Media Literacy

This book serves as a convenient entry point for researchers, practitioners, and students to understand the problems and challenges, learn state-of-the-art solutions for their specific needs, and quickly identify new research problems in their domains. The contributors to this volume describe the recent advancements in three related parts: (1) user engagements in the dissemination of information disorder; (2) techniques on detecting and mitigating disinformation; and (3) trending issues such as ethics, blockchain, clickbaits, etc. This edited volume will appeal to students, researchers, and professionals working on disinformation, misinformation and fake news in social media from a unique lens.

Are you overwhelmed at the amount, contradictions, and craziness of all the information coming at you in this age of social media and twenty-four-hour news cycles? Fake News, Propaganda, and Plain Old Lies will show you how to identify deceptive information as well as how to seek out the most trustworthy information in order to inform decision making in your personal, academic, professional, and civic lives. - Learn how to identify the alarm bells that signal untrustworthy information. - Understand how to tell when statistics can be trusted and when they are being used to deceive. - Inoculate yourself against the logical fallacies that can mislead even the brightest among us. Donald A. Barclay, a career librarian who has spent decades teaching university students to become information literate scholars and citizens, takes an objective, non-partisan approach to the complex and nuanced topic of sorting deceptive information from trustworthy information.

"It's a joy to read a book by a mathematician who knows how to write. [...] There is no better guide to the strategies and stakes of this battle for the future." ---Paul Romer, Nobel Laureate, University Professor in Economics at NYU, and former Chief Economist at the World Bank.   "By explaining the flaws and foibles of everything from Google search to QAnon--and by providing level-headed evaluations of efforts to fix them--Noah Giansiracusa offers the perfect starting point for anyone entering the maze of modern digital media." --Jonathan Rauch, senior fellow at the Brookings Institute and contributing editor of The Atlantic From deepfakes to GPT-3, deep learning is now powering a new assault on our ability to tell what's real and what's not, bringing a whole new algorithmic side to fake news. On the other hand, remarkable methods are being developed to help automate fact-checking and the detection of fake news and doctored media. Success in the modern business world requires you to understand these algorithmic currents, and to recognize the strengths, limits, and impacts of deep learning---especially when it comes to discerning the truth and differentiating fact from fiction.  This book tells the stories of this algorithmic battle for the truth and how it impacts individuals and society at large. In doing so, it weaves together the human stories and what's at stake here, a simplified technical background on how these algorithms work, and an accessible survey of the research literature exploring these various topics. How Algorithms Create and Prevent Fake News is an accessible, broad account of the various ways that data-driven algorithms have been distorting reality and rendering the truth harder to grasp. From news aggregators to Google searches to YouTube recommendations to Facebook news feeds, the way we obtain information today is filtered through the lens of tech giant algorithms. The way data is collected, labelled, and stored has a big impact on the machine learning algorithms that are trained on it, and this is a main source of algorithmic bias ­- which gets amplified in harmful data feedback loops. Don't be afraid: with this book you'll see the remedies and technical solutions that are being applied to oppose these harmful trends. There is hope. What You Will Learn The ways that data labeling and storage impact machine learning and how feedback loops can occur The history and inner-workings of YouTube's recommendation algorithm The state-of-the-art capabilities of AI-powered text generation (GPT-3) and video synthesis/doctoring (deepfakes) and how these technologies have been used so far The algorithmic tools available to help with automated fact-checking and truth-detection.

How we arrived in a post-truth era, when "alternative facts" replace actual facts, and feelings have more weight than evidence. Are we living in a post-truth world, where "alternative facts" replace actual facts and feelings have more weight than evidence? How did we get here? In this volume in the MIT Press Essential Knowledge series, Lee McIntyre traces the development of the post-truth phenomenon from science denial through the rise of "fake news," from our psychological blind spots to the public's retreat into "information silos." What, exactly, is post-truth? Is it wishful thinking, political spin, mass delusion, bold-faced lying? McIntyre analyzes recent examples--claims about inauguration crowd size, crime statistics, and the popular vote--and finds that post-truth is an assertion of ideological supremacy by which its practitioners try to compel someone to believe something regardless of the evidence. Yet post-truth didn't begin with the 2016 election; the denial of scientific facts about smoking, evolution, vaccines, and climate change offers a road map for more widespread fact denial. Add to this the wired-in cognitive biases that make us feel that our conclusions are based on good reasoning even when they are not, the decline of traditional media and the rise of social media, and the emergence of fake news as a political tool, and we have the ideal conditions for post-truth. McIntyre also argues provocatively that the right wing borrowed from postmodernism--specifically, the idea that there is no such thing as objective truth--in its attacks on science and facts. McIntyre argues that we can fight post-truth, and that the first step in fighting post-truth is to understand it.