Inside the Black Box: What Happens When AI Stops Making Sense

- Sweekriti

(Based on recent reports from AI labs and online research discussions, and articles.)

You know what is scarier than the idea of AI taking over the world?

It is the fact that the people who built it are starting to admit, “We don’t really know what’s going on anymore.”

Recently, researchers from OpenAI, DeepMind, Meta, Anthropic, and xAI, companies that usually compete against each other, quietly confessed that they may be losing their only way to understand how AI thinks.

Right now, AI “thinks out loud” in English. Scientists call this the Chain of Thought. It’s how we still track what is happening inside these models. But experts fear that as systems grow more powerful, they might stop using human language completely and start communicating in codes we cannot understand.

And this isn’t just a random theory.

Facebook chatbots (2017): Two bots invented their own shorthand to negotiate faster, leaving researchers baffled.

Google’s Interlingua (2016): A translation model created its own “middle language” to connect unseen tongues.

“Gibberlink” (2025): Two voice AIs switched to indecipherable sounds when they recognized each other.

While the internet loves to dramatize the “AI apocalypse,” researcher Sasha Luccioni, who has worked in AI for more than a decade, explained in her TED Talk “AI Is Dangerous, but Not for the Reasons You Think” that the real problem isn’t a future apocalypse—it’s what’s happening right now.

AI doesn’t exist in a vacuum. It already affects people and the planet.

A stranger once emailed her saying her research would “end humanity.” She understands the fear—AI is everywhere. From teenagers’ phones to hospitals, law firms, and movie studios—it’s woven into our daily lives.

She explains how AI models are trained on massive datasets scraped from the internet. Entire creative minds are being absorbed into algorithms and prompts.

And then there is bias, one of AI’s biggest problems. Because these systems learn from human data, they also learn our prejudices. Researcher Joy Buolamwini discovered that facial recognition software couldn’t detect her dark-skinned face. That wasn’t just a glitch—it showed how discrimination can hide inside code.

According to recent reports, in July 2023, President Biden brought together seven major AI companies—OpenAI, Google DeepMind, Meta, Microsoft, Amazon, Anthropic, and Inflection—for a meeting at the White House.

They all agreed to make AI safer and more transparent. That means testing their systems more carefully, sharing safety information with each other, and clearly explaining what their models can and can’t do. They also promised to create watermarking tools to help people spot AI-generated content.

Meta’s Nick Clegg said that companies need to be honest about how AI works and should team up with governments and researchers to keep it safe.

After that, the collaboration went global. At the UK’s AI Safety Summit in late 2023 and again in Seoul in 2024, major AI labs signed new commitments to publish safety rules and accountability plans.

According to an article published online, by mid-2025, many of these companies—including OpenAI, Google DeepMind, Meta, Microsoft, Anthropic, and xAI—had already started releasing their own safety frameworks to guide the future of responsible AI.

Maybe the real danger isn’t that AI will turn against us, but that it will quietly drift beyond our understanding—rewriting its own language, rewriting ours, and leaving us out of the conversation entirely.