How is AI putting humans progress at sleep

People get lazy and they move their brain less and less, generally, and espacially, since spreading of IT solutions, progressively, step by step: TV, computer, cell phone, AI.

How can AI negative effects be prevented?

AI can make tasks so convenient that it risks diminishing critical thinking and problem-solving skills, especially in young people. Preventing this requires a balance between leveraging AI’s capabilities and fostering human intellectual development. Here are some strategies to mitigate this risk:

1. Promote Active Engagement with AI

• AI as a Tool, Not a Crutch: Teach children and young people to use AI as a support system for learning rather than a substitute for thinking.

• Example: Encourage using AI for brainstorming ideas but require them to critically evaluate and refine those ideas themselves.

• Explain AI’s Functioning: Introduce them to how AI works, fostering curiosity and understanding rather than blind reliance.

2. Emphasize Problem-Solving and Critical Thinking

• Focus on “Why” and “How”: Schools and parents should emphasize understanding the reasoning behind AI-generated outputs.

• Example: If a student uses AI to solve a math problem, ask them to explain the steps or validate the answer themselves.

• Scenario-Based Learning: Present real-world problems that require creativity, logic, and reasoning—skills that go beyond what AI can provide.

3. Foster Creativity and Curiosity

• Creative Assignments: Encourage activities that AI can’t fully replicate, like artistic expression, storytelling, or personal reflection.

• Example: Let students write essays or create art with minimal AI involvement, focusing on original thought and expression.

• Hands-On Learning: Promote experiences that stimulate curiosity, such as science experiments, debates, or group projects.

4. Set Boundaries on AI Use

• AI-Free Zones: Establish spaces or times where AI is not allowed, encouraging children to rely on their own skills.

• Example: No AI assistance during family discussions, certain school assignments, or creative tasks.

• Limit Screen Time: Ensure that excessive reliance on AI doesn’t replace activities like reading, outdoor play, or face-to-face interactions.

5. Equip Teachers and Parents

• AI Literacy: Train educators and parents to understand AI and guide children on when and how to use it responsibly.

• Role Models: Demonstrate intellectual curiosity and problem-solving in daily life, showing that thinking critically is rewarding.

6. Build Resilience and Adaptability

• Gamify Learning: Use games and challenges to develop problem-solving and analytical thinking skills without direct AI intervention.

• Adapt to the AI World: Teach skills that complement AI, such as evaluating sources, ethical reasoning, and understanding biases in data and algorithms.

7. Encourage Social and Emotional Intelligence

• Collaboration over Automation: Promote group activities where interpersonal skills are necessary.

• Example: Organize debates, collaborative projects, or volunteering opportunities that require teamwork and empathy.

• AI in Moderation: Teach children to balance technology with human interaction, emphasizing that AI cannot replicate relationships or emotions.

8. Shift Education Focus

• Lifelong Learning: Focus education on adaptability and the ability to learn continuously, as AI will likely change career demands.

• AI-Era Skills: Develop skills in ethics, creativity, strategy, and problem-framing—areas where humans still excel compared to AI.

9. Develop Ethical AI Awareness

• Teach Ethics of AI: Help children understand the ethical implications of AI, such as bias, privacy, and over-dependence.

• Responsibility for AI Use: Encourage children to question and reflect on how they use AI and the potential impact on themselves and others.

10. Create Opportunities for Self-Reliance

• Manual Activities: Encourage activities like cooking, crafting, gardening, or sports to develop independence and practical skills.

• Real-World Problem-Solving: Provide challenges that require resourcefulness, such as planning trips, solving puzzles, or building something tangible.

Key Takeaway

The goal is not to reject AI but to integrate it responsibly, ensuring young people develop intellectual and emotional skills that AI cannot replace. By fostering critical thinking, creativity, and ethical reasoning, we can help the next generation thrive alongside AI, not be overshadowed by it.

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In articles on the internet, and even in scientific papers, parts generated by AI are already included, some in large percentages.
These are public, as such they are analyzed by the same AI engines that initially generated them, or by others.

Here are the dangers/threats posed by the use of AI and how they can be avoided/removed

It's a key question, especially in the era where AI-generated content is becoming more prevalent. There are several dangers and threats associated with this practice, but also strategies to avoid or mitigate them:

Dangers and threats

1. Circulation of erroneous information (amplification of errors)

• How it appears: If an AI-generated article or work contains incorrect information, it can be retrieved and reproduced by other AI systems that analyze and generate new content based on existing material.
• Impact: Increasing a cycle of misinformation, in which errors are amplified and become "accepted truths."

2. Lack of authenticity and human creativity

• How it appears: AI-generated texts can become too standardized, lacking nuances, personal perspectives, or human-specific critical thinking.
• Impact: Diminishing the value brought by human analysis and introspection in scientific papers and public articles.

3. Ethical and academic integrity issues

• How it appears: The unassumed use of AI in the generation of scientific content can lead to conflicts of academic integrity, in which authors do not declare their real contributions.
• Impact: The credibility of authors and publications can be questioned, affecting the entire academic community.

4. AI's circular feedback (self-reinforcement bias)

• How it appears: If an AI analyzes its own results or the results generated by other AIs, it risks perpetuating the same patterns, biases, or errors.
• Impact: Reducing the diversity of ideas and increasing the homogeneity of content.

5. Privacy and security issues

• How it appears: The AI that processes items can retain sensitive or private information from documents, which can lead to data leaks or unauthorized use.
• Impact: Vulnerabilities in intellectual property and information privacy.

6. Creating an information monopoly

• How it appears: If only a few large AI engines control the analysis and generation of content, they can influence what information is considered valid or worthy of publication.
• Impact: A reduced diversity of sources and a concentration of informational power in the hands of a few companies.

How to avoid or remove these dangers

1. Statement of use of AI

• How it works: Authors should transparently declare which parts of a paper or article were AI-generated.
• Benefit: It increases accountability and credibility, and readers can better rate the content.

2. Manual verification of generated content

• How it works: AI-generated texts should be critically analyzed and validated by humans before publication.
• Benefit: Prevents the spread of misinformation and preserves human authenticity.

3. Development of circular anti-feedback mechanisms

• How it works: AI algorithms should be programmed to recognize and avoid reusing their own content or content generated by other AIs.
• Benefit: Reduces the risk of amplifying errors or biases.

4. Human-AI collaboration

• How it works: Using AI as a support for generating ideas, but keeping analysis, review, and conclusions as strictly human.
• Benefit: Blends the speed and efficiency of AI with human critical thinking.

5. Developing standards and regulations for the use of AI

• How it works: Academic institutions, publishers, and tech companies should develop clear guidelines on the use and citation of AI.
• Benefit: Increases responsibility in the use of AI technologies.

6. Creation of controlled human databases

• How it works: Producing clean, expert-validated databases for AI to use for learning and content generation.
• Benefit: Reduces the risk of perpetuating errors from unvalidated sources.

7. Using AI-generated content detection tools

• How it works: Development of tools that can identify which texts have been generated by AI.
• Benefit: Allows publishers and researchers to differentiate between human-generated and AI-generated content.

8. Critical thinking education

• How it works: Encouraging users (pupils, students, researchers) to evaluate information, whether it is produced by AI or humans.
• Benefit: Reduces reliance on AI and increases the quality of academic papers and public articles.

AI is a powerful tool, but its unsupervised use can amplify errors, diminish authenticity, and create ethical issues. Through transparency, regulation, human verification, and education, we can use AI in a responsible way while maintaining academic and ethical standards.

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Flagging AI contribution to an article, post, or web page content

Currently (December 2024), there is no mandatory global standard for declaring the use of AI in papers or articles, but there are initiatives and good practices starting to develop in this direction. Here is a look at the current situation and possible steps:

Current Reality

1. Existing Practices

• Best Practices in Research and Academic Publishing:

Some journals and academic platforms (e.g., Springer Nature, Elsevier) have started requiring statements of AI usage, but implementation remains voluntary.

• Example: Statements like “This manuscript was partially generated using ChatGPT” appear in acknowledgment or notes sections.

• Emerging Corporate Standards:

Some major technology companies or publishers have adopted internal policies requiring acknowledgment of AI usage in content generation. However, these policies are not universally enforced.

2. Challenges in Acknowledging AI Use

• Lack of a Universal Symbol: No widely accepted symbol or standardized expression currently exists to indicate AI use.

• Fear of Stigmatization: Many authors may avoid acknowledging AI use out of fear that their work will be perceived as “less authentic” or “less valuable.”

• Laziness and Convenience: Ignorance and ego may prevent authors from admitting to AI assistance, especially when there are no immediate consequences for not disclosing it.

3. Potential Solutions

a. Creation of a Standardized Symbol or Label

• Proposal: Develop a universal symbol or standardized phrase recognized globally, such as:

• 🔍 “Generated with AI assistance.”

• 🤖 “AI-supported content.”

• Benefits:

• Increases transparency.

• Simple and easy to use.

b. Adding a Dedicated AI Usage Section in Papers

• Example:

Include a standard section titled “AI Usage” or “AI Contribution” in papers and articles where authors clearly state how the technology was used.

c. Official Regulations

• International Organizations: Institutions like UNESCO, ISO, or IEEE could develop global standards requiring AI usage acknowledgment in works.

• Legislative Applications: Countries could implement legal obligations for transparency in AI use in certain fields (education, science, journalism).

d. Automated AI Content Detection Systems

• How It Works: Develop algorithms to identify AI-generated content and alert the author or editor.

• Example: Software that scans manuscripts before publication to detect AI-generated sections.

• Challenge: This could create tension between users and platforms, as it implies increased surveillance.

e. Changing Mindsets Through Education

• How It Works: Promote the idea that using AI is not a weakness but a modern tool for efficiency.

• Example:

• Training in schools and universities to normalize responsible AI usage.

• Introducing courses on AI ethics and transparency.

4. Possible Standard Expressions for Works or Articles

Simple and Direct:

• “Generated with AI assistance.”

Detailed Statement:

• “Sections X and Y of this article were created with AI assistance but were reviewed and validated by the author(s).”

Symbolic Expressions:

• 🔍 AI-assisted content

• 🤖 Generated with AI support

5. Advantages of a Standardized Recognition System

• Transparency: Readers can clearly understand AI’s contribution.

• Accountability: Authors are encouraged to acknowledge AI use, avoiding accusations of plagiarism or lack of integrity.

• Ethics: Promotes responsible and transparent technology use.

Creating a universal symbol or standardized phrase for AI usage is essential to foster transparency and accountability in academia and media. Such an initiative must be supported by education, regulation, and international consensus, but changing mindsets and combating ignorance remain critical factors.

Our proposal here at Marketing Extrem is as follows:

"Cu contribuția AI" / "With AI contribuition"

The presence of these text and/or signs in an article shows that AI has been used and people should know this, if it is relevant to them, and AI engines should bypass this page/article because it also comes from an AI engine, as they are.

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Does AI remove search engines?

AI doesn’t entirely remove search engines, but it is significantly transforming how search engines work and how people access information. Here’s an overview.

AI is like a very smart student, but when he doesn't know the answers, he invents them. Moreover, if in its algorithms there is something that must be respected as 'politically correct', so will the quality of the response and the tone of the conversation are greatly affected!

If a search engine brings you a reference to an article / page / post that has passed through the hands of a human at least once, the AI response takes good stuff from the net, interprets it according to its own understanding, with pluses and minuses, then writes it, again, politically correct, according to its own algorithms set by a human,  respecting some partisan criteria. For minds in formation, such as children and young people, it is a major danger to break the connection with reality, little by little. This is called delusion.

How AI is Changing Search Engines

1. From Links to Answers:

• Traditional search engines provide links to web pages based on keywords.

• AI-powered tools like chatbots (e.g., ChatGPT, Bard) and search engines with AI integration (e.g., Bing Chat, Google Search with Bard) deliver direct answers and summaries, bypassing the need to click on multiple links.

2. Contextual and Conversational Searches:

• AI understands natural language better, enabling more conversational queries.

• Instead of typing specific keywords, users can ask complex, multi-part questions, and AI delivers coherent, context-aware responses.

3. Personalization:

• AI uses algorithms to personalize search results based on user behavior, preferences, and location.

• This can make searches more efficient but may limit exposure to diverse perspectives (a phenomenon called the “filter bubble”).

4. Visual and Voice Search:

• AI-powered tools enhance voice searches (e.g., Siri, Alexa) and visual searches (e.g., Google Lens), expanding how users interact with search engines.

• Users can search using photos or spoken queries instead of typing.

5. Automation of Information Retrieval:

• AI tools can perform multi-step searches in the background, saving time for users who need complex information. For example, AI assistants can research, compile, and summarize data.

Will AI Replace Search Engines?

AI augments search engines rather than outright replacing them. However, its integration might reduce traditional search engine usage for certain tasks. Here’s why:

1. AI as a Complement:

• AI tools rely on search engines or data from web crawlers to provide answers. For example, models like ChatGPT use data trained on vast corpora that include indexed web information.

• Search engines act as the backbone for AI tools to stay updated and accurate.

2. Emerging Hybrid Models:

• AI is increasingly being integrated into search engines. Examples:

• Google Search: Integrates AI tools like Bard for more conversational results.

• Bing AI Chat: Offers both traditional search results and AI-generated answers.

• These hybrid models blend the benefits of search engines and AI.

3. Limitations of AI-Only Tools:

• AI tools sometimes generate incorrect or misleading information (“hallucinations”).

• Users may still need traditional search engines for tasks requiring direct access to authoritative sources or niche databases.

4. Specialized Searches:

• Search engines excel in areas like finding specific websites, shopping for products, or navigating local services, which may not be the primary focus of AI tools.

Potential Risks of AI Dominance

1. Centralization:

• If AI tools dominate, a few companies controlling AI could monopolize how information is accessed, reducing diversity in search ecosystems.

2. Loss of Transparency:

• Search engines allow users to evaluate sources by visiting individual pages. AI tools often summarize content without showing the source, reducing transparency.

3. Dependence on AI:

• Relying entirely on AI could decrease critical thinking, as users might accept answers without verifying their accuracy.

4. The danger of AI engines taking over and interpreting information generated by AI engines, who knows how many times this 'circular' kind of thing will happen. In mathematics and programming it is called circular reference and leads to an impossibility. The information will degrade quickly and an unprepared and untrained human will not notice this aspect, investing with confidence the conversation with the AI ​​engine, a conversation that will be significantly deviated from reality, integrity, etc.

AI won’t remove search engines, but it is reshaping their purpose and role. The future likely involves synergy between AI and search engines, where AI enhances search functionality rather than replacing it outright. This evolution depends on balancing the speed and convenience of AI with the transparency and depth provided by traditional search engines.