lktniloc

There’s been a lot of debate about whether AI can ever be completely safe. Personally, I don’t think so and here’s why.

1. LLMs are probabilistic, not deterministic.

AI doesn’t follow strict rules. It predicts patterns based on data. Even with the same input, slight randomness or context changes can produce different outputs — so there’s no fixed “safe” outcome.

2. Emergent and opaque reasoning.

As models get larger, their internal reasoning becomes harder to interpret. They can form complex internal patterns that even developers can’t fully explain.

3. Impossible to anticipate every scenario.

The real world is too complex for anyone to foresee all conditions an AI might face. A system that behaves correctly 99.999% of the time can still fail catastrophically in that rare edge case. Imagine the impact of failure on healthcare or critical systems.

4. Security and adversarial factors.

AI can be tricked or manipulated. Jailbreaks and prompt injections can bypass guardrails. That’s why AI safety is as much a cybersecurity issue as a technical one.

5. Unbounded autonomy risk.

When AI moves beyond generating text to taking real-world actions — sending messages, writing code, or accessing systems — unpredictability grows exponentially.

In essence:

AI can recommend, accelerate, or assist — but humans must approve, monitor, and intervene.

True AI progress isn’t about removing humans from the loop — it’s about making sure we stay firmly in control of the decisions that matter most.