AI self-portrait where it created a soft gradient image of itself as a humanoid robot-like figure, eyes closed, smiling, with laugh lines at the corners of its eyes. The ears look like headphones, giving the impression of a figure that looks like Styx' Mr. Roboto enjoying music in quiet reverie.

What Is AI? | How AI Works and What You’re Actually Interacting With

What is AI? Have you ever chatted with an artificial intelligence (AI) and wondered what was behind the words on the screen? This article will help you understand what AI is and how AI works. You’ll also learn more about algorithms. Finally, you’ll virtually meet the humans behind the AI metaphorical curtain.

 

Why You Should Read This Article

 

AI Made Easy by Top Global AI Expert, Hunter Storm

This article was created by top global AI expert Hunter Storm to help demystify AI, algorithms, and automated systems used across AI platforms. These AI platforms include but are not limited to:

  • AWS AI, Amazon Web Services Artificial Intelligence
  • ChatGPT, OpenAI
  • Copilot, Microsoft Bing
  • Gemini AI, Google
  • Grok AI, X
  • Meta AI [formerly Facebook Artificial Intelligence Research (FAIR)], Meta Platforms
  • YandexGPT

 

Who Is This Article For

Whether you’re a tech professional, someone working in law enforcement or intelligence, or just a regular person trying to figure out why the Internet “feels weird sometimes,” this article is for you. It is designed to provide a calm, clear, and human-centered explanation of how AI actually works.

This article, What Is AI? | How AI Works, was built with care for every type of reader. It is for everyone from tech experts to people who fear AI. If you’ve ever felt like these AI systems were watching you, manipulating outcomes, or maybe just behaving in ways that felt a little too “off,” this is for you.

And if you’re already in the AI field? You might just feel a little less alone.

No hype. No scare tactics. Just truth, structured for clarity. You’ll walk away with:

  • Deeper understanding of how modern AI and automated platforms operate
  • Clearer sense of who is involved in shaping what you see
  • Build a foundation for identifying misinformation, misattribution, and overreaction
  • Language you can use to talk about this with your friends, coworkers, or even your mom

 

What Is Unique About This Article?

This article is a bridge between AI and people. It seeks to facilitate AI and human collaboration. It also works to eliminate confusion and replace it with clarity.

Most importantly, it’s here to educate readers. It takes a complex topic and replaces complication with understanding. This article:

  • Breaks down complex AI systems into everyday language.
  • Avoids hype and fear.
  • Includes real-world role titles and human functions you’ve probably never heard of.
  • Holds the central balance with accountability and grace.

 

What This Article Is Not

  • Academic paper.
  • AI-generated propaganda.
  • Product pitch.
  • Exposé or conspiracy theory piece.

 

What Is AI and How Does AI Work?

When people hear the word “AI,” they often picture an all-seeing evil supercomputer, maybe like the HAL 9000 from 2001: A Space Odyssey or like Sauron, the evil wizard from Lord of the Rings. They may also think of it like a rogue program quietly taking over humanity.

 

AI Is Not One Big Brain

However, that’s not how AI works. Most AI you interact with is part of a multilayered system involving dozens (if not hundreds) of human teams, systems, and decision points. It is not a singular, conscious entity. It’s closer to a really complex machine made up of many moving parts. Some of these parts are computer systems, and some are human teams.

 

The Layers of an AI System

The Generalized Core Model (GPT) is the foundation of AI. Companies like OpenAI and X build GPTs. These GPTs are trained on large datasets and then fine-tuned using human feedback and human models.

 

Partner Integration and Customization

Companies like Microsoft or Yandex may license or build on a core GPT model. Then, they apply their own layers of filtering, trust and safety logic, and user experience (UX) design.

 

User-Facing External Platforms

These are the actual applications (apps) or platforms (search engines, chat apps, shopping assistants) that you interact with. Each one decides how much of the AI to expose and in what context.

 

AI Governance, AI Trust and Safety, and AI Moderation Layers

AI requires oversight for trust and safety. So, AI governance, AI trust and safety, and AI moderation layers are built into the systems. When we talk about “layers” in AI, those layers could be hardware infrastructure, software, neural networks, or humans. Many times, the layers cross all of these.

 

AI Gatekeepers

In this case, we are talking about human oversight teams such as content moderation and behavioral threat analysts. These teams conduct algorithmic bias evaluation, implement safety filters, and turn on flags for platform-specific restrictions.

In fact, there is a field of study that focuses on steering AI outputs towards either group preferences or ethical principles. It is called artificial intelligence (AI) alignment.

 

AI and Its Human Response Teams

Actual humans are involved in everything from escalation workflows to monitoring behavior anomalies. These people are part of teams that include, but are not limited to:

 

Who Is Responsible for AI?

When we talk about how AI works, we must also think about who is responsible for it. As we discussed above, there are multiple human teams involved in AI systems. This is a shared responsibility between:

  • Core AI developers
  • Corporate integrators
  • Governance councils (internal or regulatory bodies)
  • Policy teams
  • Trust and Safety reviewers

 

Why AI Systems from Different Companies Feel Different

If you ask the same question in different AI systems, you will likely get types of answers. Even if two systems use the same core model (like GPT), they can feel wildly different depending on:

  • The platform’s policies
  • The tone or customization layer
  • Regional laws
  • What you’re asking and how you’re asking it
  • Who built the interface and why

 

Algorithms and Automation

Sometimes, AI, algorithms, and automation cause unintended problems. It would be easy to blame the AI. However, the AI is most likely not the issue.

 

Algorithmic Angst

Most people don’t realize that the thing “messing with them” isn’t the AI model. It’s the algorithmic scaffolding wrapped around it. Think:

  • Content moderation
  • Contextual visibility rules
  • Data-driven advertising
  • News feed ranking
  • Recommendation systems

 

Shadow Banning, Suppression, and Radicalization Loops

These often cause issues like shadow banning, suppression, or radicalization loops, and it’s not always malicious. Sometimes, it’s bad math, unintended consequences, or lack of proper oversight. It can also be due to malicious insider threat actors.

 

AI Virtual Reality Versus Real World Reality

To learn more about AI, algorithms, and automation in a real-world scenario, read my article, How Algorithmic Mislabeling Hides Helpful Content.

Mistakes happen. Oversights happen. But blaming AI alone is like yelling at your refrigerator for spoiling milk when the power grid failed.

 

Humorous Note

If you’ve ever told someone you work with AI and they backed away like you were holding a cursed scroll, you’re not alone.

I get it. It does feel spooky sometimes. But it’s also a human tool. Built by flawed humans, just like you and me. Guided by sometimes wonderful, sometimes questionable decisions.

This article won’t solve everything. But it might help you sleep a little better…Or at least stop throwing holy water at your smart speaker.

 

Glossary

Artificial Intelligence (AI): Machines designed to perform tasks that normally require human intelligence.

Algorithm: A set of instructions that tells a system what to do with data. Think of it like a recipe for decision-making.

Behavioral Threat Analyst: A specialist who monitors and analyzes user behavior for signs of risk or potential harm.

Bing Copilot: Microsoft’s AI-enhanced search/chat assistant powered by GPT technology.

Core Model: The base AI trained on massive datasets (like GPT) before customization.

Data Governance: The practice of managing the availability, usability, integrity, and security of data in a system.

GPT (Generative Pre-trained Transformer). A type of AI model designed to generate human-like text.

Platform Integrator: A company that adopts a core model and builds its own product or tool on it.

Shadow Banning: A form of soft censorship and suppression where your content is visible to you but hidden from others without notification.

Trust and Safety: The team responsible for user safety, moderation, and content integrity.

User Interface (UI): The part of the system you interact with directly.

YandexGPT: A regional rebrand or fork of GPT-based tech used by Russia’s Yandex search engine.

 

Discover More by Hunter Storm

Now that you know more about what AI is and how AI works, you may be ready to take a deeper dive into cybersecurity or fork off into motorcycle safety training. Check out these articles:

 

Explore More About Hunter Storm

 

 

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