Navigating the New Era of Learning: Top Generative AI Books for Programmers

Developer Nation
2 min readNov 7, 2023

by Manning Publications

With massive changes happening due to generative AI tools like ChatGPT and GitHub Copilot, you won’t be surprised that there’s a swarm of new books that use generative AI to teach programming to beginners or to enhance what programmers can do.

In this article, we wanted to cover our top four generative AI books that are being published by Manning Publications.

We know, we know: you just want to use generative AI to supercharge your programming productivity. We want that, too! But we’re at the dawn of a programming revolution here, and we strongly encourage you to take the time to understand the ethical and legal concerns wrought by generative AI.

What happens when generative AI models ingest objectionable speech or personal data? Why are these models apt to produce hallucinations, and why should we care? Why is it so difficult to address bias in machine learning? What is the critical role that human feedback plays in LLM training, and what are the associated costs to humans? Does generative AI’s use of copyrighted work fall under fair use?

As informed end-users of generative AI, it’s up to us to answer these questions–to understand what data we might be using, how that data was produced, and the societal and ethical impacts of these tools. This book helps us toward those answers.

We appreciate that many claims in the book are supported with references that the reader can check for additional details. We also benefited from numerous powerful examples throughout the book, such as racial bias in movie sentiment scores, a ChatGPT data breach, and a famous virtual influencer.

We’d also like to emphasize that while the focus of the book is on the responsible use of generative AI, there is also a non-mathematical overview coverage of how generative AI tools work, which we suspect will be of interest to many readers. For example, you’ll learn more about many concepts you’ve probably heard about in passing, such as foundation models, fine-tuning, emergent properties of LLMs, zero-shot and few-shot learning, and chain-of-thought prompting.

Finally, we applaud the balanced discussion of the pros and cons of synthetic media, the ways that LLMs are and will be misused, the ways that professionals are using LLMs and–of course!–the coverage of the impacts on education.

Read the complete guide and get a 35% universal discount from Manning Publications.



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