Artificial Intelligence

[Brian Peacock]

Crumple has hacked pErvy's account!

[pErvinalia]

Old man yells at clouds.

[Brian Peacock]

Robot and AI rights are human rights.

[L'Emmerdeur]

Who would've thought that consuming pablum squirted out by LLM is less educational than using a regular search engine?

Since the release of ChatGPT in late 2022, millions of people have started using large language models to access knowledge. And it’s easy to understand their appeal: Ask a question, get a polished synthesis and move on – it feels like effortless learning.

However, a new paper I co-authored offers experimental evidence that this ease may come at a cost: When people rely on large language models to summarize information on a topic for them, they tend to develop shallower knowledge about it compared to learning through a standard Google search.

Co-author Jin Ho Yun and I, both professors of marketing, reported this finding in a paper based on seven studies with more than 10,000 participants. Most of the studies used the same basic paradigm: Participants were asked to learn about a topic – such as how to grow a vegetable garden – and were randomly assigned to do so by using either an LLM like ChatGPT or the “old-fashioned way,” by navigating links using a standard Google search.

No restrictions were put on how they used the tools; they could search on Google as long as they wanted and could continue to prompt ChatGPT if they felt they wanted more information. Once they completed their research, they were then asked to write advice to a friend on the topic based on what they learned.

The data revealed a consistent pattern: People who learned about a topic through an LLM versus web search felt that they learned less, invested less effort in subsequently writing their advice, and ultimately wrote advice that was shorter, less factual and more generic. In turn, when this advice was presented to an independent sample of readers, who were unaware of which tool had been used to learn about the topic, they found the advice to be less informative, less helpful, and they were less likely to adopt it.

We found these differences to be robust across a variety of contexts.

[source]

[Brian Peacock]

"professors of marketing" eh?

[pErvinalia]

We've been gnashing teeth over climate change, thinking it will be our downfall eventually. When in reality it will be AI that will kill us off. 40-50 years of trying to fight climate change. We've barely had a couple of years to realise the threat of AI. And the rate it's improving, we might not have many more left to figure out an escape.

[pErvinalia]