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Remember:

    AI uses data that you (and others) leave on the internet. Modern technology enables scammers to collect this information quickly and in large volumes. Here are the main sources:

 
 
Social Media:
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  • Your posts, likes, comments, and photos:
    For example, if you share a picture of a new gadget, AI can craft a message related to that purchase to build trust.
  • Information about friends and family:
    Who is tagged in photos, who comments on your posts, and who you interact with most frequently.
 
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Publicly Available Data:
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  • Many people leave their details on forums, blogs, or the "About Me" section on personal websites. Even old and forgotten accounts can be a source of information.
 
Data Breaches:
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  • If your email, phone number, or other personal information has been leaked, AI can use this data to create convincing attacks.
 
Behavioral Data Analysis:
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  • Scammers can track the websites you visit, what you purchase, and how you interact online.
    • Example: If you often order food online, AI might send you a fake message from a "delivery service."
 
Phishing Attacks on Others:
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  • If scammers gain access to a friend's account, they can use their conversations with you to create believable messages.
 
AI as a "Detective":
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AI not only collects information but also analyzes it to create patterns of your behavior.
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  • Example: If you frequently post about fitness, AI might send you fake ads for gym memberships or workout equipment.
 
Why Does This Matter?
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  1. Trust in the Message: When a message feels personal, you’re less likely to suspect it’s a scam.
  2. Realism: By using your information, AI makes messages so realistic that they’re hard to distinguish from genuine ones.
 
How to Protect Yourself:
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  • Check your social media privacy settings and limit access to your information.
  • Be cautious about what you share online, even if it seems harmless.
  • Regularly check if your data has been compromised using breach monitoring services.

Core Components of AI

  • Machine Learning (ML): A subset of AI where systems learn from data and improve over time without explicit programming. It enables predictive modeling and decision-making.

  • Natural Language Processing (NLP): A branch of AI that allows machines to understand and process human language for communication and analysis.

  • Computer Vision: An AI field focused on enabling computers to interpret visual data like images and videos for decision-making.

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