🤖〽️Prompt Engineering: Copilot Unabridged (Part 20: The Negative Influence of AI on the Recruitment Process)

Prompt Engineering Series

Prompt: "write a blogpost of 600 words on how much AI influences the recruitment process"

Introduction

Artificial Intelligence (AI) has transformed the hiring landscape, making recruitment faster, more efficient, and data-driven. However, despite its advantages, AI also introduces significant drawbacks that negatively impact job seekers and hiring practices. From bias in algorithms to depersonalization of the hiring process, AI’s influence on recruitment is not always positive.

1. AI Can Reinforce Bias in Hiring

One of the biggest concerns with AI-driven recruitment is algorithmic bias. AI models are trained on historical hiring data, which may contain gender, racial, or socioeconomic biases. If AI systems are not carefully monitored, they can perpetuate discrimination rather than eliminate it.

For example, AI-powered resume screening tools may favor candidates from certain backgrounds while filtering out others. In some cases, AI has been found to reject qualified applicants simply because their resumes were formatted differently than expected.

2. AI Depersonalizes the Hiring Process

AI-driven recruitment removes the human touch from hiring decisions. Automated systems prioritize efficiency over personal interaction, leading to:

• Lack of meaningful engagement between recruiters and candidates.
• Automated rejection emails without feedback, leaving applicants frustrated.
• "Ghosting" effect, where candidates never hear back after applying.

This depersonalization can make job seekers feel disconnected and undervalued, reducing trust in the hiring process.

3. Over-Reliance on AI Reduces Human Judgment

AI excels at processing large volumes of applications, but it lacks human intuition. Recruiters who rely too heavily on AI may:

• Overlook candidates with unconventional career paths who could be valuable assets.
• Ignore soft skills and cultural fit, which are crucial for team dynamics.
• Lose critical hiring expertise, as AI replaces traditional recruitment strategies.

AI-driven hiring decisions prioritize data points over human potential, leading to missed opportunities for both employers and job seekers.

4. AI Raises Ethical and Privacy Concerns

AI recruitment tools collect and analyze vast amounts of personal data, raising concerns about:

• Privacy violations, as candidates’ information is stored and processed without transparency.
• Data security risks, where sensitive applicant details could be exposed.
• Unregulated AI decision-making, leading to unfair hiring practices.

Without proper oversight, AI can compromise candidate privacy and create ethical dilemmas in recruitment.

5. AI Can Lead to Unfair Job Market Competition

AI-driven hiring favors candidates who optimize their resumes for algorithms, rather than those with genuine qualifications. This creates:

• Unfair advantages for applicants who understand AI screening systems.
• Disadvantages for candidates with unique skills that AI fails to recognize.
• A hiring process that prioritizes keywords over real-world experience.

Job seekers must adapt to AI-driven hiring trends, but this shift does not always reflect true talent or potential.

Conclusion: AI in Recruitment Needs Human Oversight

While AI enhances efficiency, its negative influence on recruitment cannot be ignored. Bias, depersonalization, ethical concerns, and reduced human judgment highlight the risks of over-reliance on AI.

To ensure fair hiring practices, companies must balance AI automation with human oversight, ensuring that recruitment remains inclusive, ethical, and candidate-focused.

Disclaimer: The whole text was generated by Copilot at the first attempt. This is just an experiment to evaluate feature's ability to answer standard general questions, independently on whether they are correctly or incorrectly posed. Moreover, the answers may reflect hallucinations and other types of inconsistent or incorrect reasoning.

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🤖〽️Prompt Engineering: Copilot Unabridged (Part 15: What AI Can Use Its Intelligence to Damage Society)

Prompt Engineering Series

Prompt: "write a blogpost of 600 words on how AI can use its intelligence to damage society"

Introduction

Artificial Intelligence (AI) has revolutionized industries, enhanced efficiency, and pushed the boundaries of technological innovation. However, like any powerful tool, AI can also be misused - leading to potential harm and disruption across society. Whether through intentional exploitation or unintended consequences, AI has the capability to damage social structures, ethical frameworks, and security systems. Understanding these risks is crucial to ensuring responsible AI development and implementation.

1. AI-Generated Misinformation and Psychological Manipulation

AI-powered algorithms influence social media, news platforms, and online content, shaping public opinion through personalized feeds and recommendations. While this can improve engagement, it also introduces dangerous risks:

• Deepfake technology allows AI to fabricate realistic videos and audio recordings, leading to false accusations and misinformation.
• AI-driven bots can amplify propaganda, manipulating elections and social movements.
• AI algorithms prioritize engagement over accuracy, boosting sensationalist and misleading content.

These AI-driven tactics can erode trust in media, democracy, and critical thinking, causing widespread manipulation of societal beliefs.

2. Mass Surveillance and Privacy Violations

AI plays a major role in government and corporate surveillance, tracking online activity, physical movements, and personal data. While AI-powered security can improve safety, excessive surveillance poses severe privacy risks:

• AI-powered facial recognition monitors individuals without consent, limiting freedoms.
• Governments can use AI to track populations, controlling dissent and opposition.
• AI systems collect massive amounts of personal data, increasing the likelihood of breaches, identity theft, and cyber exploitation.

AI intelligence enables unprecedented monitoring capabilities, leading to a society where privacy becomes obsolete.

3. AI-Driven Automation Causing Economic Displacement

AI enhances productivity, but its growing intelligence also replaces human labor, leading to mass unemployment. Some industries facing job losses due to AI automation include:

• Manufacturing: AI-powered robotics eliminate human factory workers.
• Finance: AI automates stock trading, reducing demand for financial analysts.
• Retail and customer service: AI chatbots replace call center employees and customer support agents.

Without proper economic restructuring, AI-driven displacement could widen income inequality, leading to social unrest and instability.

4. AI in Cybersecurity: A Weapon for Hackers

AI’s intelligence is a double-edged sword in cybersecurity. While AI strengthens cyber defense, it also enables:

• AI-generated malware that adapts and evolves, evading detection systems.
• Automated phishing scams that analyze human behavior to craft deceptive emails.
• AI-powered hacking tools capable of bypassing security measures at unprecedented speeds.

If malicious AI grows too sophisticated, even government and corporate security networks could be compromised, creating financial chaos and identity breaches.

5. Autonomous AI Leading to Unintended Consequences

Advanced AI systems operate independently, optimizing processes based on predefined goals. However, in some cases, AI’s intelligence pursues efficiency at the cost of ethical considerations:

• AI-driven weapon systems could make autonomous decisions on warfare, escalating conflicts beyond human control.
• AI optimizing resource allocation may deprioritize human well-being, prioritizing efficiency instead.
• AI-driven health automation could mismanage treatments, leading to errors in life-saving procedures.

Without human oversight and ethical guidelines, AI’s intelligence may unintentionally cause harm rather than solve problems.

Conclusion: Managing AI’s Intelligence for Society’s Benefit

While AI’s intelligence can damage society, these risks are not inevitable if developers, businesses, and governments take proactive steps to regulate and guide AI’s growth. Ethical AI frameworks, transparency, and responsible integration must be prioritized to ensure AI enhances society rather than undermining it.

AI is not inherently harmful, but uncontrolled development and exploitation could lead to lasting damage. The future depends on how humanity chooses to govern AI’s intelligence - whether as a tool for progress or a force for disruption.

Disclaimer: The whole text was generated by Copilot at the first attempt. This is just an experiment to evaluate feature's ability to answer standard general questions, independently on whether they are correctly or incorrectly posed. Moreover, the answers may reflect hallucinations and other types of inconsistent or incorrect reasoning.

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🤖〽️Prompt Engineering: Copilot Unabridged (Part 2: The Importance of AI in Society - A Transformational Force II)

Prompt Engineering Series

Prompt: "write a blogpost of 600 words on the importance of AI in society"

Introduction

Artificial Intelligence (AI) has rapidly evolved from a futuristic dream to an integral part of everyday life. Its presence is felt in industries ranging from healthcare to finance, transportation to entertainment. While some view AI as a tool of convenience, others recognize it as a force capable of reshaping the very fabric of society. As we continue integrating AI into our world, its impact - both promising and challenging - deserves careful consideration.

Revolutionizing Industries

AI’s ability to process vast amounts of data and uncover patterns has revolutionized multiple industries. In healthcare, AI-driven diagnostics assist doctors in identifying diseases like cancer with unparalleled precision. Medical imaging powered by AI can detect abnormalities that might otherwise be overlooked. Moreover, AI applications in drug discovery accelerate research, leading to faster development of treatments.

In finance, AI-powered algorithms analyze market trends, optimize investments, and even detect fraudulent transactions. Companies utilize AI to enhance customer service through chatbots that provide instant responses and personalized recommendations. Meanwhile, AI-driven automation boosts efficiency in manufacturing by streamlining processes and reducing human error.

Transportation is another domain benefiting from AI. Autonomous vehicles, once thought to be purely speculative, are now in active development, promising a future with safer roads and reduced congestion. AI-driven traffic management systems enhance urban mobility, making cities more efficient and eco-friendly.

Enhancing Accessibility and Communication

One of AI’s most profound societal contributions is its role in accessibility. AI-powered speech recognition and text-to-speech tools empower individuals with disabilities, allowing seamless interaction with technology. AI-driven language translation facilitates cross-cultural communication, bridging gaps between people and businesses worldwide.

In education, AI-powered tutoring systems adapt to students’ learning styles, providing personalized guidance and support. AI can analyze student performance, identify areas for improvement, and recommend tailored resources. This transformative approach makes education more inclusive and effective, breaking down traditional barriers.

Addressing Ethical and Societal Concerns

Despite AI’s remarkable benefits, its advancement raises ethical concerns. Bias in AI algorithms is a pressing issue, as data-driven models can inadvertently reflect and perpetuate existing societal inequalities. The responsibility falls on developers to ensure fairness and transparency in AI systems, fostering an equitable digital landscape.

Another concern is the impact of automation on employment. While AI creates new job opportunities in tech-driven industries, it also replaces traditional roles, sparking debates about workforce adaptation. The key lies in preparing society for AI’s integration by promoting education in AI-related fields and encouraging continuous skill development.

Privacy and security also come into focus as AI algorithms collect and analyze vast amounts of personal data. Safeguarding user privacy while leveraging AI’s capabilities requires stringent regulations and ethical AI development.

Embracing a Future Powered by AI

AI’s influence on society is undeniable - it has transformed industries, empowered individuals, and presented new opportunities. However, navigating AI’s complexities requires thoughtful implementation and ethical considerations. As we move forward, collaboration between policymakers, researchers, and the public will be crucial in ensuring AI benefits humanity responsibly and inclusively.

The future of AI is not just about innovation; it is about shaping a world where technology uplifts rather than divides. By fostering awareness, ethical development, and responsible use, we can harness AI as a tool for progress, paving the way for a society that embraces both human intelligence and artificial intelligence in harmony.

Disclaimer: The whole text was generated by Copilot (under Windows 10) at the first attempt. This is just an experiment to evaluate feature's ability to answer standard general questions, independently on whether they are correctly or incorrectly posed. Moreover, the answers may reflect hallucinations and other types of inconsistent or incorrect reasoning.

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🤖〽️Prompt Engineering: Copilot Unabridged (Part 1: The Importance of AI in Society - A Transformational Force)

Prompt Engineering Series

Prompt: "write a blogpost of 600 words on the importance of AI in society"

Introduction

Artificial Intelligence (AI) has evolved from a futuristic concept to a daily reality that shapes industries, economies, and even personal lives. Once confined to science fiction, AI now drives technological progress and redefines the way we interact with the world. In this blog post, we will explore the significance of AI, how it influences various sectors, and the ethical considerations accompanying its rapid adoption.

AI: The Backbone of Modern Innovation

At its core, AI enables machines to perform tasks that typically require human intelligence - such as learning, reasoning, problem-solving, and decision-making. From automating repetitive tasks to augmenting human capabilities, AI has proven indispensable across multiple domains.

Take healthcare, for example. AI-powered algorithms analyze complex medical data to assist doctors in diagnosing diseases, predicting patient outcomes, and even recommending personalized treatment plans. Innovations like AI-driven robotic surgery and early cancer detection systems save lives and enhance the precision of medical procedures.

In finance, AI plays a crucial role in fraud detection, risk assessment, and automated trading. Financial institutions leverage machine learning models to analyze spending patterns, prevent cyberattacks, and provide tailored investment advice. AI’s ability to process massive amounts of data ensures accuracy and efficiency in financial operations.

Retail and e-commerce have also been transformed. AI-driven recommendation engines predict customer preferences based on purchasing behavior, allowing businesses to offer personalized shopping experiences. Chatbots streamline customer service, while automated inventory management optimizes supply chain efficiency. AI ensures that companies stay competitive in an increasingly digital marketplace.

AI and the Workplace: Automation vs. Augmentation

The integration of AI into the workplace sparks ongoing debates about its impact on jobs. While automation replaces certain manual tasks, it also opens doors for new career opportunities. AI-driven tools enable professionals to focus on creative and strategic work rather than repetitive processes.

For instance, AI-powered analytics help marketers assess consumer sentiment and predict trends with unprecedented accuracy. Similarly, AI assists engineers and researchers in designing smarter infrastructure, accelerating scientific discoveries, and optimizing business operations.

Rather than eliminating jobs, AI redefines them. Organizations must invest in upskilling employees to harness AI effectively, fostering a collaborative environment where human creativity complements machine intelligence.

Ethical Considerations and Responsible AI Development

With great power comes great responsibility. As AI grows more sophisticated, ethical concerns regarding data privacy, bias, and transparency become more pressing.

AI systems rely on large datasets to function, raising concerns about privacy and security. Governments and corporations must establish stringent regulations to protect user information from misuse or exploitation. Additionally, biases in AI models can lead to discriminatory outcomes, necessitating fair and inclusive development practices.

Transparency is another critical factor. Users should understand how AI-driven decisions are made, particularly in sensitive areas like healthcare and criminal justice. Ethical AI implementation requires collaboration between policymakers, technologists, and the public to ensure that advancements benefit society as a whole.

The Future of AI: A Balance Between Progress and Ethics

The importance of AI in society cannot be understated. It enhances productivity, improves decision-making, and solves complex problems across industries. However, its responsible use is paramount to prevent unintended consequences.

As AI continues to evolve, collaboration between academia, businesses, and governments is necessary to establish ethical guidelines and maximize its benefits. The goal should not be to replace human intelligence but to amplify it, fostering innovation while ensuring accountability.

Ultimately, AI is more than just a tool - it is a transformative force shaping the future. Harnessing its potential wisely will determine whether it serves as a steppingstone toward progress or a challenge requiring careful navigation.

Disclaimer: The whole text was generated by Copilot at the first attempt. This is just an experiment to evaluate feature's ability to answer standard general questions, independently on whether they are correctly or incorrectly posed. Moreover, the answers may reflect hallucinations and other types of inconsistent or incorrect reasoning.

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🛡️Information Security: Data Privacy (Definitions)

"Right of an individual to participate in decisions regarding the collection, use, and disclosure of information personally identifiable to that individual." (Reima Suomi, "Telework and Data Privacy and Security", 2008)

"Current United States laws provide protection to private data, including students’ performance data. Online distance education environments need to address privacy issues though design of courses and security features built into record keeping systems." (Gregory C Sales, "Preparing Teachers to Teach Online", 2009)

"Personal data should not be automatically available to other persons or organizations. Even if data have been processed, each individual should be able to exercise his or her right to control access to data and related information." (Astrid Gesche, "Adapting to Virtual Third-Space Language Learning Futures", 2009)

"The right to have personally identifiable information not disclosed in any unauthorized manner." (David G Hill, "Data Protection: Governance, Risk Management, and Compliance", 2009)

"The limitation of data access to only those authorized to view the data." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"The legal, political, and ethical issues surrounding the collection and dissemination of data, the technology used, and the expectations of what information is shared with whom." (Jonathan Ferrar et al, "The Power of People: Learn How Successful Organizations Use Workforce Analytics To Improve Business Performance", 2017)

"A compliance program aimed at protection of personal information about any individual the company may poses." (Svetlana Snezhko & Ali Coskun, "Compliance in Sustainability Reporting", 2019)

"Data containing information about a person should be treated with special attention according to the organization’s data privacy policy and legislation." (Lili Aunimo et al, "Big Data Governance in Agile and Data-Driven Software Development: A Market Entry Case in the Educational Game Industry", 2019)

"The term refers to the confidentiality of information that one has and other parties are not allowed to share it without a consent of the data owner. Privacy is a measure of control for individuals about their personal information." (M Fevzi Esen & Eda Kocabas, "Personal Data Privacy and Protection in the Meeting, Incentive, Convention, and Exhibition (MICE) Industry", 2019)

"This term relates to the individual right to restrict access to their personal, health, political/philosophical views, religious affiliation and educational data. In the case of students, schools and districts have the responsibility to control access to student data, providing it is available only to those who play a role in the learning process and for a defined time span." (Beatriz Arnillas, "Tech-Savvy Is the New Street Smart: Balancing Protection and Awareness", 2019)

"Protection of personal privacy during data acquisition, storage, transmission, and usage." (Hemlata Gangwar, "Big Data Adoption: A Comparative Study of the Indian Manufacturing and Services Sectors", 2020)

"the protection of any representation of information that permits the identity of an individual to whom the information applies to be reasonably inferred by either direct or indirect means." (James Kelly et al, "Data in the Wild: A KM Approach to Collecting Census Data Without Surveying the Population and the Issue of Data Privacy", 2020)

"A person’s right to control how much information about her/him/them is collected, used, shared by others." (Zerin M Khan, "How Do Mobile Applications for Cancer Communicate About Their Privacy Practices?: An Analysis of Privacy Policies", 2021)

"Deals defining what data may be lawfully shared with third parties, by an individual or organization." (Nikhil Padayachee & Surika Civilcharran, "Predicting Student Intention to Use Cloud Services for Educational Purposes Based on Perceived Security and Privacy", 2021)

"Is the aspect of information and communication technology that deals with the ability an organization or individual to determine what data and information in computer system can be shared with third parties." (Valerianus Hashiyana et al, "Integrated Big Data E-Healthcare Solutions to a Fragmented Health Information System in Namibia", 2021)

🛡️Information Security: Privacy (Definitions)

"Privacy is concerned with the appropriate use of personal data based on regulation and the explicit consent of the party." (Martin Oberhofer et al, "Enterprise Master Data Management", 2008)

"Proper handling and use of personal information (PI) throughout its life cycle, consistent with data-protection principles and the preferences of the subject." (Alex Berson & Lawrence Dubov, "Master Data Management and Data Governance", 2010)

"Control of data usage dealing with the rights of individuals and organizations to determine the “who, what, when, where, and how” of data access." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed, 2011)

"Keeping information as a secret, known only to the originators of that information. This contrasts with confidentiality, in which information is shared among a select group of recipients. See also confidentiality." (Mark Rhodes-Ousley, "Information Security: The Complete Reference" 2nd Ed., 2013)

"Control of data usage dealing with the rights of individuals and organizations to determine the “who, what, when, where, and how” of data access." (Carlos Coronel & Steven Morris, "Database Systems: Design, Implementation, & Management" 11th  Ed.", 2014)

"The ability of a person to keep personal information to himself or herself." (Jason Williamson, "Getting a Big Data Job For Dummies", 2015)

"The protection of individual rights to nondisclosure." (Mike Harwood, "Internet Security: How to Defend Against Attackers on the Web" 2nd Ed., 2015)

"The right of individuals to control or influence what information related to them may be collected and stored and by whom, as well as to whom that information may be disclosed." (William Stallings, "Effective Cybersecurity: A Guide to Using Best Practices and Standards", 2018)

 "The right of individuals to a private life includes a right not to have personal information about themselves made public. A right to privacy is recognised by the Universal Declaration of Human Rights and the European Convention on Human Rights. See data protection legislation." (Open Data Handbook)

"to seclude certain data /information about oneself that is deemed personal." (Analytics Insight)

🛡️Information Security: Privacy (Definitions)

"Privacy is concerned with the appropriate use of personal data based on regulation and the explicit consent of the party." (Martin Oberhofer et al, "Enterprise Master Data Management", 2008)

[MDM privacy:] "Privacy is focused on the appropriate use of personal data based on regulation and the explicit consent of the Party. MDM Systems that have Party data (customer or patient) are quite sensitive to privacy concerns and regulations." (Allen Dreibelbis et al, "Enterprise Master Data Management", 2008)

"The ability of keeping secret someone’s identity, resources, or actions. It is realized by anonymity and pseudonymity." (Tomasz Ciszkowski & Zbigniew Kotulski, "Secure Routing with Reputation in MANET", 2008)

"Proper handling and use of personal information (PI) throughout its life cycle, consistent with data-protection principles and the preferences of the subject." (Alex Berson & Lawrence Dubov, "Master Data Management and Data Governance", 2010)

"Control of data usage dealing with the rights of individuals and organizations to determine the 'who, what, when, where, and how' of data access." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)

"Keeping information as a secret, known only to the originators of that information. This contrasts with confidentiality, in which information is shared among a select group of recipients." (Mark Rhodes-Ousley, "Information Security: The Complete Reference" 2nd Ed., 2013)

"The ability of a person to keep personal information to himself or herself." (Jason Williamson, "Getting a Big Data Job For Dummies", 2015)

"The protection of individual rights to nondisclosure." (Mike Harwood, "Internet Security: How to Defend Against Attackers on the Web" 2nd Ed., 2015)

"The right of individuals to control or influence what information related to them may be collected and stored and by whom, as well as to whom that information may be disclosed." (William Stallings, "Effective Cybersecurity: A Guide to Using Best Practices and Standards", 2018)

"The right of individuals to a private life includes a right not to have personal information about themselves made public." (Open Data Handbook)

⛏️Data Management: Data Protection (Definitions)

"The protecting of data from damage, destruction, and unauthorized alteration." (Tom Petrocelli, "Data Protection and Information Lifecycle Management", 2005)

"Deals with issues such as data security, privacy, and availability. Data protection controls are required by regulations and industry mandates such as Sarbanes-Oxley, European Data Protection Law, and others." (Allen Dreibelbis et al, "Enterprise Master Data Management", 2008)

"A set of rules that aim to protect the rights, freedoms and interests of individuals when information related to them is being processed." (Maria Tzanou, "Data Protection in EU Law after Lisbon: Challenges, Developments, and Limitations", 2015)

"An umbrella term for various procedures that ensure information is secure and available only to authorized users." (Peter Sasvari & Zoltán Nagymate, "The Empirical Analysis of Cloud Computing Services among the Hungarian Enterprises", 2015)

"Protection of the data against unauthorized access by third parties as well as protection of personal data (such as customer data) in the processing of data according to the applicable legal provisions." (Boris Otto & Hubert Österle, "Corporate Data Quality", 2015)

"Legal control over access to, and use of, data in computers." (Lucy Self & Petros Chamakiotis, "Understanding Cloud Computing in a Higher Education Context", 2018)

"Data protection is a task of safeguarding personal or sensitive data which are complex and widely distributed." (M Fevzi Esen & Eda Kocabas, "Personal Data Privacy and Protection in the Meeting, Incentive, Convention, and Exhibition (MICE) Industry", 2019)

"Process of protecting important information from corruption, compromise, or loss." (Patrícia C T Gonçalves, "Medical Social Networks, Epidemiology and Health Systems", 2021)

"The process involving use of laws to protect data of individuals from unauthorized disclosure or access." (Frank Makoza, "Learning From Abroad on SIM Card Registration Policy: The Case of Malawi", 2019)

"Is the process in information and communication technology that deals with the ability an organization or individual to safeguard data and information from corruption, theft, compromise, or loss." (Valerianus Hashiyana et al, "Integrated Big Data E-Healthcare Solutions to a Fragmented Health Information System in Namibia", 2021)

"The mechanisms with which an organization enables individuals to retain control of the personal data they willingly share, where security provides policies, controls, protocols, and technologies necessary to fulfill rules and obligations in accordance with privacy regulations, industry standards, and the organization's ethics and social responsibility." (Forrester)

🧿Glenn Greenwald - Collected Quotes

"A population, a country that venerates physical safety above all other values will ultimately give up its liberty and sanction any power seized by authority in exchange for the promise, no matter how illusory, of total security. However, absolute safety is itself chimeric, pursued by never obtained. The pursuit degrades those who engage in it as well as any nation that comes to be defined by it."  (Glenn Greenwald, "No Place to Hide", 2014)

"A prime justification for surveillance - that it’s for the benefit of the population - relies on projecting a view of the world that divides citizens into categories of good people and bad people. In that view, the authorities use their surveillance powers only against bad people, those who are “doing something wrong,” and only they have anything to fear from the invasion of their privacy."  (Glenn Greenwald, "No Place to Hide", 2014)

"Converting the Internet into a system of surveillance thus guts it of its core potential. Worse, it turns the Internet into a tool of repression, threatening to produce the most extreme and oppressive weapon of state intrusion human history has ever seen."  (Glenn Greenwald, "No Place to Hide", 2014)

"Democracy requires accountability and consent of the governed, which is only possible if citizens know what is being done in their name."  (Glenn Greenwald, "No Place to Hide", 2014)

"Far from hyperbole, that is the literal, explicitly stated aim of the surveillance state: to collect, store, monitor, and analyze all electronic communication by all people around the globe."  (Glenn Greenwald, "No Place to Hide", 2014)

"For many kids, the Internet is a means of self-actualization. It allows them to explore who they are and who they want to be, but that works only if we’re able to be private and anonymous, to make mistakes without them following us."  (Glenn Greenwald, "No Place to Hide", 2014)

"Technology has now enabled a type of ubiquitous surveillance that had previously been the province of only the most imaginative science fiction writers." (Glenn Greenwald, "No Place to Hide", 2014)

"The ability to eavesdrop on people’s communications vests immense power in those who do it. And unless such power is held in check by rigorous oversight and accountability, it is almost certain to be abused."  (Glenn Greenwald, "No Place to Hide", 2014)

"The principle which protects personal writings and all other personal productions, not against theft and physical appropriation, but against publication in any form, is in reality not the principle of private property, but that of an inviolate personality."  (Glenn Greenwald, "No Place to Hide", 2014)

"To permit surveillance to take root on the Internet would mean subjecting virtually all forms of human interaction, planning, and even thought itself to comprehensive state examination."  (Glenn Greenwald, "No Place to Hide", 2014)

"We all instinctively understand that the private realm is where we can act, think, speak, write, experiment, and choose how to be, away from the judgmental eyes of others. Privacy is a core condition of being a free person."  (Glenn Greenwald, "No Place to Hide", 2014)

"We shouldn't have to be faithful loyalists of the powerful to feel safe from state surveillance. Nor should the price of immunity be refraining from controversial or provocative dissent. We shouldn't want a society where the message is conveyed that you will be left alone only if you mimic the accommodating behavior and conventional wisdom of an establishment columnist."  (Glenn Greenwald, "No Place to Hide", 2014)

"What made the Internet so appealing was precisely that it afforded the ability to speak and act anonymously, which is so vital to individual exploration."  (Glenn Greenwald, "No Place to Hide", 2014)

🧩IT: Privacy (Just the Quotes)

"The personal life of every individual is based on secrecy, and perhaps it is partly for that reason that civilized man is so nervously anxious that personal privacy should be respected." (Anton Chekhov, "A Doctor's Visit", 1898)

"Solitude and privacy have become more essential to the individual; but modern enterprise and invention have, through invasions upon his privacy, subjected him to mental pain and distress." (Samuel D Warren, "The Development of the Right of Privacy in New York", 1954)

"The fantastic advances in the field of electronic communication constitute a greater danger to the privacy of the individual." (Earl Warren, "Concurring in the judgment, Lopez v. United States 373 U.S. 427", 1963)

"Complete and accurate surveillance as a means of control is probably a practical impossibility. What is much more likely is a loss of privacy and constant inconvenience as the wrong people gain access to information, as one wastes time convincing the inquisitors that one is in fact innocent, or as one struggles to untangle the errors of the errant machine." (Victor C Ferkiss, "Technological Man: The Myth and the Reality", 1969)

"Privacy invasion is now one of biggest knowledge industries." (Marshall McLuhan, "Culture Is Our Business", 1970)

"Privacy - like eating and breathing - is one of life's basic requirements." (Katherine Neville, "A Calculated Risk: A Novel", 1992)

"If machines knew as much about each other as we know about each other (even in our privacy), the ecology of machines would be indomitable." (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995) 

"Privacy is a type of conversation. Firms should view privacy not as some inconvenient obsession of customers that must be snuck around but more as a way to cultivate a genuine relationship." (Kevin Kelly, "New Rules for the New Economy: 10 radical strategies for a connected world", 1998)

"The first form of semantic data on the Web was metadata information about information. (There happens to be a company called Metadata, but I use the term here as a generic noun, as it has been used for many years.) Metadata consist of a set of properties of a document. By definition, metadata are data, as well as data about data. They describe catalogue information about who wrote Web pages and what they are about; information about how Web pages fit together and relate to each other as versions; translations, and reformattings; and social information such as distribution rights and privacy codes." (Tim Berners-Lee, "Weaving the Web", 1999)

"Privacy is not a static construct. It is not an inherent property of any particular information or setting. It is a process by which people seek to have control over a social situation by managing impressions, information flows, and context." (Danah Boyd, "It's Complicated: The Social Lives of Networked Teens", 2014)

"Arguing that you don't care about the right to privacy because you have nothing to hide is no different than saying you don't care about free speech because you have nothing to say." (Edward Snowden, 2015)

"Data governance policies must not enforce constraints on data - Data governance intends to control the level of democracy within the data lake. Its sole purpose of existence is to maintain the quality level through audits, compliance, and timely checks. Data flow, either by its size or quality, must not be constrained through governance norms. [...] Effective data governance elevates confidence in data lake quality and stability, which is a critical factor to data lake success story. Data compliance, data sharing, risk and privacy evaluation, access management, and data security are all factors that impact regulation." (Saurabh Gupta et al, "Practical Enterprise Data Lake Insights", 2018)

"Metadata is the key to effective data governance. Metadata in this context is the data that defines the structure and attributes of data. This could mean data types, data privacy attributes, scale, and precision. In general, quality of data is directly proportional to the amount and depth of metadata provided. Without metadata, consumers will have to depend on other sources and mechanisms." (Saurabh Gupta et al, "Practical Enterprise Data Lake Insights", 2018)

"Data privacy, data confidentiality, and data protection are sometimes incorrectly diluted with security. For example, data privacy is related to, but not the same as, data security. Data security is concerned with assuring the confidentiality, integrity, and availability of data. Data privacy focuses on how and to what extent businesses may collect and process information about individuals." (Bill Inmon et al, "Building the Data Lakehouse", 2021)