Privacy Means Profit

Bulletproof your organization against data breach, identity theft, and corporate espionage In this updated and revised edition of Privacy Means Profit, John Sileo demonstrates how to keep data theft from destroying your bottom line, both personally and professionally. In addition to sharing his gripping tale of losing $300,000 and his business to data breach, John writes about the risks posed by social media, travel theft, workplace identity theft, and how to keep it from happening to you and your business. By interlacing his personal experience with cutting-edge research and unforgettable stories, John not only inspires change inside of your organization, but outlines a simple framework with which to build a Culture of Privacy. This book is a must-read for any individual with a Social Security Number and any business leader who doesn't want the negative publicity, customer flight, legal battles and stock depreciation resulting from data breach. Protect your net worth and bottom line using the 7 Mindsets of a Spy Accumulate Layers of Privacy Eliminate the Source Destroy Data Risk Lock Your Assets Evaluate the Offer Interrogate the Enemy Monitor the Signs In this revised edition, John includes an 8th Mindset, Adaptation, which serves as an additional bridge between personal protection and bulletproofing your organization. Privacy Means Profit offers a one-stop guide to protecting what's most important and most at risk-your essential business and personal data.

"Profit over Privacy gives internet surveillance a much-needed origin story by chronicling the development of its most important historical catalyst: web advertising"--

The challenges to humanity posed by the digital future, the first detailed examination of the unprecedented form of power called "surveillance capitalism," and the quest by powerful corporations to predict and control our behavior. In this masterwork of original thinking and research, Shoshana Zuboff provides startling insights into the phenomenon that she has named surveillance capitalism. The stakes could not be higher: a global architecture of behavior modification threatens human nature in the twenty-first century just as industrial capitalism disfigured the natural world in the twentieth. Zuboff vividly brings to life the consequences as surveillance capitalism advances from Silicon Valley into every economic sector. Vast wealth and power are accumulated in ominous new "behavioral futures markets," where predictions about our behavior are bought and sold, and the production of goods and services is subordinated to a new "means of behavioral modification." The threat has shifted from a totalitarian Big Brother state to a ubiquitous digital architecture: a "Big Other" operating in the interests of surveillance capital. Here is the crucible of an unprecedented form of power marked by extreme concentrations of knowledge and free from democratic oversight. Zuboff's comprehensive and moving analysis lays bare the threats to twenty-first century society: a controlled "hive" of total connection that seduces with promises of total certainty for maximum profit -- at the expense of democracy, freedom, and our human future. With little resistance from law or society, surveillance capitalism is on the verge of dominating the social order and shaping the digital future -- if we let it.

At the heart of 'The Right to Privacy' lies an exploration of the increasingly blurred line between the private and the public, a theme that resonates as much today as at its inception. This collection, curated with a keen eye for diversity in perspective and style, traverses the complex landscape of privacy rights in the modern world. The anthology stands out for its rigorous examination of the legal, ethical, and societal dimensions of privacy, weaving together landmark cases, pivotal essays, and critical analyses to offer a multifaceted view of privacy's evolving definition and its implications. The inclusion of foundational works such as the seminal essay by Louis Brandeis and Samuel D. Warren highlights the depth and historical significance of the discourse presented. The editors and contributors, hailing from a broad spectrum of backgrounds in law, ethics, and technology, collectively underscore the anthology's thematic coherence. Their disparate vantage points, rooted in different eras and engaging with varying aspects of privacy, illuminate the rich tapestry of legal thought and ethical considerations. This convergence of historical and contemporary views underlines the collection's alignment with significant cultural and legal shifts, reflecting society's ongoing struggle to balance personal privacy with public interest. 'The Right to Privacy' is indispensable for readers seeking to navigate the intricate and often contentious terrain of privacy rights. It promises an enlightening journey through the kaleidoscope of opinions and analyses, offering valuable insights and fostering a deeper understanding of what it means to protect personal boundaries in an increasingly open world. This anthology is a must-read for anyone invested in the pivotal debates surrounding privacy, beckoning with the allure of a comprehensive and nuanced exploration of one of the most pressing issues of our time.

The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of differential privacy, and proceeds to explore the fundamental techniques for achieving differential privacy, and the application of these techniques in creative combinations, using the query-release problem as an ongoing example. A key point is that, by rethinking the computational goal, one can often obtain far better results than would be achieved by methodically replacing each step of a non-private computation with a differentially private implementation. Despite some powerful computational results, there are still fundamental limitations. Virtually all the algorithms discussed herein maintain differential privacy against adversaries of arbitrary computational power -- certain algorithms are computationally intensive, others are efficient. Computational complexity for the adversary and the algorithm are both discussed. The monograph then turns from fundamentals to applications other than query-release, discussing differentially private methods for mechanism design and machine learning. The vast majority of the literature on differentially private algorithms considers a single, static, database that is subject to many analyses. Differential privacy in other models, including distributed databases and computations on data streams, is discussed. The Algorithmic Foundations of Differential Privacy is meant as a thorough introduction to the problems and techniques of differential privacy, and is an invaluable reference for anyone with an interest in the topic.

Over the course of a generation, algorithms have gone from mathematical abstractions to powerful mediators of daily life. Algorithms have made our lives more efficient, more entertaining, and, sometimes, better informed. At the same time, complex algorithms are increasingly violating the basic rights of individual citizens. Allegedly anonymized datasets routinely leak our most sensitive personal information; statistical models for everything from mortgages to college admissions reflect racial and gender bias. Meanwhile, users manipulate algorithms to "game" search engines, spam filters, online reviewing services, and navigation apps. Understanding and improving the science behind the algorithms that run our lives is rapidly becoming one of the most pressing issues of this century. Traditional fixes, such as laws, regulations and watchdog groups, have proven woefully inadequate. Reporting from the cutting edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design. Michael Kearns and Aaron Roth explain how we can better embed human principles into machine code - without halting the advance of data-driven scientific exploration. Weaving together innovative research with stories of citizens, scientists, and activists on the front lines, The Ethical Algorithm offers a compelling vision for a future, one in which we can better protect humans from the unintended impacts of algorithms while continuing to inspire wondrous advances in technology.

The De Gruyter Handbook of Artificial Intelligence, Identity and Technology Studies examines the relationship of the social sciences to artificial intelligence, surveying the various convergences and divergences between science and technology studies on the one hand and identity transformations on the other. It provides representative coverage of all aspects of the AI revolution, from employment to education to military warfare, impacts on public policy and governance and the future of ethics. How is AI currently transforming social, economic, cultural and psychological processes? This handbook answers these questions by looking at recent developments in supercomputing, deep learning and neural networks, including such topics as AI mobile technology, social robotics, big data and digital research. It focuses especially on mechanisms of identity by defining AI as a new context for self-exploration and social relations and analyzing phenomena such as race, ethnicity and gender politics in human-machine interfaces.

Author of cult classics The Pumpkin Plan and The Toilet Paper Entrepreneur offers a simple, counterintuitive cash management solution that will help small businesses break out of the doom spiral and achieve instant profitability. Conventional accounting uses the logical (albeit, flawed) formula: Sales - Expenses = Profit. The problem is, businesses are run by humans, and humans aren't always logical. Serial entrepreneur Mike Michalowicz has developed a behavioral approach to accounting to flip the formula: Sales - Profit = Expenses. Just as the most effective weight loss strategy is to limit portions by using smaller plates, Michalowicz shows that by taking profit first and apportioning only what remains for expenses, entrepreneurs will transform their businesses from cash-eating monsters to profitable cash cows. Using Michalowicz's Profit First system, readers will learn that: · Following 4 simple principles can simplify accounting and make it easier to manage a profitable business by looking at bank account balances. · A small, profitable business can be worth much more than a large business surviving on its top line. · Businesses that attain early and sustained profitability have a better shot at achieving long-term growth. With dozens of case studies, practical, step-by-step advice, and his signature sense of humor, Michalowicz has the game-changing roadmap for any entrepreneur to make money they always dreamed of.