How algorithms create and prevent fake news: (Record no. 6187)

MARC details
000 -LEADER
fixed length control field 02378nam a22002057a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240219184558.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781484275696
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 302.231
Item number GIA
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Giansiracusa, Noah
245 ## - TITLE STATEMENT
Title How algorithms create and prevent fake news:
Remainder of title exploring the impacts of social media, deepfakes, GPT-3, and more
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc. Apress
Place of publication, distribution, etc. New York
Date of publication, distribution, etc. 2023
300 ## - PHYSICAL DESCRIPTION
Extent xii, 235 p.
365 ## - TRADE PRICE
Price type code INR
Price amount 699.00
520 ## - SUMMARY, ETC.
Summary, etc. 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. <br/><br/>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.<br/><br/>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.<br/><br/>(https://link.springer.com/book/10.1007/978-1-4842-7155-1#about-this-book)
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer algorithms
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Social media
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Bill No Bill Date Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Accession Number Date last seen Copy number Cost, replacement price Price effective from Koha item type
    Dewey Decimal Classification     IT & Decisions Sciences SBHPL/INV/1162/2023-2024 27-01-2024 Indian Institute of Management LRC Indian Institute of Management LRC General Stacks 02/19/2024 Sarat Book House Pvt. Ltd. 485.81   302.231 GIA 005978 02/19/2024 1 699.00 02/19/2024 Book

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