EasterBlack-owned or founded brands at TargetGroceryClothing, Shoes & AccessoriesBabyHomeFurnitureKitchen & DiningOutdoor Living & GardenToysElectronicsVideo GamesMovies, Music & BooksSports & OutdoorsBeautyPersonal CareHealthPetsHousehold EssentialsArts, Crafts & SewingSchool & Office SuppliesParty SuppliesLuggageGift IdeasGift CardsClearanceTarget New ArrivalsTarget Finds#TargetStyleTop DealsTarget Circle DealsWeekly AdShop Order PickupShop Same Day DeliveryRegistryRedCardTarget CircleFind Stores

Sponsored

How Algorithms Create and Prevent Fake News - by Noah Giansiracusa (Paperback)

How Algorithms Create and Prevent Fake News - by  Noah Giansiracusa (Paperback) - 1 of 1
$43.25 sale price when purchased online
$44.99 list price
Target Online store #3991

About this item

Highlights

  • "It's a joy to read a book by a mathematician who knows how to write.
  • About the Author: Noah Giansiracusa received a PhD in mathematics from Brown University and is an Assistant Professor of Mathematics and Data Science at Bentley University, a business school near Boston.
  • 235 Pages
  • Computers + Internet, Programming

Description



About the Book



"From deepfakes to GPT-3, deep learning is now powering a new assault on our ability to tell whats real and whats 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 whats 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. Dont 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"--



Book Synopsis



"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 todayis 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

Who This Book is For

People who don't have a technical background (in data, computers, etc.) but who would like to learn how algorithms impact society; business leaders who want to know the powers and perils of relying on artificial intelligence. A secondary audience is people with a technical background who want to explore the larger social and societal impact of their work.



From the Back Cover



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 anaccessible, 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.



Review Quotes




"The book requires no technical background and is widely accessible. The narrative is compelling, with good use of historical and contemporary examples ... . The exposition hits a sweet spot - precise and thorough, yet brisk and not overly technical - that could make for some excellent supplemental reading ... . This book succeeds in its objective and is an easy recommendation for anyone looking to understand these issues at a deeper level than we find in the popular media." (Bill Wood, MAA Reviews, January 10, 2022)



About the Author



Noah Giansiracusa received a PhD in mathematics from Brown University and is an Assistant Professor of Mathematics and Data Science at Bentley University, a business school near Boston. He previously taught at U.C. Berkeley, University of Georgia, and Swarthmore College. He has dozens of publications in math and data science and has taught courses ranging from a first-year seminar on quantitative literacy to graduate machine learning. Most recently, he created an interdisciplinary seminar on truth and lies in data that was the impetus for this book. He has received national grants and spoken at international conferences for his research in mathematics, and he has been quoted several times in Forbes as an expert on artificial intelligence. Noah also created a high school outreach program for underrepresented and disadvantaged youths, focusing on mathematics and statistics in the courtroom, that was headlined by an Obama-appointed Federal Circuit judge.

Dimensions (Overall): 9.21 Inches (H) x 6.14 Inches (W) x .52 Inches (D)
Weight: .78 Pounds
Suggested Age: 22 Years and Up
Sub-Genre: Programming
Genre: Computers + Internet
Number of Pages: 235
Publisher: Apress
Theme: Algorithms
Format: Paperback
Author: Noah Giansiracusa
Language: English
Street Date: July 15, 2021
TCIN: 93043800
UPC: 9781484271544
Item Number (DPCI): 247-31-2703
Origin: Made in the USA or Imported
If the item details above aren’t accurate or complete, we want to know about it.

Shipping details

Estimated ship dimensions: 0.52 inches length x 6.14 inches width x 9.21 inches height
Estimated ship weight: 0.78 pounds
We regret that this item cannot be shipped to PO Boxes.
This item cannot be shipped to the following locations: American Samoa (see also separate entry under AS), Guam (see also separate entry under GU), Northern Mariana Islands, Puerto Rico (see also separate entry under PR), United States Minor Outlying Islands, Virgin Islands, U.S., APO/FPO

Return details

This item can be returned to any Target store or Target.com.
This item must be returned within 90 days of the date it was purchased in store, shipped, delivered by a Shipt shopper, or made ready for pickup.
See the return policy for complete information.

Related Categories

Get top deals, latest trends, and more.

Privacy policy

Footer

About Us

About TargetCareersNews & BlogTarget BrandsBullseye ShopSustainability & GovernancePress CenterAdvertise with UsInvestorsAffiliates & PartnersSuppliersTargetPlus

Help

Target HelpReturnsTrack OrdersRecallsContact UsFeedbackAccessibilitySecurity & FraudTeam Member Services

Stores

Find a StoreClinicPharmacyOpticalMore In-Store Services

Services

Target Circle™Target Circle™ CardTarget Circle 360™Target AppRegistrySame Day DeliveryOrder PickupDrive UpFree 2-Day ShippingShipping & DeliveryMore Services
PinterestFacebookInstagramXYoutubeTiktokTermsCA Supply ChainPrivacyCA Privacy RightsYour Privacy ChoicesInterest Based AdsHealth Privacy Policy