ChatGPT vs Bard vs Hugging Chat - Book Review of "Prediction Machines"

Allie K. Miller and Cassie Kozyrkov had an awesome Instagram live today - you can find my TL;DR and the full video recording here. During the event Allie gave 3 book suggestions. The first of which was "Prediction Machines" by Ajay Agrawal , Joshua Gans , and Avi Goldfarb .

Since the book has been out for 3 years, there have been lots of human reviews, such as Jack Le at https://blog.primus.vn/prediction-machine-book-review/

Given that I've been using ChatGPT and Bard quite a bit the last few months, I thought it would be a good test to ask them to offer up their reviews of the book, so we can have a little compare of their review styles - like my son's 6th grade teacher likes to say "it's not a competition" <yeah right>

Let's get ready to rumble!

Rules: Exactly same asks, no additional prompts, and clean session for both. Formatting in bold empahsis mine.

Request posed to both: Please create a blog post book review of "Prediction Machines" by Ajay Agrawal, Joshua Gans

ChatGPT's Review

Title: Unveiling the Future: A Review of "Prediction Machines" by Ajay Agrawal, Joshua Gans, and Avi Goldfarb

Introduction:

In today's data-driven world, the power of prediction and its impact on industries cannot be understated. "Prediction Machines: The Simple Economics of Artificial Intelligence" by Ajay Agrawal, Joshua Gans, and Avi Goldfarb delves into the transformative potential of artificial intelligence (AI) and its role in shaping our future. In this book, the authors explore the economic implications of AI and provide a refreshing perspective on how businesses can harness the predictive power of machines to thrive in an increasingly competitive landscape.

Summary:

Agrawal, Gans, and Goldfarb skillfully dismantle the notion that AI is a complex, incomprehensible force, and instead present it as a set of powerful prediction tools. The authors argue that at its core, AI is not about replicating human intelligence but rather about predicting outcomes more accurately and efficiently than humans. By framing AI as a prediction problem, they make the topic accessible to a wide range of readers.

The book explores three fundamental aspects of prediction machines: data, algorithms, and judgment. The authors emphasize that data is the fuel that powers AI, highlighting the importance of gathering, cleaning, and curating quality data. They also examine the role of algorithms, explaining how the ability to process vast amounts of data and generate accurate predictions is the true essence of AI. Lastly, they discuss the significance of human judgment in leveraging AI's predictions effectively and avoiding potential pitfalls.

Key Insights:

1. The Value of Data: The authors emphasize that data, more than algorithms, is the key driver of AI's predictive power. They stress the need for organizations to collect high-quality data and invest in data infrastructure to derive maximum value from AI technologies.
2. Complementing Human Intelligence: Contrary to popular belief, the authors contend that AI's primary function is not to replace human intelligence but to augment it. They present compelling arguments and examples to support the idea that combining human judgment with AI predictions can lead to better decision-making.
3. The Impact on Industries: "Prediction Machines" provides a comprehensive analysis of how AI will impact various industries. From healthcare to finance, transportation to education, the authors shed light on the potential disruptions and opportunities that lie ahead, offering readers a glimpse into a future shaped by AI.
4. Ethical Considerations: The authors delve into the ethical dimensions of AI and highlight the importance of addressing issues such as bias, fairness, and transparency. They stress the need for responsible AI deployment and emphasize the role of policymakers and organizations in shaping an ethical AI ecosystem.

Conclusion:

In "Prediction Machines," Ajay Agrawal, Joshua Gans, and Avi Goldfarb deliver a thought-provoking exploration of AI's transformative power and its implications for the future of business and society. Through their lucid explanations and real-world examples, the authors demystify the complex world of AI and present it as a set of powerful prediction tools that can unlock tremendous value. This book is a must-read for anyone interested in understanding the economic forces driving the AI revolution and how businesses can harness its potential for success.

Not bad. But can Bard do better?

Prediction Machines: The Simple Economics of Artificial Intelligence

In their book "Prediction Machines", Ajay Agrawal and Joshua Gans offer a clear and concise overview of the economics of artificial intelligence (AI). The book begins by explaining the basic principles of AI, such as machine learning and statistical prediction. It then goes on to discuss the ways in which AI is being used to improve our lives, in areas such as healthcare, finance, and transportation.

One of the key arguments that Agrawal and Gans make is that AI is not just a technology, but also an economic force. They argue that AI is lowering the cost of prediction, which is having a profound impact on the way that businesses operate. For example, AI is being used to personalize marketing campaigns, predict customer churn, and identify fraud.

The book also discusses the potential risks of AI, such as job displacement and bias. However, Agrawal and Gans argue that the benefits of AI outweigh the risks. They believe that AI has the potential to make our lives better in many ways, and that we should embrace this technology responsibly.

Overall, "Prediction Machines" is an excellent book that provides a clear and concise overview of the economics of AI. It is a must-read for anyone who wants to understand how AI is changing the world.

Here are some of the pros and cons of the book:

Pros:

• Clear and concise explanation of the basic principles of AI
• Discussion of the ways in which AI is being used to improve our lives
• Argument that AI is an economic force that is having a profound impact on the way that businesses operate
• Discussion of the potential risks of AI, such as job displacement and bias

Cons:

• Some of the technical concepts may be difficult to understand for readers with no background in AI
• The book does not go into great detail about the potential risks of AI

Overall, I highly recommend "Prediction Machines" to anyone who wants to understand the economics of AI. It is a well-written and informative book that provides a good overview of this rapidly growing field.

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Who won this Book Review Battle?

IMHO, ChatGPT by a K.O! If you were expecting a more detailed assessment of the contents, structure and key points of the book.

If you were looking for a review that directly answers a question of "Should I bother reading this book", then Bard helps you out with basically a Pro and Con of why you should or should not bother.

ChatGPT gets extra marks for noting the 3rd author Avi Goldfarb whom I deliberately left out to see what each would do.

Now of course this all comes down to style and preference of the reviewer of the Book reviews, since one is more detailed and verbose, and the other short and concise. So in the end it call comes down to preference.

Since I put this test together in 15 minutes, I will admit I have not personally yet read the book - which you can get from Amazon here

But I now have 1 human review from Jack Le, 1 from ChatGPT and another from Bard to chose from. I'll also be reading the book and writing my own review soon and to fact check for hallucinations.

What do you think? You can make this blog post even more Meta if you review my review of the book reviews by commenting below

Update 6/15/23: Here's the Hugging Chat version (that uses OpenAI as well) giving a completely different style and form to the exact same original ask.

Book Review: Prediction Machines by Ajay Agrawal, Joshua Gans, and Avi Goldfarb

In their new book "Prediction Machines," Ajay Agrawal, Joshua Gans, and Avi Goldfarb explore the powerful impact that artificial intelligence (AI) is having on our economy and society as we move towards becoming more predictive. They argue that machine learning is rapidly transforming industries such as finance, healthcare, marketing, education, and transportation, among others, by enabling computers to make decisions based on data rather than human intuition alone. Through fascinating case studies, the authors illustrate how companies can leverage prediction machines to gain a competitive edge and increase efficiency across many different fields.

One of the key messages of the book is that while there are significant benefits to using prediction machines for decision making, they also come with risks. For example, biases in data sets can lead to unintended consequences and perpetuate inequality. Therefore, it becomes increasingly important for organizations to carefully consider the implications of implementing these technologies into their operations. Additionally, the authors stress that humans must remain involved in the decision making process, even if it means accepting lower levels of accuracy. This balance ensures ethical considerations are taken into account and provides opportunities for innovative problem solving through the collaboration of humans and technology.

Overall, I found this book very insightful and well-written. Each chapter was filled with examples from real life situations which made it easier for me to relate to the content. With so many potential applications, predictions machines are clearly here to stay, but it's up to us to use them responsibly. I would recommend "Prediction Machines" to anyone interested in understanding the future role of AI in our economy and society.