Название: AI, Algorithms, and Misinformation: Law, Politics, and Our Digital Futures
Автор: Jeffrey Layne Blevins
Издательство: Routledge
Год: 2027
Страниц: 182
Язык: английский
Формат: True PDF, True EPUB
Размер: 10.1 MB

This book examines how - in the 21st century world of big data and social media - artificial intelligence and algorithms are being used to predict our economic, political, and cultural activity.

Drawing inspiration from the concept of a "minority report," as introduced in Philip K. Dick’s 1956 short story, the book explores how the byproduct of digital content on social media often generates a collective perception of reality. This book breaks down how this collective perception is ultimately manufactured by cultural, political, and economic interests, and how additional issues - such as data errors, misinformation, and bias - can often render it false. Applying critical political economic analysis and cultural legal studies to these problems, Blevins emphasizes how we can do more to challenge the perceptions that pervade popular online discourse. Throughout the book, he demystifies the systems and processes that generate these information flows, enabling readers to better fight for remedies to the problem - legal and otherwise - and create a more just digital future.

In the first chapter, I will lay out the main thesis of the book that although Machine Learning and other algorithmic devices that comprise our data-based and social media environments may often be accurate, they are imperfect, subject to manipulation, and may sometimes produce falsity with significant consequence. Like Dick's novella implies: “The existence of a majority logically implies a corresponding minority.” However, in today's algorithmically churned and digitally platformed society, most data are presumed to be accurate and upon this assumption beliefs are held, and political and economic actions are taken. But what about the minority of this data production and its byproducts of decontextualized facts, misinformation, and other errors? If data are presumed to be accurate, what is the impact of inaccurate computations or outright falsity? How are we to discern reality or the simple truth in our digital environs? We must broadly examine the political and economic systems and their algorithmic processes that generate the information flows on social media platforms to describe how and understand why we get so much misinformation and falsity that is acted upon as truth. From there, we can engage in a process of critical analysis that reverse-engineers this process, so that we may more effectively suggest legal or other remedies to the problem and point to more just digital futures.

Before we can begin critically analyzing information on social media networks and its relationship to reality though, we must understand how data is produced from digital cypher. Chapter 2 defines a series of terms that will be analyzed throughout the remainder of the book. The chapter further describes their interrelationships, as well as how online platforms reproduce misinformation throughout the system. In addition to parsing the differences between disinformation, fake news, misinformation, and what has been termed as “bullshit” on social media, the focus will be on how I will use the terms “Artificial Intelligence” (e.g., “AI”) and x. “algorithm,” similar to Kenneth Wenger, to distinguish certain types of algorithms that engage in some form of Machine Learning.

This book will be of interest to students and scholars of media and communication studies, political science, sociology, and beyond who have an interest in understanding and addressing the impact AI, algorithms, and misinformation have on social media and society.