Noah Giansiracusa - How Algorithms Create and Prevent Fake News: Exploring the impacts of Social Media, Deepfakes, GPT-3, and More

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You might have heard rumors that the newsfeed algorithm at Facebook and the video recommendation algorithm at YouTube are spreading fake news, or that artificial intelligence (AI) can now rapidly generate convincing articles and make videos of people doing and saying things they never did, or that machine learning algorithms will save us from fake news by automatically detecting it and labeling assertions as true or false. But what do these claims even mean, and what should you believe? The main goal of this book is to help readers of all backgroundsno knowledge of math, statistics, computers, algorithms, or journalism requiredunderstand whats really going on by collecting all the investigations, research, and stories about fake news and algorithms in one place and explaining it in a simple way while weaving it together into a coherent narrative. Another goal is to teach you about the publicly available tools that can help you do your own part in the fight against fake news.

If we are not serious about facts and whats true and whats not, if we cant discriminate between serious arguments and propaganda, then we have problems. Barack Obama said this on November 17, 2016, just nine days after Donald Trump was elected to be his successor in the White House. Since then, there has been an increasing awareness of the scope and impact of fake news, a catchall label for misinformation (false information that is spread regardless of intent to mislead) and disinformation (deliberately false or misleading information). There has also been an increasing awareness of the role played by data-driven algorithms in the creation, dissemination, and detection/moderation of fake news. But the story of fake news and algorithms has been difficult for most of us to follow. It has unfolded in a wide range of academic publications, journalistic investigations, corporate announcements, and governmental hearings, and it involves many sophisticated technological concepts that sound mysterious. I strongly believe that the barriers to entering this important discussion are not nearly as high as they might seem, and this book is my attempt to lower them even further.

Chapter is all about YouTube and its recommendation algorithm that automatically selects videos for you to watch. A history of this algorithm is provided, including brief discursions into deep learning and reinforcement learning, and empirical investigations into the way it works in practice are explored. This frames a discussion of fake news and conspiratorial content on YouTube, especially in the context of Brazils 2018 election and the 2016 and 2020 US elections.

After several chapters on how AI can create and spread fake news, Chapter collects and explains some publicly available AI-powered fact-checking tools that you can use to make sure what youre reading is trustworthy and truthful.

Thanks to Jordan Ellenberg, Cathy ONeil, and Francis Su for inspiring me to write a book and helping me learn about the publishing industry. Thanks to Karen Hao, Will Douglas Heaven, Davey Alba, Jack Nicas, Kevin Roose, James Vincent, Issie Lapowsky, Carole Cadwalladr, Julia Angwin, Deepa Seetharaman, Jeff Horwitz, Sheera Frenkel, and so many other technology journalists for doing the hard work that this book relies so heavily upon. Thanks to Gerald Seidler, Jim Morrow, Henry Cohn, Dan Abramovich, Angela Gibney, Bernd Sturmfels, and my other teachers and mentors who helped me become a math professor. Thanks to Charlie Hadlock, Rick Oches, Lucy Kimball, and others at Bentley University for believing in me as a data scientist and providing me with the opportunities that led to this book. Thanks to Steffen Marcus for encouraging me to think and write about the broader context of math and technology. Thanks to Tom Taulli for putting me in contact with Apress, and to my team at ApressShiva Ramachandran, Matthew Moodie, Nancy Chen, Rita Fernando, and Mark Powersfor all their work shaping this book and helping get it across the finish line. Thanks to my parents, Bob and Dorothy, for homeschooling me and passing along a passion for lifelong learning. Thanks to my brother, Jeffrey, for paving the way forward for us both. And thanks to my wife, Emily, and our daughter, Claire, for more than words can convey.