Kann KI die wissenschaftliche Literatur überprüfen – und herausfinden, was das alles bedeutet? | Künstliche Intelligenz könnte helfen, Forschungsergebnisse schnell zusammenzufassen. Aber es birgt Risiken.

Seed Statement:

For decades, scholars have been trying to accelerate the onerous task of compiling bodies of research into reviews. “They’re too long, they’re incredibly intensive and they’re often out of date by the time they’re written,” says Iain Marshall, who studies research synthesis at King’s College London. The explosion of interest in large language models (LLMs), the generative-AI programs that underlie tools such as ChatGPT, is prompting fresh excitement about automating the task.

Some of the newer AI-powered science search engines can already help people to produce narrative literature reviews — a written tour of studies — by finding, sorting and summarizing publications. But they can’t yet produce a high-quality review by themselves. The toughest challenge of all is the ‘gold-standard’ systematic review, which involves stringent procedures to search and assess papers, and often a meta-analysis to synthesize the results. Most researchers agree that these are a long way from being fully automated. “I’m sure we’ll eventually get there,” says Paul Glasziou, a specialist in evidence and systematic reviews at Bond University in Gold Coast, Australia. “I just can’t tell you whether that’s 10 years away or 100 years away.”

Personally, I had and still have this feeling that being able to synthesize all scientific findings related a specific field will definitely help define better research questions.