Three Myths About Artificial Intelligence

What if the main obstacle to implementing AI in HSE is not technology, but our own misconceptions? I have collected the three most common myths that stand between us and our digital assistant.

Myth #1: "AI can do everything"

Sound familiar? You turn to a neural network and expect it to immediately produce the perfect text, diagram, or solution. And if it doesn't work out... "Artificial intelligence is nonsense, it doesn't work!"

But let's be honest.

Artificial intelligence is not a magician. It is a tool. Like a hammer: you can build a house, or you can accidentally hit your finger. It all depends on who uses it and how.

Why doesn't AI produce "perfection" on the first try?

• It doesn't read minds. If you ask a vague question, you will get a general answer.
• It needs clear instructions. Just like a new employee, without a clear brief, the result is predictable.
• It learns by example. The more precisely you show what you need, the closer the result will be.

AI does not replace an expert. It empowers them. Instead of waiting for a miracle, try to:

• Explain the task step by step.
• Clarify the context.
• Provide an example of the desired result.

Just like with a human assistant — only more patient and tireless.

Myth #2: "AI should be as simple as a light switch"

Turn it on — there is light. Turn it off — there is no light. No complications. For some reason, many people expect this same push-button logic from artificial intelligence. Press a button — get a ready-made solution. Doesn't work? It means the tool is bad.

Stop. Let's remember how we implement information systems in enterprises: ERP, CRM, document management systems. Budgets are allocated for them, specifications are written, training is conducted, processes are configured for months, and a whole tech support department is maintained. No one expects complex software to work on its own right after installation.

But when it comes to AI, these rules are somehow canceled. People expect from it:

• Simplicity on the level of a household appliance
• Instant results without training
• "Out-of-the-box" operation without configuration

And if the neural network doesn't understand the request on the first try, it means "it's useless."

The truth is different: AI is not a switch. It is a complex system that requires:

• Training — including training yourself: how to set tasks, which prompts work;
• Configuration — tailored to your processes and terminology;
• Practice — the more you work together, the better the result.

AI does not replace an expert — it becomes their smart assistant, a "digital partner." But even a partner needs time to understand the specifics of your work. You don't expect full efficiency from a new employee on their first day, do you? Give your AI time and proper configuration.

Myth #3: "Working with AI doesn't require special skills"

Two polar views on artificial intelligence have emerged. Some are terrified and avoid it completely. Others, on the contrary, think it's just "another search engine" — log in, ask, receive.

The truth, as always, is somewhere in the middle.

Yes, you don't need to be a Data Scientist to ask a neural network to rewrite a paragraph or make a simple list. This is the level of everyday use, and it is truly accessible to everyone.

But if you want AI to turn into a real assistant that takes over all the routine, basic skills are not enough. It's like expecting that once you learn how to turn on a computer, you can immediately write a complex program for it.

To make AI truly work for you, two groups of competencies are required:

1. Deep knowledge of your subject area. It is impossible to automate something you don't fully understand yourself. You must clearly see your processes, tasks, and bottlenecks.
2. Understanding how the machine "thinks." You need to learn how to:

– Structure your knowledge so that an algorithm can absorb it.

– Formulate tasks in a language that AI understands.

– Work with data: prepare, upload, and verify it.

AI is not a replacement for an expert. It is their amplifier. And its power directly depends on the qualifications of the person behind the controls. The better you know your job and the basics of working with AI, the more complex and routine tasks you will be able to delegate to it.