much of my career working with leaders as technology reshapes how decisions are made, authority is exercised, and organizations evolve. What keeps me engaged with this topic is how quickly uncertainty has become the norm rather than the exception. AI and digital systems are no longer abstract forces; they shape everyday choices, incentives, and outcomes. I read these books because they help me think more clearly about leadership in that reality: how judgment, learning, and responsibility need to adapt when systems move faster than intuition. They’ve influenced how I approach real-world leadership challenges in complex, technology-driven environments.
I value this book because it helped me see how deeply technology reshapes leadership decisions long before leaders realize it.
What struck me most is how clearly it shows that AI doesn’t just optimize processes; it rewires how organizations scale, allocate authority, and compete.
I often think about this book when leaders treat AI as a tool rather than as a force that changes operating logic. It sharpened my understanding of why traditional management instincts (control, linear planning, incremental change) break down in AI-driven systems, and why leadership today requires rethinking structure, speed, and accountability at a much more fundamental level.
AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value.
Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning--to drive ever more accurate, complex, and…
