This book explores, through a children’s rights-based perspective, the emergence of a safeguarding dystopia in child online protection that has emerged from a tension between an over-reliance in technical solutions and a lack of understanding around code and algorithm capabilities. The text argues that a safeguarding dystopia results in docile children, rather than safe ones, and that we should stop seeing technology as the sole solution to online safeguarding. The reader will, through reading this book, gain a deeper understanding of the current policy arena in online safeguarding, what causes children to beocme upset online, and the doomed nature of safeguarding solutions. The book also features a detailed analysis of issues surrounding content filtering, access monitoring, surveillance, image recognition, and tracking. This book is aimed at legal practitioners, law students, and those interested in child safeguarding and technology.

Examines the crucial role of nurses and other public health professionals in child protection.

"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics (aka machine learning) unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a

In an ever-evolving educational landscape, traditional methods face unprecedented challenges. The Impact of ChatGPT on Higher Education takes you on a trailblazing journey into ChatGPT's transformative potential and the ethical considerations in higher education.

Comprehensive coverage of critical issues related to information science and technology.

This edited volume analyses the digital development of the European Union, presenting an interdisciplinary perspective from the disciplines of political science, international relations, economics, and law. The contributions address the main areas where the EU can, and should act, for creating an efficient and protective digital space in Europe. The book highlights the responsibility of the European Union to work on the future of its digital development, looking for prosperity and defending the European conception of society. It explains how European values must be incorporated into the digital revolution and shows how the digital revolution of the EU will defend the Europeans from new threats. The book's comprehensive approach allows the reader to understand this process without in-depth knowledge of the specific discipline. Therefore, it is a must-read for everybody interested in a better understanding of digital development, European Union policy, and the future of Europe.