Book excerpt: Overview from the book proposal

(This is an excerpt from the book proposal for my unpublished book, "Algorithms and Misinformation: Why Wisdom of the Crowds Failed the Internet and How to Fix It")

Without most of us even realizing it, algorithms determine what we see everyday on the internet.

Computer programs pick which videos you’ll watch next on TikTok and YouTube. When you go to Facebook and Twitter, algorithms pick which news stories you’ll read. When it’s movie night, algorithms dictate what you’ll watch on Netflix based on what you watched in the past. Everywhere you look, algorithms decide what you see.

When done well, these computer programs have enormous value, helping people find what they need quickly and easily. It’s hard to find what you are looking for with so much out there. Algorithms filter through everything, tossing bad options away with wild abandon, to bring rare gems right to you.

Imagine you’re looking for a book. When you go to Amazon and start searching, algorithms are what filter through all the world’s books for you. But not only that. Algorithms also look at what books people seem most interested in and then bring you the very best choices based on what other customers bought. By quickly filtering through millions of options, computers help people discover things they never would have been able to find on their own.

These algorithms make recommendations in much the same way that you would. Suppose you have a friend who asks you to recommend a good book for her to read. You might ask yourself, what do you know about her? Does she like fiction or nonfiction? Which authors does she like? What books did she read in the past few months? With a little information about your friend’s tastes, you might narrow things down. Perhaps she would like this well-reviewed mystery book? It has some similar themes to a book she enjoyed last year.

Algorithms combine opinions, likes, and dislikes from millions of people. The seminal book The Wisdom of Crowds popularized the idea that combining the opinions of many random people often gives useful results. What algorithms do is bring together the wisdom of crowds at massive scale. One way they do this is by distilling thousands of customer reviews so you can easily gauge the average review of a movie or video game before you sink time and money into it. Another way is by showing you that customers who bought this also bought that. When algorithms pick what you see on the internet, they use wisdom of the crowds.

Something changed a few years ago. Wisdom of the crowds failed. Algorithms that use wisdom of the crowds started causing harm. Across the internet, algorithms that choose what people see started showing more spam, misinformation, and propaganda.

What happened? In the same way a swindler on a street corner will stack the crowd with collaborators who loudly shill the supposed wonders of their offerings, wisdom of the crowd algorithms got fooled into promoting misinformation, scams, and frauds. With the simple ease of creating many online accounts, a fraudster can pretend to be an entire crowd of people online. A fake crowd gives scammers a megaphone that they can use to amplify their own voice as they drown out the voices of others.

Search and recommendation algorithms across the internet were fooled by these fake crowds. Before the 2020 election in the United States, foreign adversaries posted propaganda to social media, then pretended to be large numbers of Americans liking and resharing, fooling the algorithms into amplifying their posts. 140 million people in the United States saw this propaganda, many of whom were voters. In 2019, the largest pages on social media for Christian Americans, such as “Be Happy Enjoy Life” and “Jesus is my Lord”, were controlled by foreign operatives pretending to be Americans. These troll farms shilled recommendation, search, and trending algorithms, getting top placement for their posts and high visibility for their groups, reaching 75 million people. Scammers manipulated wisdom of the crowd algorithms with shills to promote their bogus cures during the COVID-19 global pandemic. In 2021, the US Surgeon General was so alarmed by health misinformation on the internet that he warned of increased illness and death if it continued.

Misinformation and disinformation are now the biggest problems on the internet. It is cheap and easy for scammers and propagandists to get seen by millions. Just create a few hundred accounts, have them like and share your stuff to create the illusion of popularity, and wisdom of the crowd algorithms will amplify whatever you like. Even once many companies realized the algorithms had gone wrong, many failed to fix it.

This book is about fixing misinformation on the internet by fixing the algorithms that promote misinformation. Misinformation, scams, and propaganda are ubiquitous on the internet. Algorithms including trending, recommendations, and search rankers amplify misinformation, giving it much further reach and making it far more effective.

But the reason why algorithms amplify misinformation is not what you think. As this book shows, the process of how big tech companies optimize algorithms is what causes those algorithms to promote misinformation. Diving deep inside the tech companies to understand how they build their algorithms is the key to finding practical solutions.

This book could only be written by an insider with an eye toward how the biggest tech companies operate. That’s because it’s necessary to not only understand the artificial intelligence technology behind the algorithms that pick what people see on the internet, but also understand the business incentives inside these companies when teams build and optimize these algorithms.

When I invented Amazon’s recommendation algorithm, our team was idealistic about what would happen next. We saw algorithms as a tool to help people. Find a great book. Enjoy some new music. Discover new things. No matter what you are looking for, someone out there probably already found it. Wisdom of the crowd algorithms share what people found with other people who might enjoy it. We hoped for an internet that would be a joyful playground of knowledge and discovery.

In the years since, and in my journeys through other tech companies, I have seen how algorithms can go terribly wrong. It can happen easily. It can happen unintentionally. Like taking the wrong path in a dark forest, small steps lead to bigger problems. When algorithms go wrong, we need experts like me who can see realistic ways to correct the root causes behind the problems.

Solutions to what is now the world’s algorithm problem require interdisciplinary expertise in business, technology, management, and policy. I am an artificial intelligence expert, invented Amazon’s recommendation algorithm, and have thirty-two patents on search and recommendation algorithms. I also have a Stanford MBA, worked with executives at Amazon, Microsoft, and Netflix, and am an expert on how tech companies manage, measure, and reward teams working on wisdom of the crowd algorithms. Past books have failed to offer solutions because authors have lacked the insider knowledge, and often the technical and business expertise, to solve the problems causing misinformation and disinformation. Only with a deep understanding of the technology and business will it be possible to find solutions that not only will work, but also will be embraced by business, government, and technology leaders.

This book walks readers through how these algorithms are built, what they are trying to do, and how they go wrong. I reveal what it is like day-to-day to work on these algorithms inside the biggest tech companies. For example, I describe how the algorithms are gradually optimized over time. That leads to the surprising conclusion that critical to what the algorithms show people is not the algorithms themselves but the metrics companies pick for judging if the algorithms are doing their job well. I show how easy it is for attempts to improve algorithms to instead go terribly wrong. Seemingly unrelated decisions such as how people are promoted can not only cause algorithms to amplify misinformation, but also hurt customers and the long-term profitability of the company.

Readers need to know both why the algorithms caused harm and why some companies failed to fix the problems. By looking at what major tech companies have done and failed to do, readers see the root causes of the massive spread of misinformation and disinformation on the internet. Some companies have invested in fixing their algorithms and prospered. Some companies failed to fix their algorithms and suffered higher costs as misinformation and scams grew. By comparing companies that have had more success with those that have not, readers discover how some companies keep fraudsters from manipulating their algorithms and why others fail.

Other books have described misinformation and disinformation on the internet, but no other book offers practical solutions. This book explains why algorithms promote misinformation with key insights into what makes misinformation cost effective for fraudsters. This book describes what tempts giant tech companies to allow misinformation on their platforms and how that eventually hurts the companies and their customers. Importantly, this book provides strong evidence that companies would benefit from fixing their algorithms, establishing that companies make more money when they fix their algorithms to stop scams, propaganda, and misinformation. From this book, consumers, managers, and policy makers not only will know why algorithms go wrong, but also will be equipped with solutions and ready to push for change.

This is the story of what went wrong and how it can be fixed as told by people who were there. I bring together rare expertise to shine a light on how to solve the greatest problem on the internet today. This book is a guide inside how the world’s biggest technology companies build their algorithms, why those algorithms can go wrong, and how to fix it.