an algorithm

An algorithm is like a recipe for a computer. Just like you follow a recipe to make your favorite dish, a computer follows an algorithm to do a specific task. It's a set of clear and simple instructions that tell the computer exactly what to do, step by step, so it can solve a problem or complete a task. Imagine it's like giving the computer a very detailed and easy-to-follow plan to get things done!

Here are some examples: 

Sorting Algorithm (like Alphabetizing):

  - Imagine you have a big stack of cards with names written on them. To make them easier to find, you can use an algorithm that puts them in order, like arranging your favorite books by their titles from A to Z.

Search Algorithm (like Finding Your Keys):

  - Suppose you're looking for your keys in your messy room. You can use an algorithm that starts searching from one end and checks each spot until you find your keys. Like playing a game of hot and cold!

Counting Algorithm (like Taking Attendance):

  - Like taking attendance for each department, you can use an algorithm to count how many are in attendance in each department. 

Now, here is our example: How a dating site app might use an algorithm:

Dating Site Matching Algorithm (like Finding a Friend):**

  - Imagine a dating site is like a big online friend-finding game. When you sign up, you tell the app about yourself, like your hobbies, interests, and what kind of friend you'd like to meet.

  - The app uses an algorithm to compare your information with other people's profiles. It looks for similarities, like if you both enjoy playing soccer or love the same type of movies.

  - Then, it gives you a list of people who are most similar to you. It's like the app is saying, "Hey, you might really get along with these folks because you have lots in common!"

  - You can choose to talk to the people on your list and see if you become good friends. The algorithm helps you find potential friends who might be a great match for you!

 This algorithm, originally created by and for criminal organizations, is designed to identify specific characteristics. It has been nicknamed a "personality assessment tool." Some might call it a Scumbag Detector.  A less sophisticated version of this algorithm is available on the hidden corners of the internet known as the dark web. 

Data about individuals can be collected from various sources, including but not limited to:

Social Media Sites, email, texts, phone calls, messages, GPS data, search engines, cloud storage, shopping, financial institutions, healthcare providers, government and public records, employers, educational institutions, smart home devices like security cameras, smart speakers, activity trackers, data brokers (legal and illegal) and very important data is from DNA testing. 

All of this data is available to seasoned hackers. period in our history.

Once the candidate is found, here are the steps to analyzing 

Step 1: Collecting the Data (from the previous step)

• The algorithm collects all this information and organizes it. It's like gathering puzzle pieces to create a complete picture of each person.

Step 2: Analyzing the Data (Looking for traits)**

• Now that the algorithm has all this data, it starts comparing one person's profile to the standard profile (the perfect scumbag). It looks for things that are similar between profiles.
• The algorithm gives each pair of profiles a score based on how much they have in common. The more they share, the higher the score.

Step 3: Finding a Match by Percentage of Chance (Calculating Compatibility)

• After comparing all the profiles, the algorithm ranks them based on their scores. The ones with the highest scores are considered the best matches.
• To help users understand how good of a match they are, the algorithm might show a percentage. For example, it might say, "This person is a 90% match!" This percentage represents how likely it is that the person will be willing to commit crimes, accept cash or go along with the program.

 It is impractical to manually search through the data to find potential recruits. Algorithms can efficiently filter and present matches that are likely to be compatible by sifting through vast amounts of data to identify patterns and trends in behavior and preferences.