Every year, we put together a list of books that we’re excited to read via recommendations from our community and research on what will be necessary for IT leaders to know in the coming year. This post will highlight 10 tech books that we think should be on your radar for 2023. (Stay tuned for our picks for the top leadership books and books for job hunters coming soon.)
Whether you are more interested in the here and now – like how technologies designed to boost convenience are also prone to perpetuating bias – or emerging technology predictions for cloud tactics that unlock the benefits of digitalization, there's a book on this list for you.
Let's dive in.
By Emanuelle Burton, Judy Goldsmith, Nicholas Mattei, Cory Siler, and Sara-Jo Swiatek
Book Description (via Amazon): “A new approach to teaching computing and technology ethics using science fiction stories. Should autonomous weapons be legal? Will we be cared for by robots in our old age? Does the efficiency of online banking outweigh the risk of theft? From communication to travel to medical care, computing technologies have transformed our daily lives, for better and for worse. But how do we know when a new development comes at too high a cost? Using science fiction stories as case studies of ethical ambiguity, this engaging textbook offers a comprehensive introduction to ethical theory and its application to contemporary developments in technology and computer science.”
Why you should read it: This book is for IT leaders who are curious about the major ethical frameworks (deontology, utilitarianism, virtue ethics, communitarianism, and the modern responses of responsibility ethics, feminist ethics, and capability ethics) and how they apply to many of the modern issues arising in technology ethics including privacy, computing, and artificial intelligence.
By Meredith Broussard
Book description (via Amazon): “Broussard, a data scientist who has worked in journalism and software development, masterfully synthesizes concepts from computer science and sociology alongside her own experience as one of the few Black female researchers in artificial intelligence. When technology reinforces inequality, it’s not just a glitch—it’s a signal that we need to redesign our systems to create a more equitable world. The word “glitch” implies an incidental error, as easy to patch up as it is to identify. But what if racism, sexism, and ableism aren’t just bugs in mostly functional machinery—they’re coded into the system itself? In More Than a Glitch, Meredith Broussard demonstrates how technological neutrality is a myth and why algorithms need to be held accountable.”
Why you should read it: You’re a tech leader who understands that there is always bias in modern technologies – you recognize the fallibility of humans – but you want to learn about potential solutions to this problem. Explore the frameworks that target specific demographics as “other” in the first place. This is essential reading for anyone invested in building a more equitable future.
[ Are you asking the right questions when it comes to systemic bias? Read also AI bias: 9 questions leaders should ask. ]
By Thomas H. Davenport and Steven M. Miller
Book description (via Amazon): “Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings. This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, [the authors] show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers.”
Why you should read it: Curious about the implications of human collaboration with smart systems? This book shares specific use cases of humans working with AI successfully, e.g., a digital system for life insurance underwriting that analyzes applications and third-party data in real-time, allowing human underwriters to focus on more complex cases. Read this book if you want reassurance on the positive potential outcomes of AI versus the ominous view that artificial intelligence is a job stealer.
by Yada Pruksachatkun, Matthew Mcateer, and Subho Majumdar
Book description (via Amazon): “With the increasing use of AI in high-stakes domains such as medicine, law, and defense, organizations spend a lot of time and money to make ML models trustworthy. Many books on the subject offer deep dives into theories and concepts. This guide provides a practical starting point to help development teams produce models that are secure, more robust, less biased, and more explainable.”
Why you should read it: You’d like to see the positives of machine learning, especially in precarious fields like medicine. Are you interested in understanding how to curate datasets and build models into a foundation for releasing trustworthy ML applications? Building trusted machine learning systems is nuanced and complicated in our hostile world. This book is a practical guide that goes beyond theories and what-ifs.
By Daniel Situnayake and Jenny Plunkett
Book description (via Amazon): “Edge artificial intelligence is transforming the way computers interact with the real world, allowing internet of things (IoT) devices to make decisions using the 99% of sensor data that was previously discarded due to cost, bandwidth, or power limitations. This practical guide gives engineering professionals and product managers an end-to-end framework for solving real-world industrial, commercial, and scientific problems with edge AI. You’ll explore every stage of the process, from data collection to model optimization to tuning and testing, as you learn how to design and support edge AI and embedded ML products. Edge AI is destined to become a standard tool for systems engineers.”
Why you should read it: Looking to develop your AI expertise and machine learning on edge devices? Want to understand which projects are best solved with edge AI? This book gives engineering professionals and product managers a framework for solving real-world problems using edge AI. Edge AI will soon become the standard 'systems engineer' tool. Read "AI at the Edge" to learn how to design and support edge AI and ML products.
[ Related read: Edge and cloud: 4 reasons to adopt both ]
by Jamil Mina, Armin Warda, Rafael Marins, and Russ Miles
Book description (via Amazon): “If you’re planning, building, or implementing a cloud strategy that supports digitalization for your financial services business, this invaluable guide clearly sets out the crucial factors and questions to consider first. With it, you’ll learn how to avoid the costly and time-consuming pitfalls and disappointments of cloud adoption and take full advantage of the cloud operational model.”
Why you should read it: Are you a cloud leader curious about real-world case studies for ensuring operability across cloud services providers? Dealing with digitalization issues in finance? Have cloud adoption disillusionment? This is the read for you. Packed with invaluable advice, this book will help you select the right operational models for your needs and show you how to build resilience into your organization’s tech while balancing innovation and accountability.
by Tomas Chamorro-Premuzic
Book description via Amazon: " In I, Human, psychologist Tomas Chamorro-Premuzic offers a guide for reclaiming ourselves in a world in which most of our decisions will be made for us. To do so, we’ll need to double down on what makes us so special—our curiosity, adaptability, and emotional intelligence—while relying on the lost virtues of empathy, humility, and self-control. It’s no secret that AI is changing the way we live, work, love, and entertain ourselves. Dating apps are using AI to pick our potential partners. Retailers are using AI to predict our behavior and desires. Rogue actors are using AI to persuade us with Twitter bots and fake news. Companies are using AI to hire us—or not."
Why you should read it: You're a tech leader who wants to understand how AI’s evolution affects humanity. Will these changes enhance our species or dehumanize us and make us more machinelike in our interactions with others? "I, Human" is the book you need to read to understand how to thrive in an automated future.
[ Also read: Automation: 5 ways it can change lives ]
By Ramon Amaro
Book description (via Amazon): “On the abstruse nature of machine learning, mathematics, and the deep incursion of racial hierarchy. To impair the racial ordering of the world, The Black Technical Object introduces the history of statistical analysis and “scientific” racism into research on machine learning. Computer programming designed for taxonomic patterning, machine learning offers useful insights into racism and racist behavior, but its connection to the racial history of science and the Black lived experience has yet to be developed.”
Why you should read it: You want to become a more modern, educated leader by exploring how the history of data and statistical analysis informs the complex relationship between race and machine learning. Interested in considering alternative approaches to contemporary algorithmic practice and understanding racial hierarchies? This is the book all tech leaders should be reading!
by Ajay Agrawal, Joshua Gans, and Avi Goldfarb
Book description (via Amazon): “In Power and Prediction, [the authors examine] the most basic unit of analysis: the decision. Two key decision-making ingredients are prediction and judgment, and we perform both together in our minds, often without realizing it. The rise of AI is shifting prediction from humans to machines, relieving people from this cognitive load while increasing the speed and accuracy of decisions. This sets the stage for a flourishing of new decisions and has profound implications for system-level innovation. Redesigning systems of interdependent decisions takes time—many industries are in the quiet before the storm—but when these new systems emerge, they can be disruptive on a global scale. Decision-making confers power. In industry, power confers profits; in society, power confers control. This process will have winners and losers, and the authors show how businesses can leverage opportunities, as well as protect their positions.”
Why you should read it: You’re an IT leader curious about how AI has impacted large industries worldwide – banking and finance, pharmaceuticals, automotive, medical technology, manufacturing, and retail. How can your organization leverage the opportunities created by AI for cheaper, better, and faster predictions that drive strategic business decisions? This book provides insights, rich examples, and practical advice. It is a must-read guide for any business leader to make the coming AI disruptions work for you rather than against you.
by Stephanie L. Woerner, Peter Weill, and Ina M. Sebastian
Book description (via Amazon): “It seems like almost every company you can think of—including your own—has embarked on a “digital transformation” journey. The problem is, many companies start down the road without a good sense of where they are going or a clear idea of how they will create and capture digital value. Not surprisingly, this leads to problems: failure to realize the value from digital in their bottom lines, wasted resources and effort, added complexity and dysfunction. In their years of working with senior executives around the world, MIT research scientists Stephanie Woerner, Peter Weill, and Ina Sebastian noticed that these leaders knew they had to transform their businesses, but lacked a coherent framework and a common language—a playbook—to guide and motivate their employees and keep everyone focused on a common goal.”
Why you should read it: You’re a CIO in need of a competitive business transformation playbook for leading your organization. Want to become future-ready and be a top performer in the digital economy? This book provides examples, sharp analyses, benchmark assessments, and eye-opening visuals to help understand data and embrace organizational disruptions that are a part of every transformation journey.
What to read next
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