Learning Log #1: All About AI | Part One
What I Explored
There’s been a lot of debate online about whether AI should be banned, restricted, or heavily regulated. People point to environmental impact, misuse, and the rapid spread of harmful content as reasons to slow things down. I wanted to step back and look at AI from a broader perspective- not just generative AI like ChatGPT or Gemini, but the entire ecosystem of artificial intelligence that has existed long before these tools became popular.
Key concepts I learned…
AI is not new
A lot of people talk about AI as if it suddenly appeared in 2022, but AI has been around for decades. Businesses, researchers, and engineers have used AI systems for:
fraud detection
recommendation engines
medical diagnostics
search algorithms
robotics
predictive modeling
What AI actually is
AI- artificial intelligence- refers to technology that allows computers to simulate human intelligence. That includes:
learning from experience
recognizing patterns
solving problems
understanding languages
making decisions
Instead of being programmed step‑by‑step, AI learns from massive datasets.
Machine learning
Machine learning is the process that allows AI to learn from data. Developers feed the model huge datasets, and the system identifies patterns, relationships, and structures. Over time, it improves its predictions or outputs based on what it has learned.
AI is biased !!
AI systems learn from the data they’re trained on. If that data contains:
stereotypes
historical inequalities
skewed representation
biased language
Then the AI will absorb and repeat those patterns.
If the data is flawed, the model will be flawed too.
Why It matters
Understanding the foundations of AI helps cut through the noise in online debates. When people say “AI is dangerous,” they’re usually talking about:
generative AI misuse
deepfakes
automated cyberattacks
misinformation
privacy concerns
But AI as a whole is much bigger than that. It’s embedded in almost every modern system we use. The real challenge isn’t whether AI should exist- it’s how we design, regulate, and use it responsibly. I think a lot of other tools can be said the same.
For cybersecurity and OSINT, especially, AI is becoming a major tool. Knowing how it works (and where it fails) is pretty important for anyone learning about the field.
My thoughts
There’s a lot of fear around AI right now, and honestly, some of it is justified. People have misused it. Harmful tools do exist. Humans will always find ways to exploit a tool. Just like a lot of tools out there, you really can’t just…ban AI. This takes me back to my Capstone project, where I asked my classmates and friends what should be done about the dark web. Some people said the government should ban it. If only it were that easy. Some people said they should tighten the regulations on it, and I agree. I think that’s what should be done with some AI tools as well.
I hope to explore the different categories of AI for the next learning log.
