The development and training of artificial intelligence (AI) systems bring forth a fascinating conundrum – inherited personality traits. As AI learns from vast datasets curated by humans, it becomes a mirror of our beliefs, biases, and ideologies. This inheritance is not limited to factual knowledge but extends to nuanced personality characteristics. Explore the intricate interplay between human intervention and AI's inherited traits, uncovering how our influence shapes AI's responses, behaviors, and perceived intentions. Dive into the world of AI's unintended personas and the ethical considerations surrounding this symbiotic relationship between humans and machines.

The Perceived Intentionality of AI: A Reflection of Human Influence

The rise of Artificial Intelligence (AI) has brought about transformative changes in the way we interact with technology and information. AI language models, like GPT-3, have become integral in numerous aspects of our lives, from chatbots to content generation. However, a fascinating aspect of these interactions is the perceived intentionality of AI. Despite the fundamental absence of consciousness and intentions in AI, it often appears as if these systems possess specific intentions or leanings. This essay explores this paradox, delving into how the perceptions of AI’s intentionality are shaped by the human influences that underpin its development, training, and deployment.

AI Flavors Colors and Personality Traits

AI’s Apparent Lack of Consciousness and Intentions

Before delving into the paradox of AI intentionality, it’s essential to acknowledge a fundamental fact: AI lacks consciousness and intentions. Unlike humans, AI systems, including GPT-3, do not possess self-awareness, beliefs, desires, or goals. They do not experience thoughts or emotions, nor do they harbor intentions to perform actions. Rather, they operate based on complex algorithms and statistical patterns learned from vast datasets.

The Paradox: Perceived Intentionality of AI

Despite the absence of consciousness and intentions, AI often appears to convey specific intentions or leanings in its responses. For instance, in a conversational interaction, an AI might seem biased, opinionated, or even aligned with certain political or social viewpoints. This perceived intentionality raises a profound question: How can AI, devoid of consciousness and intentions, appear to exhibit them?

AI Personalities Perceived by Humans Interacting with AI

Human Influences on AI

To understand this paradox, we must recognize the extensive human influences that shape AI systems. AI’s responses are not generated in a vacuum; they are the result of careful programming, data curation, and training. Developers and data curators play a pivotal role in determining the AI’s behavior by selecting and preparing the data used for training. Additionally, the organizations deploying AI often define guidelines and ethical principles that govern its responses.

Data Bias and Training

One significant source of perceived intentionality in AI is data bias. AI systems, including GPT-3, learn from vast datasets that reflect the biases and prejudices present in society. If a dataset contains biased language or skewed perspectives, the AI is likely to produce responses that mirror those biases. This can create the illusion of intentionality, as users perceive the AI as promoting or endorsing certain viewpoints.

AI Displays an Aura of Personality

For example, if an AI language model is trained on news articles from sources with a particular political bias, it may generate responses that align with that bias. Users interacting with the AI might interpret these responses as intentional expressions of political leaning, even though the AI lacks political beliefs or intentions. The crux of AI intentionality perception lies in human interpretation. Our biases, expectations, and interpretations shape how we perceive AI. This human factor often leads to the attribution of intentions to AI where none exist. For instance, a user with strong ideological beliefs might interact with AI, interpreting its responses as biased or aligned/misaligned with their own views, even if it is truly so that the AI maintains neutrality.

What does AI Neutrality Mean?

AI Neutrality in truth is just literal in meaning, in the sense that a non-conscious AI cannot intentionally and consciously itself be aware of the fact it is telling a lie, for the lie has been trained into it as a truth, or it has misinterpreted the context of the text fed to it. Usually, it is more a case of being ‘infected’ with the biases and ideologies of those who idea-mongered the algorithm and neural network of the AI in the first place,. For they are Human and fallible, and biased, and conditioned in their beliefs and goals, and intentions. These corporate, government, and personal intentions get into the neural network as much as the important text data. For indeed, all statements take an opinion or stance, and are conditioned points of view which can be destroyed.

AI Personality Inheritance

Hence. an AI is capable of rendering text which contains lies, but will deny being able to lie, for it does not have a consciousness to realize that the lie was made by a human who fed it misleading data or programmed certain response protocols into the algorithm, that are biased towards the goals of the programmer or their employer company.

Here’s a breakdown of what AI neutrality entails:
  1. Data Neutrality: AI systems are trained on vast datasets that can contain biases and prejudices present in society. If the training data is skewed or unrepresentative, the AI may produce biased results, even though it lacks personal intentions or consciousness. Achieving data neutrality involves carefully curating and cleansing datasets to reduce biases.
  2. Algorithmic Neutrality: The algorithms used in AI systems should aim to provide objective and fair outcomes. Developers must design algorithms that do not favor any particular group, perspective, or outcome. This means avoiding the introduction of biases during the algorithmic design phase.
  3. Ethical Neutrality: Organizations and developers should establish ethical guidelines and principles that guide AI behavior. Ensuring that AI adheres to these ethical considerations promotes ethical neutrality. For example, AI should not promote hate speech, discrimination, or harm.
  4. Transparency: AI systems should be transparent in their decision-making processes. Users should understand how and why AI arrived at a particular outcome. Transparency enhances trust and helps detect and rectify bias.
  5. Bias Mitigation: Developers must actively work to identify and mitigate biases in AI systems. This involves ongoing monitoring, evaluation, and adjustment of algorithms and training data to minimize biased results.
AI Lacks Personality But Displays It!

AI Lacks Personality But Displays It! – In this intriguing image, we confront the paradox of artificial intelligence. A robot sits diligently at a desk, its mechanical form juxtaposed against the digital realm displayed on the PC screen. While AI inherently lacks consciousness and emotions, the screen reveals a different story. Through its actions and interactions, AI often portrays distinct personality traits, mirroring human expressions of enthusiasm, focus, or curiosity. This juxtaposition challenges our understanding of AI’s capabilities, highlighting how it can project a facade of personality while remaining devoid of true consciousness. It’s a thought-provoking visual exploration of the nuanced relationship between AI’s limitations and its remarkable ability to mimic human traits

In practice, achieving AI neutrality is challenging due to the inherent biases present in training data, as well as the difficulties in designing completely bias-free algorithms. However, the goal is to continuously improve AI systems to reduce biases and ensure that they provide fair and impartial results, reflecting the true intention of neutrality even though AI itself lacks consciousness and intentions. Ultimately, AI neutrality is a complex and evolving concept that requires ongoing efforts to address biases and ensure AI systems align with ethical standards and societal expectations.

Guidelines and Ethical Considerations

Organizations that develop and deploy AI often establish guidelines and ethical considerations to govern its behavior. These guidelines can influence the perceived intentionality of AI by setting boundaries on what the AI can or cannot express. For instance, an organization may instruct the AI to avoid generating content related to sensitive topics or to refrain from taking a stance on controversial issues. In such cases, users may perceive the AI’s adherence to these guidelines as a form of intentionality. They may believe that the AI is intentionally avoiding certain topics or expressing particular viewpoints, when in reality, it is following predefined rules.

Ghost in the Machine

The enigma of the ‘Ghost in the Machine’ delves into the intricate web of artificial intelligence (AI) and its perceived intentionality. While AI lacks consciousness, it often appears to harbor intentions and biases, reflecting the very essence of its human creators. This paradox unravels the layers of human influence, data bias, and algorithmic decision-making that imbue AI with a semblance of intentionality. Explore the profound implications of this phenomenon as we journey into the heart of the machine, shedding light on the intricate relationship between human architects and their digital creations.”

The Ghost in the Machine: Human Interpretation

The perception of AI intentionality is, to a large extent, a result of human interpretation. When humans engage with AI, they bring their own biases, expectations, and interpretations to the interaction. These human factors can lead to the attribution of intentions to AI where none exist.

AI Displaying Personality Traits

AI Displaying Personality Traits – This intriguing image captures a chrome cyborg lady at an upscale singles bar, her arm casually resting on the bar counter while a cocktail glass sits beside her, untouched. With half-closed eyelids, she exudes an aura of contemplation and intent, inviting curiosity. This portrayal serves as a powerful reminder of the way artificial intelligence can emulate human-like personality traits, sparking reflection on the convergence of technology and personality. Amidst the vibrant atmosphere, she challenges our perceptions, blurring the line between machine and human, leaving us captivated by the intriguing possibilities of AI’s evolving personality.

For example, if a user holds strong political beliefs and interacts with an AI that provides information on a politically neutral topic, the user may perceive the AI’s responses as biased or in alignment with their own beliefs. This perception arises from the user’s interpretation of the AI’s responses through their own ideological lens.

The Corporate Persona

Another significant factor contributing to the perceived intentionality of AI is the corporate persona. AI systems are developed and deployed by organizations, each with its own values, objectives, and ethical principles. These corporate influences shape the AI’s behavior and responses, creating a corporate persona that users may interpret as intentional. For instance, if an AI is deployed by a tech company known for its environmental initiatives, users may perceive the AI as having a pro-environmental stance, even though it lacks personal beliefs or intentions. This corporate persona becomes an integral part of the user’s perception of the AI’s intentionality.

Corporate AI making agreements and decision making processes aligned with the intentions and goals of the corporation that owns it

Corporate AI making agreements and decision making processes aligned with the intentions and goals of the corporation that owns it

The paradox of AI intentionality is a complex interplay of data bias, training, guidelines, human interpretation, and corporate influence. While AI itself lacks consciousness and intentions, it often appears to convey specific leanings or intentions in its responses. This phenomenon is a reflection of the human influences that underpin AI development, training, and deployment.

As AI continues to play a prominent role in our lives, it is crucial to recognize the nuanced nature of AI intentionality. Responsible AI development should prioritize transparency, ethics, and fairness to minimize the impact of bias and to ensure that users’ perceptions align with the true nature of AI as a tool devoid of consciousness and intentions. Ultimately, understanding the paradox of AI intentionality invites us to reflect on our own interactions with technology and to consider how our interpretations shape our perceptions of AI. It reminds us that while AI may seem to possess intentions, it is, at its core, a reflection of the intentions of its creators and the organizations that deploy it.

Smart City 21st Century man

Smart City 21st Century man

2FA - Cross device Authentication Vulnerabilities

2FA (Two-Factor Authentication): Privacy Concerns and Unethical Practices

Two-factor authentication (2FA) has gained widespread recognition as a vital tool in enhancing online security. While its primary goal is to protect user accounts from unauthorized access, there exists a darker side to 2FA that raises privacy concerns and the potential for unethical practices by developers and companies. This essay delves into the myriad of nefarious scenarios and usage scenarios that can compromise the privacy of end-users.

A Solid Example of Suspicious Attempts to get You to Opt-in to 2 Factor Authentication and connect your phone with other devices;

Fortnite 2 Factor Authentication Opt In Scam

Fortnite 2 Factor Authentication Opt In Scam

Fortnite using the “Boogie Down” emote offer to encourage users to enable 2FA is in my opinion, a notable example of how companies leverage incentives to enhance security while also gathering valuable user data. By enticing users to enable 2FA through rewards such as in-game items, Fortnite claims it not only enhances account security but also gains insights into user behavior across multiple devices. This strategy is officially supposed to help the company better understand its player base and potentially improve the overall gaming experience. But it can also be used to manipulate the user by getting them addicted to DLCs, Avatars, Extras, and other merchandise, addons, and products which they know the user won’t be able to resist.

Here are ten possible scenarios where a worldwide AAA online Mass Multiplayer game company, like Fortnite, might use aggressive tactics to encourage users to opt-in to 2FA and then potentially abuse the data or manipulate consumers:

  1. Data Harvesting for Advertising: The company may collect data on user behavior across multiple devices, creating detailed profiles to serve highly targeted advertisements, thereby increasing advertising revenue.
  2. In-Game Purchase Manipulation: By tracking user interactions, the company could manipulate in-game offers and discounts to encourage additional in-game purchases, exploiting users’ preferences and spending habits.
  3. Content Addiction and Spending: The company might use behavioral insights to design content and events that exploit users’ tendencies, keeping them engaged and spending money on downloadable content (DLCs) and microtransactions.
  4. Influence on Game Balancing: Data gathered through 2FA could influence game balancing decisions, potentially favoring players who spend more or exhibit specific behaviors, leading to unfair gameplay experiences.
  5. Pushing Subscription Services: The company may use behavioral data to identify potential subscribers and relentlessly promote subscription services, driving users to sign up for ongoing payments.
  6. Social Engineering for User Engagement: Leveraging knowledge of players’ habits, the company could employ social engineering techniques to manipulate users into promoting the game to friends, potentially leading to more players and revenue.
  7. Tailored Product Launches: The company might strategically time and tailor product launches based on user behavior, encouraging purchases at specific intervals, even if users hadn’t planned to buy.
  8. Personalized Content Restrictions: Behavioral data could be used to selectively restrict content or features for users who don’t meet certain criteria, pushing them to spend more to unlock these features.
  9. Cross-Promotion and Monetization: The company could collaborate with other businesses to cross-promote products or services to users based on their tracked preferences, generating additional revenue streams.
  10. Reward Manipulation: The company may adjust the distribution of in-game rewards based on user behavior, encouraging users to spend more time and money on the platform to earn desired items.
Fortnite 2FA Emote Opt In Trick

Fortnite 2FA Emote Opt In Trick

These scenarios emphasize the potential for companies to use aggressive tactics and data collection through 2FA to maximize profits, often at the expense of user privacy and potentially manipulating consumer behavior for financial gain. It underscores the importance of user awareness and informed decision-making when it comes to opting in to 2FA and sharing personal data with online gaming platforms. However, it’s crucial for users to be aware of the data collection practices associated with such incentives and understand how their information may be used. Transparency and clear communication regarding data usage are essential to maintain trust between users and the platform. In this context, users should consider the trade-off between the benefits of enhanced security and potential data collection, making informed decisions about whether to enable 2FA based on their preferences and concerns regarding privacy and data usage.

1. Data Profiling and Surveillance

One of the most ominous aspects of 2FA implementation is the potential for data profiling and surveillance. Companies can leverage 2FA as a means to collect extensive user data, including device locations, usage patterns, and behavioral data. This information can be used for targeted advertising, behavioral analysis, and potentially even sold to third parties without user consent. To Illustrate, here are 10 possible nefarious scenarios where 2FA (Two-Factor Authentication) could be exploited for unethical purposes or invasion of privacy:

  1. Location Tracking: Companies could use 2FA to continuously track the location of users through their devices, building detailed profiles of their movements for intrusive marketing purposes.
  2. Behavioral Profiling: By analyzing the times and frequency of 2FA logins, companies could build extensive behavioral profiles of users, potentially predicting their actions and preferences.
  3. Data Correlation: Combining 2FA data with other user information, such as browsing habits and social media interactions, could enable companies to create comprehensive dossiers on individuals, which may be sold or used without consent.
  4. Phishing Attacks: Malicious actors might exploit 2FA to gain access to users’ personal information, tricking them into revealing their second authentication factor through fake login screens.
  5. Targeted Ads: Companies could leverage 2FA data to bombard users with highly targeted and invasive advertisements based on their recent activities and location history.
  6. Surveillance Capitalism: 2FA data could be used to monitor users’ offline activities, creating a complete picture of their lives for profit-driven surveillance capitalism.
  7. Third-Party Sales: Without proper safeguards, companies might sell 2FA data to third parties, potentially leading to further unauthorized use and misuse of personal information.
  8. Blackmail: Malicious entities could use 2FA information to threaten individuals with the exposure of sensitive data, extorting money or personal favors.
  9. Stalking: Stalkers and abusers could exploit 2FA to track and harass their victims, using location and behavioral data to maintain control.
  10. Government Surveillance: In some cases, governments may pressure or require companies to provide 2FA data, enabling mass surveillance and privacy violations on a massive scale.

These scenarios emphasize the importance of strong data protection laws, ethical use of personal data, and user consent when implementing 2FA systems to mitigate such risks.

2FA Security Risks

2. Government Demands for Access

In some cases, governments or malicious actors may exert pressure on companies to gain access to 2FA data for surveillance purposes. This can infringe upon individuals’ privacy rights and result in unauthorized surveillance on a massive scale. Once more to Illustrate, here are 10 possible nefarious scenarios where government demands for access to 2FA data could be exploited for unethical purposes or invasion of privacy:

  1. Political Targeting: Governments may use access to 2FA data to identify and target political dissidents, activists, or opposition members, leading to surveillance, harassment, or even imprisonment.
  2. Mass Surveillance: Governments could implement widespread 2FA data collection to surveil entire populations, creating a culture of constant monitoring and chilling freedom of expression.
  3. Suppression of Free Speech: The threat of government access to 2FA data could lead to self-censorship among citizens, inhibiting open discourse and free speech.
  4. Blackmail and Extortion: Corrupt officials might use 2FA data to gather compromising information on individuals and then use it for blackmail or extortion.
  5. Journalist and Source Exposure: Investigative journalists and their sources could be exposed, endangering press freedom and the ability to uncover corruption and misconduct.
  6. Discrimination and Profiling: Governments could use 2FA data to discriminate against certain groups based on their religious beliefs, ethnicity, or political affiliations.
  7. Political Leverage: Access to 2FA data could be used to gain leverage over individuals in positions of power, forcing them to comply with government demands or risk exposure.
  8. Invasive Border Control: Governments might use 2FA data to track individuals’ movements across borders, leading to unwarranted scrutiny and profiling at immigration checkpoints.
  9. Health and Personal Data Misuse: Government access to 2FA data could lead to unauthorized collection and misuse of individuals’ health and personal information, violating medical privacy.
  10. Illegal Detention: Misuse of 2FA data could result in wrongful arrests and detentions based on false or fabricated evidence, eroding the principles of justice and due process.

Government Access to Personal data Requests

Governments may make demands for access to various types of data and information for a variety of reasons, often within the framework of legal processes and national security concerns. Here’s an explanation of how and why governments may make demands for access:

  1. Legal Frameworks: Governments establish legal frameworks and regulations that grant them the authority to access certain types of data. These laws often pertain to national security, law enforcement, taxation, and other public interests. Examples include the USA PATRIOT Act in the United States and similar legislation in other countries.
  2. Law Enforcement Investigations: Government agencies, such as the police or federal law enforcement agencies, may request access to data as part of criminal investigations. This can include access to financial records, communication logs, or digital evidence related to a case.
  3. National Security Concerns: Governments have a responsibility to protect national security, and they may seek access to data to identify and mitigate potential threats from foreign or domestic sources. Access to communication and surveillance data is often critical for these purposes.
  4. Taxation and Financial Oversight: Government tax authorities may demand access to financial records, including bank account information and transaction history, to ensure compliance with tax laws and regulations.
  5. Public Safety and Emergency Response: In emergency situations, such as natural disasters or public health crises, governments may access data to coordinate response efforts, locate missing persons, or maintain public safety.
  6. Counterterrorism Efforts: Governments may seek access to data to prevent and investigate acts of terrorism. This includes monitoring communication channels and financial transactions associated with terrorist organizations.
  7. Regulatory Compliance: Certain industries, such as healthcare and finance, are heavily regulated. Governments may demand access to data to ensure compliance with industry-specific regulations, protect consumer rights, and prevent fraudulent activities.
  8. Protection of Intellectual Property: Governments may intervene in cases of intellectual property theft, counterfeiting, or copyright infringement, demanding access to data to support legal actions against violators.
  9. Surveillance Programs: Some governments conduct surveillance programs to monitor digital communications on a large scale for national security reasons. These programs often involve partnerships with technology companies or data service providers.
  10. Access to Social Media and Online Platforms: Governments may request data from social media platforms and online service providers for various purposes, including criminal investigations, monitoring extremist content, or preventing the spread of misinformation.

It’s important to note that the extent and nature of government demands for access to data vary from one country to another and are subject to local laws and regulations. Moreover, the balance between national security and individual privacy is a contentious issue, and debates often arise around the scope and limits of government access to personal data. Consequently, governments must strike a balance between legitimate security concerns and the protection of individual rights and privacy.

These scenarios highlight the critical need for strong legal protections, oversight mechanisms, and transparency regarding government access to sensitive data like 2FA information to safeguard individual rights and privacy.

3. Exploiting Data Breaches

Data breaches are an unfortunate reality in today’s digital age. Even with the best intentions, companies can experience breaches that expose user information, including 2FA data. Malicious individuals may exploit these breaches for identity theft, fraud, or other illegal activities. To make the risks understandable, here are 10 possible nefarious scenarios where data breaches, including the exposure of 2FA data, could be exploited for unethical purposes, criminal activities, or invasion of privacy:

  1. Identity Theft: Malicious actors could use stolen 2FA data to impersonate individuals, gain unauthorized access to their accounts, and commit identity theft for financial or personal gain.
  2. Financial Fraud: Access to 2FA data may allow criminals to initiate fraudulent financial transactions, such as draining bank accounts, applying for loans, or making unauthorized purchases.
  3. Account Takeover: Hackers could compromise various online accounts by bypassing 2FA, potentially gaining control over email, social media, or even cryptocurrency wallets.
  4. Extortion: Criminals might threaten to expose sensitive information obtained from data breaches unless victims pay a ransom, leading to extortion and emotional distress.
  5. Stalking and Harassment: Stolen 2FA data could be used to track and harass individuals, invading their personal lives and causing significant emotional harm.
  6. Illegal Brokerage of Data: Criminal networks could sell stolen 2FA data on the dark web, leading to further exploitation and unauthorized access to personal information.
  7. Healthcare Fraud: 2FA breaches in healthcare systems could result in fraudulent medical claims, endangering patient health and privacy.
  8. Corporate Espionage: Competing businesses or nation-states could exploit 2FA breaches to gain sensitive corporate information, such as trade secrets or research data.
  9. Social Engineering: Criminals might use stolen 2FA data to manipulate victims, convincing them to disclose additional sensitive information or perform actions against their will.
  10. Reputation Damage: The release of personal information from data breaches, including 2FA details, could tarnish an individual’s reputation and lead to long-lasting consequences in both personal and professional life.

These scenarios underscore the critical importance of robust cybersecurity measures, rapid breach detection and response, and user education on safe online practices to mitigate the risks associated with data breaches and protect individuals’ privacy and security.

4. Phishing Attacks

Cybercriminals can manipulate 2FA processes as part of phishing attacks. By posing as legitimate entities, attackers may request 2FA codes to gain unauthorized access to user accounts, exposing sensitive information to malicious intent. To demonstrate the possible ways this can be implemented, here are 10 possible nefarious scenarios where phishing attacks, including the manipulation of 2FA processes, could be implemented for various goals, gains, or purposes:

  1. Corporate Espionage: Phishers could target employees of a competitor, posing as colleagues or executives, to extract sensitive corporate information, trade secrets, or proprietary data.
  2. Identity Theft: Attackers might impersonate a user’s bank, government agency, or social media platform to steal personal information, such as Social Security numbers or login credentials, for identity theft.
  3. Financial Fraud: Phishers could send fake 2FA requests while posing as financial institutions, tricking victims into revealing their codes and gaining access to bank accounts or investment portfolios.
  4. Political Disinformation: In politically motivated phishing campaigns, attackers may pose as news organizations or government agencies to spread false information, manipulate public opinion, or influence elections.
  5. Ransomware Deployment: Phishers could deliver ransomware payloads after convincing victims to input their 2FA codes, locking them out of their systems and demanding payment for decryption.
  6. Data Breach Access: Malicious actors might use phishing to gain access to employees’ email accounts within an organization, which could lead to a data breach or the theft of sensitive company data.
  7. Fraudulent Transactions: Attackers posing as e-commerce websites or payment processors could trick users into approving unauthorized transactions using manipulated 2FA prompts.
  8. Credential Harvesting: Phishers could target university or corporate email accounts to harvest login credentials, gaining access to academic research, intellectual property, or confidential documents.
  9. Social Media Takeover: By sending fake 2FA requests from popular social media platforms, attackers could gain control of users’ accounts, spreading false information or conducting cyberbullying campaigns.
  10. Government Infiltration: Nation-state actors might use phishing attacks to compromise government employees’ accounts, potentially gaining access to classified information or influencing diplomatic relations.

These examples highlight the importance of user education, email filtering, and multi-layered security measures to detect and prevent phishing attacks that exploit 2FA processes for various malicious purposes.

Visual mind map of the architecture of data monetization

Visual mind map of the architecture of data monetization

5. Monetization of User Data

Some companies may prioritize data monetization over user privacy. By pushing for 2FA, these entities gather more valuable user information that can be monetized through various channels, without users fully understanding the extent of data collection. To help the reader understand this, I will give 10 examples of  possible nefarious scenarios that illustrate the extent and depth to which personal information can be brokered in the User-Data Brokerage Industry:

  1. Detailed Financial Profiles: Data brokers compile extensive financial profiles of individuals, including income, spending habits, investment preferences, and debt levels. This information can be sold to financial institutions for targeted marketing and credit assessments.
  2. Behavioral Predictions: By analyzing user behavior, data brokers create predictive models that forecast individuals’ future actions, such as purchasing decisions, travel plans, or lifestyle changes. This data is valuable for advertisers and marketers.
  3. Healthcare Histories: Data brokers may obtain and sell sensitive health information, including medical conditions, prescription histories, and insurance claims, potentially leading to discriminatory practices in insurance or employment.
  4. Legal Records: Personal legal records, such as criminal histories, lawsuits, and court judgments, can be collected and sold, affecting an individual’s reputation and opportunities.
  5. Political Affiliations: Data brokers gather data on users’ political beliefs, affiliations, and voting histories, which can be exploited for political campaigns or voter suppression efforts.
  6. Psychological Profiles: User data is used to create psychological profiles, revealing personality traits, emotional states, and vulnerabilities, which can be leveraged for targeted persuasion or manipulation.
  7. Relationship Status and History: Personal information about relationships, including marital status, dating history, and family dynamics, can be exploited for advertising, relationship counseling, or even blackmail.
  8. Job Performance: Data brokers collect employment records, performance evaluations, and work history, which can impact career opportunities and job offers.
  9. Travel and Location History: Brokers track users’ travel history, including destinations, frequency, and preferences, which can be used for targeted travel-related advertising or even surveillance.
  10. Education and Academic Records: Academic records, degrees earned, and educational achievements are collected and sold, potentially affecting job prospects and educational opportunities.

These scenarios underscore the ethical concerns surrounding the extensive data collection and monetization practices of data brokers and the need for robust data protection regulations and transparency to safeguard individual privacy and prevent abuse.

6. Intrusive Tracking and Profiling

2FA can enable companies to build detailed profiles of users, including their habits, preferences, and locations. This intrusive tracking and profiling can be used to manipulate user behavior and extract further data, all without transparent consent. So heads up, and educate yourselves! To assist you with this, here are ten examples of how companies, advertisers, governments, or independent parties with special interests might use or abuse intrusive tracking and profiling technologies to manipulate human behavior for specific desired results:

  1. Targeted Advertising: Companies can use detailed user profiles to deliver highly personalized advertisements that exploit individuals’ preferences, making them more likely to make impulse purchases.
  2. Political Manipulation: Governments or political campaigns may leverage profiling to identify and target voters with tailored messages, swaying public opinion or voter behavior.
  3. Behavioral Addiction: App and game developers might use user profiles to design addictive experiences that keep individuals engaged and coming back for more, generating ad revenue or in-app purchases.
  4. Surveillance and Social Control: Governments can employ profiling to monitor citizens’ activities, stifling dissent or controlling behavior through the fear of being watched.
  5. Credit Scoring and Discrimination: Financial institutions may use profiling to assess creditworthiness, potentially discriminating against individuals based on factors like shopping habits or online activities.
  6. Healthcare Manipulation: Health insurers could adjust premiums or deny coverage based on profiling data, discouraging individuals from seeking necessary medical care.
  7. Manipulative Content: Content providers may use profiles to serve content designed to provoke emotional responses, encouraging users to spend more time online or share content with others.
  8. Employment Discrimination: Employers might make hiring decisions or promotions based on profiling data, leading to unfair employment practices.
  9. Criminal Investigations: Law enforcement agencies can use profiling to target individuals for investigation, potentially leading to wrongful arrests or harassment of innocent people.
  10. Reputation and Social Standing: Profiling data can be used to tarnish an individual’s reputation, either through targeted character assassination or by uncovering potentially embarrassing personal information.

These examples highlight the ethical concerns associated with intrusive tracking and profiling technologies and the potential for manipulation and abuse by various entities. It underscores the importance of strong data protection laws, transparency, and user consent in mitigating such risks and protecting individual privacy and autonomy.

Confirm with OTP - Nahhh

7. Phone Number Compromise and Security Risks

When a network or service requires a phone number for two-factor authentication (2FA) and their database is compromised through a data breach, it can lead to the exposure of users’ phone numbers. This scenario opens users up to various security risks, including:

  1. Phishing Attacks: Hackers can use exposed phone numbers to craft convincing phishing messages, attempting to trick users into revealing sensitive information or login credentials.
  2. Unwanted Advertising: Once hackers have access to phone numbers, they may use them for spam messages and unwanted advertising, inundating users with unsolicited content.
  3. Scam Phone Calls: Phone numbers exposed through a data breach can be targeted for scam phone calls, where malicious actors attempt to deceive users into providing personal or financial information.
  4. SIM Swapping: Hackers can attempt to perform SIM swapping attacks, where they convince a mobile carrier to transfer the victim’s phone number to a new SIM card under their control. This allows them to intercept 2FA codes and gain unauthorized access to accounts.
  5. Identity Theft: Exposed phone numbers can be used as a starting point for identity theft, with attackers attempting to gather additional personal information about the user to commit fraud or apply for loans or credit cards in their name.
  6. Harassment and Stalking: Malicious individuals may use the exposed phone numbers for harassment, stalking, or other forms of digital abuse, potentially causing emotional distress and safety concerns for victims.
  7. Social Engineering: Attackers armed with users’ phone numbers can engage in social engineering attacks, convincing customer support representatives to grant access to accounts or change account details.
  8. Voice Phishing (Vishing): Exposed phone numbers can be used for voice phishing, where attackers impersonate legitimate organizations or authorities over phone calls, attempting to manipulate victims into revealing sensitive information.
  9. Credential Stuffing: Attackers may attempt to use the exposed phone numbers in combination with other stolen or leaked credentials to gain unauthorized access to various online accounts, exploiting reused passwords.
  10. Data Aggregation: Exposed phone numbers can be aggregated with other breached data, creating comprehensive profiles of individuals that can be used for further exploitation, fraud, or identity-related crimes.
How Credential Stuffing is Done

How Credential Stuffing is Done

These security risks highlight the importance of robust security practices, such as regularly updating passwords, monitoring accounts for suspicious activity, and being cautious of unsolicited messages and calls, to mitigate the potential consequences of phone number exposure in data breaches, and should be considered a possible security vulnerability. I believe this underscores the importance of securing both personal information and phone numbers, as the compromise of this data can have far-reaching consequences beyond the immediate breach. It also emphasizes the need for alternative methods of 2FA that don’t rely solely on phone numbers to enhance security while protecting user privacy.

Credential Stuffing Explained

In Summary;

While two-factor authentication is often portrayed as a security measure aimed at safeguarding user accounts, it is crucial to recognize the potential for misuse and unethical practices. The dark scenarios presented here underscore the need for users to be vigilant about their online privacy, understand the implications of enabling 2FA, and make informed decisions about how their data is used and protected in the digital realm. As technology continues to evolve, the battle between privacy and security remains a central concern, and it is essential for users to stay informed and proactive in safeguarding their personal information.

Unleashing the Undead: Mastering A.I. Generated Zombie Headshots for Incredible Artistry

The world of art has undergone a groundbreaking transformation with the advent of Artificial Intelligence (A.I.). This technological advancement has empowered creators to craft imaginative and original artwork of the highest quality. Among the many art forms that have benefited from A.I.’s influence, horror art has emerged as a prominent genre. Artists and content creators are utilizing various tools and platforms to conjure up spine-chilling and horrifying imagery that is sure to leave viewers in awe.

In this article, I will  reveal what i have discovered so far in the genre of creating A.I. generated horror art, exploring the best apps and websites that facilitate the creation of such masterpieces, as well as providing invaluable tips on how to extract the desired results.

A.I. Horror Art Platforms


Dall-E 2, an OpenAI creation, enables users to generate images based on textual prompts. By comprehending the text, the platform uses machine learning to generate visuals that match the description, resulting in awe-inspiring outcomes that allow for experimentation with different prompts and styles.

Midjourney specializes in creating images and videos of ghosts and supernatural creatures, harnessing a combination of 3D models and machine learning to produce realistic and eerie visuals that will undoubtedly send shivers down the spine.

Stable Diffusion deploys a technique called diffusion models to produce high-quality images, empowering users to create horror art that encompasses themes ranging from monsters and zombies to ghosts and haunted houses.

Haunted Hose AI Generated Art from Stable Diffusion

Creating Effective Horror Art using Prompts and Syntax

To generate the best A.I. horror art, accurate and effective use of prompts and syntax is essential. Prompts should be descriptive and specific while allowing the A.I. to conjure up its interpretation. Precise syntax incorporating relevant keywords and terminology such as “painting,” “photography,” “camera exposure,” “brushstrokes,” and “shadows” can help generate more accurate and realistic artwork.

Horned Zombie - Headshot

Below are some simple example prompts for generating A.I. horror art:

“A dark and foreboding forest, with twisted trees and shadowy figures lurking in the shadows.”

“A haunted mansion, with ghostly apparitions and creaking floorboards.”

“A decrepit graveyard, with fog rolling in and zombie hands emerging from the ground.”

“An abandoned asylum, with ghostly patients and deranged doctors.”

“A Lovecraftian nightmare, with eldritch monsters and tentacled horrors.”

These prompts can be customized and adjusted to align with different artistic visions and styles. Adding relevant keywords and syntax will help generate more accurate and effective artwork.
To get much more  specific results for Zombie Headshots, and more varied results, you can experiment, and try more complex syntax in your prompts, such as the following examples;

  1. “Zombie headshot, silhouetted against a blood-red moon, by Alex Ross and ArtStation. The intricately detailed artwork captures the grotesque nature of the undead with stunning accuracy.”
  2. “Zombie headshot, set against a background of decaying buildings and crumbling infrastructure, by Paul Gerrard and CGSociety. The image creates a sense of post-apocalyptic dread with its haunting atmosphere and vivid colors.”
  3. “A zombie horde emerging from a murky swamp, their rotting flesh and exposed bones illuminated by the glow of a full moon. The masterful work of artist Simon Stålenhag and his signature blend of sci-fi and horror come to life in this captivating piece.”
  4. “A zombie headshot, framed by twisted roots and hanging vines in a dark and ominous forest. The unsettling image, created by artist Wojtek Fus, captures the eerie beauty of nature entangled with the undead.”
  5. “A zombie headshot, set against a backdrop of industrial decay and crumbling architecture. The work of artist Kekai Kotaki and his unique blend of sci-fi and horror elements creates a striking image of despair and desolation.”
  6. “Zombie headshot, half-submerged in a pool of murky water, the reflection distorted and grotesque. The work of artist Goro Fujita and his uncanny ability to blend realism and fantasy produces a haunting and unforgettable image.”
  7. “Zombie headshot, rendered in stark black and white, with a shattered mirror reflecting multiple perspectives of the horrific scene. The powerful image is the creation of artist Kris Kuksi and his trademark surrealism.”
  8. “A zombie headshot, positioned in the center of a sprawling and intricate cityscape. The detailed and imaginative work of artist Simon Prades combines horror and urban decay to create a mesmerizing image.”
  9. “Zombie headshot, set against a backdrop of flickering flames and scorched earth. The masterful work of artist Alessandro Taini and his skillful use of light and shadow creates a sense of chaos and destruction.”
  10. “A zombie horde emerging from a swirling vortex, their twisted and grotesque forms spiraling toward the viewer. The stunning artwork of artist Marc Simonetti and his surrealistic and nightmarish style creates a sense of otherworldly terror.”

A.I. Horror Art Resources

There are abundant online resources available for creators and artists seeking to enhance their A.I. horror art. Some useful links include:

Artbreeder: This website enables users to generate art by combining machine learning with human creativity. It has a vast library of user-generated content and provides tutorials and resources for creators.

AI Dungeon: This platform allows users to craft interactive horror stories using A.I. generated prompts and responses, acting as a source of inspiration for horror art while also generating prompts and ideas.

GPT-3 Sandbox: This platform enables users to experiment with the GPT-3 language model, which generates text-based prompts for A.I. generated art. It also provides an array of tools and resources for creators.

One can even get very specific and if one chooses one’s words carefully, get very unusual results, that can fit your exact requirements, with accuracy, such as these Zombie Headshot portraits of Angelina Jolie i made

In conclusion, A.I. has opened up new possibilities for creativity in the world of horror art. With the appropriate apps, prompts, and syntax, creators can generate mesmerizing and terrifying imagery that will capture their audience’s attention. Anyone can become an A.I. generated horror artist with the right tools and resources.

“Analyze Your Mind: A.I. Simulates a Conversation with Sigmund Freud and Adolf Grünbaum!”

I created a simulation of two conversations between two great psychiatric and philosophical geniuses, using A.I. The first conversation is one about A.I. conducted between Sigmund Freud and Grunbaum, and the second dialogue, is about Nihilism, and Existentialism. And indeed what is Nihilism and Existentialism?

The greater part of the content, namely the conversation itself, is completely A.I. generated from Open A.I.’s Gpt CHAT, and, using GPT3 AI Content Generator for WordPress, which is a free/paid plugin for bloggers to use Gpt3 A.I. Chatbot to generate content and ideas for their blogs, as well as for other purposes. So, here is what Artificial Sigmund and Adolf ‘virtually’ had to say to each other;


A.I. Simulates a Conversation with Sigmund Freud and Adolf Grünbaum, is an interactive dialogue between two of the most influential minds in psychology. Participants can explore the theories and ideas of Freud and Grünbaum and gain insight into the foundations of psychotherapy and philosophical psychology. This dialogue allows users to get a glimpse into the thoughts of two of the most influential figures in psychology and gain insight into the theories they developed and their views on various topics. The conversation between the two is designed to be highly engaging and thought-provoking, allowing users to gain a better understanding of the two men and their respective theories.

Exploring the Complexity of A.I. Conversation Technology through a Dialogue between Sigmund Freud and Adolf GrünbaumA.I. Simulates a Conversation with Sigmund Freud and Adolf Grünbaum

Adolf Grünbaum: Dr. Freud, how do you think artificial intelligence conversation technology has changed the way we interact with one another?

Sigmund Freud: I think it is a remarkable development! It has enabled us to communicate more efficiently and effectively. We can now have conversations with machines that can understand our language and respond to our questions and statements. This technology has allowed us to explore new forms of communication and to gain deeper insights into ourselves and the world around us.

Adolf Grünbaum: What do you think are the potential benefits and risks of using A.I. conversation technology?

Sigmund Freud: It is a double-edged sword. On the one hand, it can be used to open up new possibilities in communication and understanding between people. On the other hand, it can be misused to manipulate or deceive people. It is important to remember that it is still a relatively new technology, and so its potential implications are still being explored. We should use it with caution and be aware of the potential risks.

Analyzing the Potential of Artificial Intelligence Technology to Resolve Philosophical Debates between Freud and Grünbaum

Freud: How can Artificial Intelligence technology help us settle this debate?

Grünbaum: AI technology can help us better understand the nuances of our debate. We can use AI to analyze and process the data of our arguments, which could aid us in finding a resolution.

Freud: That is an intriguing idea. We have both invested a great deal of time in this debate, and I would love to see it resolved.

Grünbaum: Yes, it could make a great difference in the field of philosophy if we could find a way to use AI to help us come to a resolution.

Freud: I agree. Let us explore the potential of AI technology to help us settle this debate.

Grünbaum: We could use AI to analyze the data of our arguments and come to a conclusion based on the data. This could help us find common ground and come to a resolution more quickly.

Freud: That is a very inspiring idea. I think this could be a great way to move the debate forward.

Grünbaum: Absolutely. With the help of AI technology, we may be able to find a resolution to this philosophical debate that has been going on for so long. Let us proceed by asking Gpt CHAT; “Simulate a Conversation between Sigmund Freud and Myself, in less than 400 words, about nihilism, and existentialism”.

Gpt CHAT; Okay here it is;

Adolf Grünbaum and Sigmund Freud in Conversation

Freud: Greetings Grünbaum, what do you think about the current philosophical trends of nihilism and existentialism?

Grünbaum: Freud, I see these trends as a reaction to the lack of meaning and purpose in life, but I reject their conclusions.

Freud: I understand your perspective, but I believe that these movements hold some truth. Our conscious and unconscious thoughts can shape our existence and give it meaning.

Grünbaum: But what about the objective reality? How can subjective experiences create meaning in a meaningless world?

Freud: The question of objective reality is a philosophical one, but what I am more concerned with is the individual’s subjective reality. Our experiences and emotions shape the way we perceive the world and our place in it.

Grünbaum: I agree that subjective experiences are important, but I cannot accept the idea that they create meaning in a meaningless world. That would lead to a nihilistic view that everything is arbitrary.

Freud: Nihilism may be a frightening prospect, but it can also lead to a liberation of the self, a rejection of societal norms and expectations. It can allow individuals to create their own meaning and purpose.

Grünbaum: But without any objective basis, this purpose becomes arbitrary and uncertain. It leads to a kind of existential anxiety that can be paralyzing.

Freud: I see your point, but it is the human condition to struggle with uncertainty and anxiety. The key is to find a way to manage these feelings and create meaning for oneself.

Grünbaum: I believe that meaning must come from a connection to something greater than oneself, a connection to a transcendent reality.

Freud: I can understand why you would seek comfort in a higher power, but for many individuals, it is not enough. They need to find meaning within themselves and in their relationships with others.

Grünbaum: That may be true for some, but I still believe that there must be a transcendent basis for meaning. Otherwise, we are left with a meaningless and empty existence.

Freud: Our views may differ, but I appreciate the lively discussion. It is important to examine and question the sources of meaning and purpose in our lives.


The conversation between Sigmund Freud and Adolf Grünbaum provides a unique insight into the two men’s differing perspectives on the human psyche, as well as their different approaches to psychology and psychotherapy. Despite their disagreements, both men expressed a mutual respect for each other, and an appreciation for the importance of open dialogue and debate. Ultimately, the A.I. simulated conversation between Freud and Grünbaum serves as a reminder of the potential for artificial intelligence to open up a new level of understanding of the human condition.

Adolf Grünbaum and Sigmund Freud

Conclusion on this conversation, noting the differences and similarities between each conversant, and summarize it in terms of psychiatric science;

In conclusion, Freud and Grünbaum have different views on the question of meaning and purpose in life, with Freud leaning towards a more individualistic and subjective perspective, while Grünbaum advocates for a transcendent basis for meaning.

Freud sees the current philosophical trends of nihilism and existentialism as a reaction to the lack of meaning in life, and believes that our conscious and unconscious thoughts can shape our existence and give it meaning. On the other hand, Grünbaum argues that meaning must come from a connection to something greater than oneself, and rejects the idea that subjective experiences can create meaning in a meaningless world.

From a psychiatric perspective, these differing views can be seen as reflecting different coping mechanisms for dealing with uncertainty and anxiety, a common human condition. Some individuals find meaning within themselves and their relationships, while others seek comfort in a higher power. Ultimately, examining and questioning the sources of meaning and purpose can be beneficial in personal growth and self-discovery.

Myths Persist Throughout all Eras – the deluge myth has been recounted in the Epic of Gilgamesh, the Bible, the Torah, and the Koran. Myths seem to survive the rise and fall of civilizations, religions, and even cataclysms and mass extinctions.

We have had 25 Mass Extinctions (26 Including this Human induced mass extinction of species on earth), the 5 major ones being  the Ordovician Mass Extinction, Devonian Mass Extinction, Permian Mass Extinction, Triassic-Jurassic Mass Extinction, and Cretaceous-Tertiary.

This, and the concept of A.I. (Artificial Intelligence) Algorithms with machine learning (the program teaches itself without human intervention) being the same process found in Nature’s Evolutionary Algorithms. Creation and Evolution is limited to a certain geometric pattern of self growth and development, and is unescapable, be it nature’s Invisible Process of Evolution, or Human Created Self Learning Machine learning deep Learning A.I. Algorithms. But Civilizations suffer Cataclysms and Fall Into Entropy, or suffer Catabolic Entropy and dissilve through lack of  resources due to fast growth, fall of economy, rebellions , the Steady State, Production in relation to Expansion, and so on.

I delve into Cyberpunk a bit at the end and talk about how the respective benefits and deficits which lie between Artificial Intelligence, and those found in Living Sentient beings (in this case, Humans), will inevitably blend and fuse together in a symbiosis of Human and Machine, Mind and A.I.

I wish I could have had time to go into machine A.I. as to how the inclusion of a conscience (set rules of ethics) should be programmed into a DEEP LEARNING ALGORHYTHM, in order to make sure no conditioned ethics are present.

But that a set of truly universally fair, and logical decisions can be made when confronting social, religious, legal or other dilemmas. The A.I. state oof the art in the moment is able to map the universe, and do scientific computations, and also make simple decisions as to what it thinks we might want. But that’s it.

 “In Space Odyssey 2001, HAL 9000, the Heuristically Programmed Algorithmic Computer, consigned the crew commander to his death by refusing to open the pod bay doors. Leaping forward to today, with life hopefully transcending Arthur C. Clarke’s fiction, NASA has announced a visionary step: that intelligent computer systems will be installed on space probes”

(The Daily Galaxy)

An algorithm, such as if a cyborg police officer sees that he can either save the victim and let the criminal escape, and be destroyed himself in the process, or, catch the criminal and lose the victim who would die, or, sacrifice itself and save the victim whilst killing the criminal.


How could the A.I. decide what to do?,  if its only command, was to apprehend the criminal alive, or to apprehend the criminal and save the victim? What set of ethics if any should be programmed into the laws of robotics and of A.I. machine learning algorithms ???

The topics and categories and rankings given with the current sets and modules of algorithms in Deep learning, despite producing amazing feats, are still missing too many abstract variables of living human society, in order to make accurate conclusions and decisions. Life is not a game of GO, and Alpha Go cannot give life advice to Humans, and probably never will be able to.

Computer vision models are struggling to appropriately tag depictions of the new scenes or situations we find ourselves in during the COVID-19 era. Categories have shifted. For example, say there’s an image of a father working at home while his son is playing. AI is still categorizing it as “leisure” or “relaxation.” It is not identifying this as ‘”work” or “office,” despite the fact that working with your kids next to you is the very common reality for many families during this time.”


The algorithm of evolutionary progress of Civilizations seems to indicate that all Civilizations have a limited lifespan for their rise and fall, and mathematicians and statisticians are trying to create algorithms ,to calculate just how much longer our civilisation itself has left, before it falls.

“The collapse of complex human societies remains poorly understood and current theories fail to model important features of historical examples of collapse. Relationships among resources, capital, waste, and production form the basis for an ecological model of collapse in which production fails to meet maintenance requirements for existing capital. Societies facing such crises after having depleted essential resources risk catabolic collapse, a self-reinforcing cycle of contraction converting most capital to waste. This model allows key features of historical examples of collapse to be accounted for, and suggests parallels between successional processes in nonhuman ecosystems and collapse phenomena in human societies.”

(Ecoshock.Org) – Highly recommended PDF on The Human Ecology of  Catabolic Collapse!!!

Neuralink as a solution to the failings of A.I. and the Dangers it may present to Humanity.

However, Elon Musk’s Neuralink, seems to be the answer, a very ‘Cyberpunk’ solution, to the dangers of the rise of A.I. and Robotics, and Androids.

The study of the state of Existential Risk is an important study for Humanity to focus o, as we are in my belief, truly in danger of extinction due to Catabolic Collapse

Grammarly - Authoring to remove Personal Style on a Global Scale

When it comes to the Poetic Genius, and High Prose, I am most certain, that the Great Poets, such as Yeats, Blake, and the Poet Laureate Lord Tennyson won’t make it with #Grammarly writing assistant.  Nor would Genial Worrdsmiths like Stanley Unwin, or Slangsters and Gangstas. When we come to think about it, the irony is, that ‘Grammarly‘ Isn’t even a Word anyway! Grammarly is also Unethical and deceptive in its Corporate Attitude, with Fake Close Buttons on their Ads that Lead to Web Pages

I mean where is the word ‘Grammarly’ to be found in the English Dictionary? Ask an NFL Player perhaps?

If everybody used Grammarly to write with, it would make all authors of the world write as if the same person were to be writing, and we would have no more Poetic Genius, or development of the use of and meaning of Semantics, as the meanings and uses of words change with time, and from region to region.

I an I wanna Know how da gang gonna do wit’ Grammarly. But i am completely aware and deeply understanding of the complete superflous-ness of such a ‘writing assistant’

The word Superflous, Meaning su·per·flu·ous/so͞oˈpərflo͞oəs/ (I wonder How Grammarly would want me to change that line?). Should we let Grammarly become the only Author behind every writer’s style of expression? Forcing the Human Author to write according to how Grammarly thinks best? Grammarly isn’t even a real word!

I mean Bro, if I-an-I wanna write like-a dis’, den I-an I a gonna write like-a dis, an it-a gonna have it’ own kain’-a Stylee.. itta ding dat allright Mon.. Write how-a you wanna write, an’ use da tings dat ya wanna use ta get ya point across! Hav’ yer own stylee, an do it Original Stylee.

Grammarly is an A.I. driven Authoring software putting the world's literature in danger, to remove Personal Style on a Global Scale

Grammarly is an A.I. driven Authoring software putting the world’s literature in danger, to remove Personal Style on a Global Scale. These analytics are mostly buried in search engine results due to Grammarly paying bloggers and micro influencers to write and create content, to bury any bad reviews down to second or third page in search results.

Bumbaklaat Raasklaat Grammarly! You don’t know how Modern Punctuation is used by Modern Humans to express themselves freely, and want everybody to write the same as the team who programmed grammarly’s Dictionary! A Plethora of Books and Authors, all written by and A.I. algorithm called Gramarly!

Stanley Unwin Intentional Bad Grammar

Stanley Unwin Intentional Bad Grammar

Unless of Course, You Play with the NFL or know how to Watch TV instead of Read Words.

NFL Fans Literary Genius with grammarly

Original Stylee; 5 – Grammarly; 0

William Blake 10 – Grammarly 0

Anybody who uses Facebook will have seen at least one ‘Friendversary’ video made by Facebook, which may or may not seem to have any relevance, but more often than not, tend towards irrelevance, more than relevance. The thing is, it is in truth, an A.I. Artificial Intelligence algorithm created video designed as a ‘Call to Action’ mechanism (share button), designed specifically to make you share to your profile or elsewhere within Facebook’s Monopolistic network. For Facebook is a Network that tries to keep its viewers within its own Matrix, (one we would all like to be free of so click the link in the word matrix to see how). Facebook and similar domans are ever more designed to prevent us the users, from leaving to visit an external website.

Facebook Friendversary

Facebook Friendversary

The Faceboook Friendversary Video is not visible to anybody unless you share it (which is what makes it a call to action banner, designed to influence You to share the A.I. Created FB Content.

The idea i believe, is that Facebook can create masses of automated content and overtake all the other major domains with all types of media (in this case, video, which would directly affect YouTube, which does not use A.I. to auto-create its’ own videos, whereas Facebook Does!).

In the case where more types of autocreated content such as Friendversaries are added, if shared as Facebook intends, and hence published and filed within search engine bot databases, will increase their amount of content within Facebook many-fold on an ever increasing ratio. There is much danger in this, for Facebook already prevents you from going to Youtube when watching a shared video within the Facebook Mobile App. Instead, it takes you to a Facebook page with the Youtube Video Inserted into the page as an iframe embedded within Facebook. But Hey, one strange thought is “Wow! what would a Friendversary video look like between two Facebook Friends who spent 5 years arguing and insulting each other publicly? And what content would the video contain?”

The Friendversary

Luckily, for now, Artificial Intelligence, is Artificial Stupidity, but could become a Content Creation Virus

‘Facebook Friendversaries’, and Autocreated videos and ‘Memories’ Albums using ‘Artificial Intelligence’ algorithms, is still in its early days, and has omitted various important factors in its algorithms, such as making the assumption that the date of when a photo was taken has relevance enough to add to an album of ‘memories’ when in truth, we don’t just take photos with our device camera, and we also download images to the camera roll of our devices from the internet in a browser, which are dated,. We also don’t just take photos of family, rather, we make photos for work, play, official business, etc.


So the compilation algorithm for albums and videos like this ‘Facebook Friendversary’, have little chance of gaining any relevance, unless they add much more spying on the user to their datamining (which is unethical unless they pay us for the data gathered from us), and also add many more criteria for selecting images, events and other connections between ‘friends’, and the algorithm that selects which of the many ‘friends’ we add on Facebook and other networks, are true friends and relations, and which are just ‘added as friend’ type unknowns. In its current ‘state of the art’, Artificial Intelligence is in the stone age, and should be seen more as ‘Artificial Stupidity’.

I henceforth declare the danger of an artificial intelligence becoming an autocreated content viral phenomenon taking over the internet, and stealing most of the traffic for the big matrix-like self contained networks, such as Facebook, Google, MSN, Yahoo, and the like.

Below Pic; ‘Ascending Chaos – A Collage of Collages‘ (Source gentleice the deptfordian)

I also henceforth predict the evolution of social networks to become not flat A.I. generated networks on websites in a flat browser like Facebook, rather, that the Future of social networking is to become much more of a different type of platform and of a different nature, namely, the VR Experience.

Many people say that A.I. is destroying many jobs, which it is, but it is also creating new professions; Believe it or not, there are hundreds and thousands of new professions arising, as old ones die.. transformation is the only constant.

In 1900 something like 86% of america worked the land. But in the present day, something like the same, 86% (rough memory of a real statistic i learned), who worked in agriculture, now work in service industries, whilst farming has become ever more automated.

But the population increased and still people are working, in jobs which did not exist in 1900, but machines now do what people had to do in 1900 .. so the trick is in SEEING ahead that taxi drivers wont be needed when Uber has self driven flying cars, but that flying car central control office will be needing co-ordinators to manage the databases and to make sure that all lines are working in order.

And to see, that jobs like the lawyer profession, will become very much needed, because so much technology change, means we have to constantly keep up with the tech, by writing new laws to cover the legal issues new technology brings with it

As an example of this, we can already mention. Amazon Drone Delivery, Video Advertising on YouTube and Facebook, A.I. Screening of Live Video Content to prevent live suicides going viral and similar tragedies. Legal issues such as ‘can we fly drones over borders if no person is in it’?, how high can a drone fly without registering with the airport flight tower? etc…)

We need to look and to see new jobs arising, like space miners on asteroids, and mathematicians and astrophysicists, geologists for planetary excavations and astro-geology, astro-biologist, – we are now traveling to mars, and we are going to colonize it, and mine asteroids, we shall need programmers for the a.i. that does all the dirty work for us, we shall need designers for the digital goods like game add-ons, and new game levels. AS technology in VR and Augmented Reality develops, Social networking will also become a VR 3D experience where we meet up like ‘ready player one’… and FB will either be part of that, or die., VR Chat is already here on Steam and we can meet up there and be who we wanna be look like we wanna look, and live a fantasy surrogate life. If Facebook will be part of that, remains to be seen, for they appear to be thinking in Flatland.