AI in the lab: The power of smarter questions

A couple of years ago, artificial intelligence felt like a futuristic buzzword, intriguing but not yet part of my research reality. That changed in late 2022, when ChatGPT-3.5 was released, and I thought, “Why not give it a try?”

The first time I used artificial intelligence, or AI, was at a conference. The speaker mentioned an intriguing paper, and mid-talk, I used an AI tool to query the PDF directly. To my surprise, it pulled up exactly what I needed. Since then, I’ve hit my stride with these tools, and I’m still amazed by just how much they can do.

To be clear, AI isn’t magic. It can’t replace critical thinking, deep reading or lab work. But used thoughtfully, it can make a real difference.

Today, dozens of AI tools are available, many with free accounts, and each excels in different areas. Some, like Writefull or ChatGPT, excel at fine-tuning writing by adjusting tone, tightening sentences and improving clarity. Others, like AskYourPDF or ChatPDF, can dissect dense scientific papers, pulling out key elements like the main hypothesis, sample size or even the specific statistical methods used.

I often test the same prompt across platforms just to compare interpretations. The variation is surprising, and, honestly, a little fun. Sometimes I even ask AI to merge the results into one tidy summary.

For technical tasks, AI is a serious time-saver. Need to fix a command-line error or learn a new Windows trick? It’s like having a patient, on-call tutor.

Not long ago, I needed a free C++ code editor and compiler, a search that once took over half an hour of sifting through forums and reviews. Instead, I asked ChatGPT, and within seconds, it returned a curated list of options with pros and cons. That kind of time saved adds up quickly.

In my research, I study gene expression patterns to better understand brain diseases like Alzheimer’s. Mapping gene functions once meant hours of cross-referencing databases and papers. Now, with tools like Perplexity AI or Elicit, I can get reliable, peer-reviewed summaries in seconds. And yes — I always double-check the sources. That’s key.

Of course, AI isn’t perfect. It can sound confident while being completely wrong. It reflects the biases in its training data and, if unchecked, can introduce errors into your work. That’s why I always verify outputs and stick to platforms that cite sources. I constantly remind myself that AI should assist, not replace, the scientific method.

Ultimately, AI’s value hinges on asking the right questions. Clear, well-crafted prompts yield the best answers. But it’s our critical thinking, deep reading and domain expertise that keep results grounded. With curiosity and a healthy dose of skepticism, AI becomes a powerful collaborator that amplifies rather than replaces human insight.