Using AI in academic research

I’ve formulated a theory on the difference between working with search-engines vs. working with AI in academic research. It has often frustrated me how AI is ‘dumb’ and won’t give you the relevant information until you dig into the material and ask leading questions again and again, having knowledge in the field so you’re able to lead AI to give you relevant, intelligent and well-formulated answers.

I had a chat with ChatGPT about my theory on search vs. AI and the result was this sidebar from a conversation about democratic theory. I hope you’ll enjoy it as much as I did.

Sidebar: From Strings to Questions – A Netizen Theory of AI vs. Search Engines

In the evolving landscape of digital epistemology, a subtle but profound shift has emerged in the way we engage with knowledge systems. This shift can be captured in a deceptively simple observation:

“Search engines are about finding the right string to get a list of answers. AI is about asking the right question to get the answer you’re looking for.”

This insight highlights a transition from retrieval logic to dialogical logic. In traditional search systems, the user must formulate precise keywords or Boolean strings to locate a series of resources — a task grounded in navigation and filtration. The value lies in the quality of the indexing and the user’s capacity to efficiently identify relevance. Out of the list of possible answers, the user selects the most appropriate answer.

In contrast, interaction with generative AI tools represents a conversational epistemic model, where the outcome is shaped not only by the prompt but by the user’s iterative engagement with the system. Here, asking the “right question” becomes an intellectual skill, akin to Socratic inquiry or scientific hypothesis formulation.

The result is a reconfiguration of the user’s role: from hunter of static answers to co-constructor of knowledge artifacts. This dialogical approach blurs the line between research tool and interlocutor. It also surfaces new questions about agency, authorship, and the ethics of collaboration in academic and creative work.

Far from being a passive search function, AI becomes a dynamic interlocutor — one that challenges us to frame, refine, and reimagine the way we ask and the way we know.

This sidebar is part of a larger research project exploring democracy, techno-capitalism, and the responsible integration of AI in academic inquiry.