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Summer Reading List: 11 Books That Will Help You Navigate the New Age Of AI

2023 May 28
by Greg Satell

It’s hard to believe that summer is already here. Where I live, outside of Philadelphia, the nights in May have been pretty cold, so I’m still trying to get used to the idea that the time for backyard barbecues and hanging out by the pool has already arrived. Still, summer is by far my favorite season, so I gotta have faith!

It also appears that we’ve entered the dawn of a new age of artificial intelligence. New services like OpenAI’s ChatGPT and Google’s Bard, while not exactly great leaps forward in technology, have introduced generative AI to the greater public. Every day millions of people are using these services to do real work.

Like it or not, we’re all going to have to learn to navigate this new age and figure out what it means for us. Much like earlier innovations, such as smartphones and the Internet, AI will alter our lives in ways that are hard to predict and we’ll all have to figure out how to navigate the opportunities and the dangers. Here are 11 books that will help you do that.

The Master Algorithm by Pedro Domingos

We tend to think of technologies as monoliths, single objects that we use for specific purposes. An automobile is a mode of transportation that gets us from Point A to Point B, as well as a personal space in which we live a life apart. An iPhone is a communication device, as well as an access point for other technologies.

Yet the truth is that every technology is made of different components that shape its functionality. A car has an internal combustion engine, transmission, etc. An iPhone is made up of hardware and software. The components themselves can be broken down further and, as we learn about them, we improve our understanding.

In The Master Algorithm veteran AI researcher Pedro Domingos explains that there are five basic approaches to machine learning, each with their own advantages and disadvantages. Every machine learning system is, in fact, a combination of these approaches and, if you want to understand how AI functions, you first need to understand its underlying components.

Besides being a leader in the AI community, Domingos is a good communicator and this book is surprisingly readable, especially given the subject. I recommend it highly.

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The Book of Why by Judea Pearl

Statisticians often say that correlation is not causation. We can, for example, find a correlation between high readings on a thermometer and ice cream sales and conclude that if we put the thermometer next to a heater, we can raise sales of ice cream. This is because there is a confounding factor—the weather—that is causing both effects.

This might seem like a silly example, but such confounding factors have important real world effects. For example, if certain teachers have students with low scores on standardized tests, many would conclude that these are poorly qualified instructors. Yet another explanation could be that they are highly dedicated professionals willing to take on students in distress.

Judea Pearl is a pioneer in the field of artificial intelligence whose groundbreaking work on Bayesian networks was a major breakthrough. For the last quarter century he’s been working on another great project, a “causal calculus” which can untangle the knot of cause and effect. This book tells that story.

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The Structure of Scientific Revolutions by Thomas Kuhn

Clearly, the Age of AI represents an enormous paradigm shift, a term Thomas Kuhn first introduced in his 1962 classic The Structure of Scientific Revolutions. So to understand how to adapt to the shifts ahead, this book is a good place to start.

Kuhn describes a process that starts with models that become established because they are effective. Yet no model is perfect and eventually anomalies show up. Initially, these are regarded as “special cases” and are worked around. However, as the number of special cases proliferate, the model becomes increasingly untenable and a crisis ensues.

We can expect that process to be repeated across many industries and fields of endeavor in the Age of AI many tasks thought of as exclusively human become human machine collaborations. We can’t expect the process to go smoothly and some version of a crisis will likely ensue. This book will help you understand how to adapt.

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Weapons of Math Destruction by Cathy O’Neil

In Weapons of Math Destruction, data scientist Cathy O’Neil explains how data has become so pervasive in our lives, we hardly even notice it until it affects us directly. For example, she tells the story of Sarah Wysocki, a teacher who, despite being widely respected by her students, their parents and her peers, was fired because she performed poorly according to an algorithm.

We tend to think of machines as being more objective than humans and not subject to our weaknesses and flaws, but that’s hardly the case. Algorithms are designed by humans to process data collected by humans. There is human judgment and human error at every step. The fact that those judgments are encoded into a system doesn’t make them unbiased.

As technology creates ever greater possibilities and takes a larger and larger part of our lives, we need to always be cognizant of its downsides and dangers and this book explains them better than any other I’ve seen.

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The Information by James Gleick

Generative AI has potential far beyond simply writing your emails for you. It can have a real impact on the real world by helping us manage massive bits of information such as genomic and materials databases and come up with new possibilities for revolutionary drugs, building materials and product components.

But what is “information” and what does it mean to manage it? What makes some information simple and other information complex? These might seem like philosophical questions, but they are actually incredibly important and pragmatic. In fact, it’s hard to see how the computer age could have come about without a theory of information.

How we got one is an amazing story. In 1948, with a single paper, Claude Shannon created information out of whole cloth with little or no antecedentes. Written by the lenderary science author James Gleick, this book is one of my all-time favorites!

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The Singularity Is Near and How to Create A Mind by Ray Kurzweil

When Ray Kurzweil published The Singularity Is Near in 2006, many scoffed at his outlandish predictions. A year before Apple launched its iPhone, Kurzweil imagined a world in which humans and computers essentially fuse, unlocking capabilities we normally see in science fiction movies.

Yet today, his predictions don’t seem so crazy. We now find it completely ordinary to speak into our phones and get an artificially intelligent response. And, as I noted above, the three nascent technologies he predicted would come to the fore, genomics, nanotechnology and robotics, are indeed becoming central to how we create revolutionary new products.

However, I think that his later  effort, How To Create A Mind, is the better book. More focused and readable, it gives a comprehensive—but still comprehendible—explanation of how we are creating machines that learn and has some great insights on what we can expect in the future.

Get The Singularity     Get How to Create a Mind

 

A Question Concerning Technology and Other Essays by Martin Heidegger

A big part of the debate about artificial intelligence centers around whether we should be building it at all. A group of luminaries (most of which were not AI experts) even called for a 6-month halt on AI research so that we can think more deeply about the ramifications.

In his 1954 essay, A Question Concerning Technology the German philosopher Martin Heidegger sheds some light. He described technology as akin to art, in that it reveals truths about the nature of the world, brings them forth and puts them to some specific use. In the process, human nature and its capacity for good and evil is also revealed.

In another essay, Building Dwelling Thinking, he explains that building also plays an important role, because to build for the world, we first must understand what it means to live in it. The revealing power of technology forces us to rethink old truths and reimagine new societal norms. That, more than anything else, is where the challenges lie.

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9 Algorithms That Changed The Future by Jack MacCormick

In an earlier age, people used to interact with technology on a more visceral level. They would fix their own cars, build their own houses and tinker with the tools of their trade. Today, on the other hand, the vast majority of the artifacts of our daily lives are a mystery to us, incomprehensible to all but a small priesthood of specialists.

This book can do much to remedy that. Written by John MacCormick, a leading researcher and professor of computer science, it explains key algorithms in a surprisingly engaging way. It won’t make you a computer genius, but it will help you better understand the technology that surrounds us.

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A Crack in Creation by Jennifer Doudna and Samuel Sternberg

Marshall McLuhan wrote that we “march backwards into the future.” He meant that we see new technologies through the lens of our past experiences. So when we think about AI, we naturally think about its impact on digital technology, helping us write documents, edit videos, retrieving information and explaining it to us.

However the major impacts are more likely to be in the realm of atoms than the realm of bits. Artificial intelligence can help us understand how proteins fold and how materials are constructed on a subatomic level. That, in turn, can help us discover life saving drugs, revolutionary product components and safe, sustainable building materials.

To understand the possibilities, I highly recommend A Crack In Creation in which Jennifer Doudna, the discoverer of the revolutionary gene editing technology CRISPR, tells her personal story. It will give you a sense of the incredible possibilities—and very real dangers—that lie ahead.

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Labyrinths by Jorge Luis Borges

Often the best way to understand reality is through fiction and Jorge Borges is one of the most thought provoking writers ever. His stories rarely run for more than six pages and can be read in an hour, so are ideal to fit in between other activities at the beach or the pool.

With respect to AI, his story The Library of Babel is especially helpful. He asks us to imagine a library that contains every possible combination of characters in every possible language. In such a library, all of the information in the universe would accessible, but deriving meaning would require curation.

Those of us in Generation X and older grew up in a scarce information environment. Much of our work in school and at the office involved finding information in places like libraries and file cabinets. With AI, we have information all around us, but to make use of it we need to curate it intelligently to find meaning. Borges can help us think through that.

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***

So that’s my list for this summer. If you would like to add a suggestion of your own, please feel free to do that in the comments section.

Greg Satell is Co-Founder of ChangeOS, a transformation & change advisory, an international keynote speaker, and bestselling author of Cascades: How to Create a Movement that Drives Transformational Change. His previous effort, Mapping Innovation, was selected as one of the best business books of 2017. You can learn more about Greg on his website, GregSatell.com and follow him on Twitter @DigitalTonto

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Photo by Jorge Acre

2 Responses leave one →
  1. David Hoo permalink
    June 4, 2023

    Everyone should check out Columbia University Professor Sheena Iyengar’s newly published book – Think Bigger.

    She has recently invented the first major breakthrough creative idea generation methodology since brainstorming in the 1950s. Think Bigger, though, is vastly superior to brainstorming where Think Bigger can reliably ideate true breakthroughs by the typical average person, not just the creatively talented, or professionally trained (IDEO types) individuals!

    However, Think Bigger best requires considerable, persistent efforts by individuals. Notably though, diverse teams of individual agents perform even better.

  2. June 4, 2023

    Thanks! I’ll check it out.

    Greg

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